ORCID Profile
0000-0002-5108-4828
Current Organisations
Shanghai Astronomical Observatory, Chinese Academy of Sciences
,
Henan Polytechnic University
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Publisher: Elsevier BV
Date: 12-2014
Publisher: Elsevier BV
Date: 09-2015
Publisher: Elsevier BV
Date: 08-2021
Publisher: IEEE
Date: 07-2016
Publisher: Springer Science and Business Media LLC
Date: 30-03-2020
DOI: 10.1186/S40562-020-00154-8
Abstract: The soil freeze/thaw processes have a significant impact on the surface energy and moisture balance, which play a key role in ecosystem ersity and productivity. The air-/space-borne Global Navigation Satellite System (GNSS)-Reflectometry (GNSS-R) is a bistatic radar with receiving power as the Delay Doppler Map (DDM), which may monitor soil freeze/thaw processes. However, the scattering mechanism of monitoring soil freeze/thaw processes by GNSS-R DDM is not clear. In this paper, it is the first time to simulate full-polarization GNSS-R Delay-Doppler-Map (DDM) for bare soil freeze/thaw process, not only the linear polarization but also the circular polarizations. As the bare soil freeze/thaw process occurs, the corresponding DDM variations are able to present by this simulator. Other geophysical parameters, such as soil moisture and surface roughness, are also two important parameters affecting the final GNSS-R receiver power and their effects on DDM are also presented by the simulator. This simulator can be a potentially efficient tool for data analysis and interoperation of GNSS-R received power as well as the in situ experimental design.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Springer Netherlands
Date: 2014
Publisher: Elsevier BV
Date: 02-2023
Publisher: Elsevier BV
Date: 09-2014
Publisher: IEEE
Date: 08-2014
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2015
Publisher: Wiley
Date: 03-05-2021
Publisher: Elsevier BV
Date: 12-2015
Publisher: Springer Science and Business Media LLC
Date: 2021
Publisher: Springer Berlin Heidelberg
Date: 26-07-2012
Publisher: Elsevier BV
Date: 30-05-2007
Publisher: MDPI AG
Date: 03-02-2021
DOI: 10.3390/RS13040545
Abstract: The plasmasphere is located above the ionosphere with low-energy plasma, which is an important component of the solar-terrestrial space environment. As the link between the ionosphere and the magnetosphere, the plasmasphere plays an important role in the coupling process. Therefore, it is of great significance to study the electron content variation of the plasmasphere for the solar-terrestrial space environment. Nowadays, the topside global positioning system (GPS) observations on Low Earth Orbit (LEO) satellites provide a unique opportunity to estimate and study variations in the plasmasphere. In this paper, the plasmaspheric total electron content (PTEC) is estimated, and its long-term variations are studied from topside GPS observations onboard the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC). The PTEC in the daytime is higher than that in the nighttime, with the peak between 14:00 and 17:00 in the magnetic local time, while the minimum value of PTEC in the belt appears between 3:00 and 6:00 in the magnetic local time before sunrise. For seasonal variations, the PTEC is the highest in spring of the northern hemisphere and the lowest in summer of the northern hemisphere regardless of the state of the solar activity. The long-term variation in PTEC is further analyzed using 11-year COSMIC GPS observation data from 2007 to 2017. A high correlation between PTEC and the F10.7 indices is found. Particularly in the geomagnetic high-latitude region during the daytime, the correlation coefficient reaches 0.93. The worst case occurs during the nighttime in the geomagnetic middle-latitude region, but the correlation coefficient is still higher than 0.88. The long-term variations of plasmaspheric TEC are mainly related to the solar activity.
Publisher: Elsevier BV
Date: 06-2019
Publisher: Springer Science and Business Media LLC
Date: 11-2012
Publisher: Springer Science and Business Media LLC
Date: 15-03-2008
Publisher: Cambridge University Press (CUP)
Date: 23-08-2006
DOI: 10.1017/S0373463306003821
Abstract: Nowadays GPS is widely used to monitor the ionosphere. However, the current results from ground-based GPS observations only provide some information on the horizontal structure of the ionosphere, and are extremely restricted in mapping its vertical structure. In this paper, tomography reconstruction technique was used to image 3D ionospheric structure with ground-based GPS. The first result of the 3D images of the ionospheric electron density distribution in South Korea has been generated from the permanent Korean GPS Network (KGN) data. Compared with the profiles obtained by independent ionosondes at or near the GPS receiver stations, the electron density profiles obtained by the GPS tomographic construction method are in better agreement, showing the validity of the GPS ionospheric tomographic reconstruction. It has also indicated that GPS-based 3D ionospheric mapping has the potential to complement other expensive observing techniques in ionospheric mapping, such as ionosondes and radar.
Publisher: IEEE
Date: 06-2018
Publisher: MDPI AG
Date: 04-01-2018
DOI: 10.3390/RS10010062
Publisher: MDPI AG
Date: 27-11-2022
DOI: 10.3390/W14233862
Abstract: Accurate shallow water bathymetry data are essential for coastal construction and management, marine traffic, and shipping. With the development of remote sensing satellites and sensors, the satellite-derived bathymetry (SDB) method has been widely used for bathymetry in shallow water areas. However, traditional satellite bathymetry requires in-situ bathymetric data. Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) with the advanced high-resolution topographic laser altimeter system (ATLAS) provides a new technical tool and makes up for the shortcomings of traditional bathymetric methods in shallow waters. In this study, a new method is proposed to automatically detect photons reflected from the shallow seafloor with ICESat-2 altimetry data. Two satellite bathymetry models were trained, to obtain shallow water depth from Sentinel-2 satellite images. First, sea surface and seafloor signal photons from ICESat-2 were detected in the Oahu (in the U.S. Hawaiian Islands) and St. Thomas (in the U.S. Virgin Islands) s ling areas, to obtain water depths along the surface track. The results show that the RMSE is between 0.35 and 0.71 m and the R2 is greater than 0.92, when compared to the airborne LiDAR bathymetry (ALB) data in the field. Second, the ICESat-2 bathymetric points from Oahu Island are used to train the Back Propagation (BP) neural network model and obtain the SDB. The RMSE is between 0.97 and 1.43 m and the R2 is between 0.90 and 0.96, which are better than the multi-band ratio model with RMSE of 1.03–1.57 m and R2 of 0.89–0.95. The results show that the BP neural network model can effectively improve bathymetric accuracy, when compared to the traditional multi-band ratio model. This approach can obtain shallow water bathymetry more easily, without the in-situ bathymetric data. Therefore, it extends to a greater extent with the free ICESat-2 and Sentinel-2 satellite data for bathymetry in shallow water areas, such as coastal, island and inland water bodies.
Publisher: Elsevier BV
Date: 08-2013
Publisher: Elsevier BV
Date: 11-2018
Publisher: InTech
Date: 29-05-2013
DOI: 10.5772/51536
Publisher: Springer Science and Business Media LLC
Date: 29-07-2019
Publisher: Cambridge University Press (CUP)
Date: 08-2012
DOI: 10.1017/S1743921312017139
Abstract: The total electron content (TEC) is an important parameters in the Earth's ionosphere, related to various space weather and solar activities. However, understanding of the complex ionospheric environments is still a challenge due to the lack of direct observations, particularly in the polar areas, e.g., Antarctica. Now the Global Positioning System (GPS) can be used to retrieve total electron content (TEC) from dual-frequency observations. The continuous GPS observations in Antarctica provide a good opportunity to investigate ionospheric climatology. In this paper, the long-term variations and fluctuations of TEC over Antarctica are investigated from CODE global ionospheric maps (GIM) with a resolution of 2.5°×5° every two hours since 1998. The analysis shows significant seasonal and secular variations in the GPS TEC. Furthermore, the effects of TEC fluctuations are discussed.
Publisher: Elsevier BV
Date: 09-2022
Publisher: IEEE
Date: 08-2016
Publisher: IEEE
Date: 08-2016
Publisher: IEEE
Date: 08-2016
Publisher: MDPI AG
Date: 29-03-2021
DOI: 10.3390/RS13071296
Abstract: The Global Navigation Satellite System (GNSS) plays an important role in retrieving high temporal–spatial resolution precipitable water vapor (PWV) and its applications. The weighted mean temperature (Tm) is a key parameter for the GNSS PWV estimation, which acts as the conversion factor from the zenith wet delay (ZWD) to the PWV. The Tm is determined by the air pressure and water vapor pressure, while it is not available nearby most GNSS stations. The empirical formular is often applied for the GNSS station surface temperature (Ts) but has a lower accuracy. In this paper, the temporal and spatial distribution characteristics of the coefficients of the linear Tm-Ts model are analyzed, and then a piecewise-linear Tm-Ts relationship is established for each GPS station using radiosonde data collected from 2011 to 2019. The Tm accuracy was increased by more than 10% and 20% for 86 and 52 radiosonde stations, respectively. The PWV time series at 377 GNSS stations from the infrastructure construction of national geodetic datum modernization and Crustal Movement Observation Network of China (CMONC) were further obtained from the GPS observations and meteorological data from 2011 to 2019. The PWV accuracy was improved when compared with the Bevis model. Furthermore, the daily and monthly average values, long-term trend, and its change characteristics of the PWV were analyzed using the high-precision inversion model. The results showed that the averaged PWV was higher in Central-Eastern China and Southern China and lower in Northwest China, Northeast China, and North China. The PWV is increasing in most parts of China, while the some PWVs in North China show a downward trend.
Publisher: IEEE
Date: 07-2017
Publisher: IEEE
Date: 08-2016
Publisher: IEEE
Date: 11-07-2021
Publisher: Springer Science and Business Media LLC
Date: 18-07-2012
Publisher: MDPI AG
Date: 2020
DOI: 10.3390/RS12010122
Abstract: Global Navigation Satellite Systems-Reflectometry (GNSS-R) has shown unprecedented advantages to sense Soil Moisture Content (SMC) with high spatial and temporal coverage, low cost, and under all-weather conditions. However, implementing an appropriated physical basis to estimate SMC from GNSS-R is still a challenge, while previous solutions were only based on direct comparisons, statistical regressions, or time-series analyses between GNSS-R observables and external SMC products. In this paper, we attempt to retrieve SMC from GNSS-R by estimating the dielectric permittivity from Fresnel reflection coefficients. We employ Cyclone GNSS (CYGNSS) data and effectively account for the effects of bare soil roughness (BSR) and vegetation optical depth by employing ICESat-2 (Ice, Cloud, and land Elevation Satellites 2) and/or SMAP (Soil Moisture Active Passive) products. The tests carried out with ICESat-2 BSR data have shown the high sensitivity in SMC retrieval to high BSR values, due to the high sensitivity of ICESat-2 to land surface microrelief. Our GNSS-R SMC estimates are validated by SMAP SMC products and the results provide an R-square of 0.6, Root Mean Squared Error (RMSE) of 0.05, and a zero p-value, for the 4568 test points evaluated at the eastern region of China during April 2019. The achieved results demonstrate the optimal capability and potential of this new method for converting reflectivity measurements from GNSS-R into Land Surface SMC estimates.
Publisher: Copernicus GmbH
Date: 02-06-2022
DOI: 10.5194/ANGEO-40-359-2022
Abstract: Abstract. In the last decades, several studies reported the tropics' expansion, but the rates of expansion are widely different. In this paper, data of 12 global navigation satellite systems radio occultation (GNSS-RO) missions from June 2001 to November 2020 with high resolution were used to investigate the possible widening of the tropical belt along with the probable drivers and impacts in both hemispheres. Applying both lapse rate tropopause (LRT) and cold point tropopause (CPT) definitions, the global tropopause height shows an increase of approximately 36 and 60 m per decade, respectively. The tropical edge latitudes (TELs) are estimated based on two tropopause height metrics, subjective and objective methods. Applying both metrics, the determined TELs using GNSS have expansive behavior in the Northern Hemisphere (NH), while in the Southern Hemisphere (SH) there are no significant trends. In the case of ECMWF Reanalysis v5 (ERA5) there are no considerable trends in both hemispheres. For the Atmospheric Infrared Sounder (AIRS), there is expansion in the NH and observed contraction in the SH. The variability of tropopause parameters (temperature and height) is maximum around the TEL locations in both hemispheres. Moreover, the spatial and temporal patterns of total column ozone (TCO) have good agreement with the TEL positions estimated using GNSS LRT height. Carbon dioxide (CO2) and methane (CH4), the most important greenhouse gases (GHGs) and the main drivers of global warming, have spatial modes in the NH that are located more poleward than that in the SH. Both surface temperature and precipitation have strong correlation with GNSS LRT height. The surface temperature spatial pattern broadly agrees with the GNSS TEL positions. In contrast, the standardized precipitation evapotranspiration index (SPEI) has no direct connection with the TEL behavior. The results illustrate that the tropics' widening rates are different from one dataset to another and from one metric to another. In addition, TEL behavior in the NH is different from that in the SH. Furthermore, the variability of meteorological parameters agrees with GNSS TEL results more than with that of other datasets.
Publisher: Springer Science and Business Media LLC
Date: 05-2004
DOI: 10.1360/03YW0113
Publisher: Elsevier BV
Date: 05-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2018
Publisher: MDPI AG
Date: 13-08-2022
DOI: 10.3390/RS14163930
Abstract: Global Navigation Satellite System (GNSS) has drawn the attention of scientists and users all over the world for its wide-ranging Earth observations and applications. Since the end of May 2022, more than 130 satellites are available for fully global operational satellite navigation systems, such as BeiDou Navigation Satellite System (BDS), Galileo, GLONASS and GPS, which have been widely used in positioning, navigation, and timing (PNT), e.g., precise orbit determination and location-based services. Recently, the refracted, reflected, and scattered signals from GNSS can remotely sense the Earth’s surface and atmosphere with potential applications in environmental remote sensing. In this paper, a review of multi-GNSS for Earth Observation and emerging application progress is presented, including GNSS positioning and orbiting, GNSS meteorology, GNSS ionosphere and space weather, GNSS-Reflectometry and GNSS earthquake monitoring, as well as GNSS integrated techniques for land and structural health monitoring. One of the most significant findings from this review is that, nowadays, GNSS is one of the best techniques in the field of Earth observation, not only for traditional positioning applications, but also for integrated remote sensing applications. With continuous improvements and developments in terms of performance, availability, modernization, and hybridizing, multi-GNSS will become a milestone for Earth observations and future applications.
Publisher: Elsevier BV
Date: 12-2020
Publisher: Elsevier BV
Date: 09-2014
Publisher: Cambridge University Press (CUP)
Date: 13-02-2015
DOI: 10.1017/S037346331500003X
Abstract: The performance of Global Positioning System and Inertial Navigation System (GPS/INS) integrated navigation is reduced when GPS is blocked. This paper proposes an algorithm to overcome the condition where GPS is unavailable. Together with a parameter-optimised Genetic Algorithm (GA), a Support Vector Regression (SVR) algorithm is used to construct the mapping function between the specific force, angular rate increments of INS measurements and the increments of the GPS position. During GPS outages, the real-time pseudo-GPS position is predicted with the mapping function, and the corresponding covariance matrix is estimated by an improved adaptive filtering algorithm. A GPS/INS integration scheme is demonstrated where the vehicle travels along a straight line and around a curve, with respect to both low-speed-stable and high-speed-unstable navigation platforms. The results show that the proposed algorithm provides a better performance when GPS is unavailable.
Publisher: Elsevier BV
Date: 09-2018
Publisher: MDPI AG
Date: 23-08-2023
DOI: 10.3390/RS15174135
Abstract: Progress toward habitat protection goals can effectively be performed using satellite imagery and machine-learning (ML) models at various spatial and temporal scales. In this regard, habitat types and landscape structures can be discriminated against using remote-sensing (RS) datasets. However, most existing research in three-dimensional (3D) habitat mapping primarily relies on same/cross-sensor features like features derived from multibeam Light Detection And Ranging (LiDAR), hydrographic LiDAR, and aerial images, often overlooking the potential benefits of considering multi-sensor data integration. To address this gap, this study introduced a novel approach to creating 3D habitat maps by using high-resolution multispectral images and a LiDAR-derived Digital Surface Model (DSM) coupled with an object-based Random Forest (RF) algorithm. LiDAR-derived products were also used to improve the accuracy of the habitat classification, especially for the habitat classes with similar spectral characteristics but different heights. Two study areas in the United Kingdom (UK) were chosen to explore the accuracy of the developed models. The overall accuracies for the two mentioned study areas were high (91% and 82%), which is indicative of the high potential of the developed RS method for 3D habitat mapping. Overall, it was observed that a combination of high-resolution multispectral imagery and LiDAR data could help the separation of different habitat types and provide reliable 3D information.
Publisher: MDPI AG
Date: 03-08-2023
DOI: 10.3390/RS15153855
Abstract: Hyperspectral images (HSIs) provide rich spectral information, facilitating many applications, including landcover classification. However, due to the high dimensionality of HSIs, landcover mapping applications usually suffer from the curse of dimensionality, which degrades the efficiency of supervised classifiers due to insufficient training s les. Feature extraction (FE) is a popular dimension reduction strategy for this issue. This paper proposes an unsupervised FE algorithm that involves extracting endmembers and clustering spectral bands. The proposed method first extracts existing endmembers from the HSI data via a vertex component analysis method. Using these endmembers, it subsequently constructs a prototype space (PS) in which each spectral band is represented by a point. Similar/correlated bands in the PS remain near one another, forming several clusters. Therefore, our method, in the next step, clusters spectral bands into multiple clusters via K-means and fuzzy C-means algorithms. Finally, it combines all the spectral bands in the same cluster using a weighted average operator to decrease the high dimensionality. The extracted features were evaluated by applying an SVM classifier. The experimental results confirmed the superior performance of the proposed method compared with five state-of-the-art dimension reduction algorithms. It outperformed these algorithms in terms of classification accuracy on three widely used hyperspectral images (Indian Pines, KSC, and Pavia Centre). The suggested technique also showed comparable or even stronger performance (up to 9% improvement) compared with its supervised competitor. Notably, the proposed method exhibited higher accuracy even when only a limited number of training s les were available for supervised classification. Using only five training s les per class for the KSC and Pavia Centre datasets, our method’s classification accuracy was higher than that of its best-performing unsupervised competitors by about 7% and 1%, respectively, in our experiments.
Publisher: Copernicus GmbH
Date: 18-02-2016
DOI: 10.5194/ANGEO-34-259-2016
Abstract: Abstract. The differential code bias (DCB) of global navigation satellite systems (GNSSs) affects precise ionospheric modeling and applications. In this paper, daily DCBs of the BeiDou Navigation Satellite System (BDS) are estimated and investigated from 2-year multi-GNSS network observations (2013–2014) based on global ionospheric maps (GIMs) from the Center for Orbit Determination in Europe (CODE), which are compared with Global Positioning System (GPS) results. The DCB of BDS satellites is a little less stable than GPS solutions, especially for geostationary Earth orbit (GEO) satellites. The BDS GEO observations decrease the precision of inclined geosynchronous satellite orbit (IGSO) and medium Earth orbit (MEO) DCB estimations. The RMS of BDS satellites DCB decreases to about 0.2 ns when we remove BDS GEO observations. Zero-mean condition effects are not the dominant factor for the higher RMS of BDS satellites DCB. Although there are no obvious secular variations in the DCB time series, sub-nanosecond variations are visible for both BDS and GPS satellites DCBs during 2013–2014. For satellites in the same orbital plane, their DCB variations have similar characteristics. In addition, variations in receivers DCB in the same region are found with a similar pattern between BDS and GPS. These variations in both GPS and BDS DCBs are mainly related to the estimated error from ionospheric variability, while the BDS DCB intrinsic variation is in sub-nanoseconds.
Publisher: Research Square Platform LLC
Date: 30-09-2022
DOI: 10.21203/RS.3.RS-2083919/V1
Abstract: Total nitrogen (TN) and total phosphorus (TP) are important indicators for water quality. However, although water quality with high accuracy can be obtained by traditional measurement methods, the cost is high and the area is limited. A single satellite remote sensing was used to retrieve water quality with larger scale, less bands and limited accuracy. In this paper, the inversion models of TN and TP are obtained and validated in the main stream of the Yangtze River by using multi-source remote sensing data. The accuracy of models from joint multi-source remote sensing data is higher than that from using a single satellite data. The correlation of TN joint inversion model can reach 0.80, and the root mean square error(RMSE) is about 0.5mg L -1 . The correlation of TP joint inversion model can reach 0.85, and RMSE is about 0.1mg L -1 . Using the models, the water quality changes are obtained and analysed in the main stream of the Yangtze River from 2019 to 2021. It is found that TN and TP in the upstream and downstream are high. In spring and autumn, the water quality is poor. The main stream of the Yangtze River mostly class III and getting better year by year. Finally, the reasons for the change of water quality are discussed with other factors. It is found that TN and TP are negatively correlated with water level, temperature and flow. The correlation between water level and water quality is higher than others and it can reach − 0.76 and − 0.64.
Publisher: Springer Science and Business Media LLC
Date: 2006
Publisher: American Geophysical Union (AGU)
Date: 22-02-2021
DOI: 10.1029/2020JA028287
Abstract: Thermospheric nitric oxide (NO) has a strong response to the energy injection, and it serves as the “natural thermostat.” Previous studies have tended to concentrate on NO radiative flux and its effectiveness on the global energy budget rather than the altitudinal dependence. In this study, measurements from TIMED/SABER (the Sounding of the Atmosphere using Broadband Emission Radiometry instrument on TIMED satellite) were used to investigate the variation of the NO radiance cooling in thermosphere as a function of altitude, latitude, and local time. Using the methods of principal component analysis and spherical harmonic regression, we have developed an empirical model to capture the most significant variation in NO radiance cooling for the altitude range 100–280 km. The model reproduced the variations of NO radiation at different latitudes and altitudes. Moreover, the integrated model NO radiative flux is in good agreement with satellite measurements with a correlation coefficient up to 0.96. This empirical model can be used to investigate the NO cooling evolution and serve as a validation tool for future physics‐based simulations.
Publisher: IEEE
Date: 21-11-2021
Publisher: Research Square Platform LLC
Date: 06-12-2022
DOI: 10.21203/RS.3.RS-2332308/V1
Abstract: Precise prediction of the extremely heavy rainstorm is still challenging due to less or low spatial-temporal measurements. Nowadays, space-borne Global Navigation Satellite System (GNSS) radio occultation (RO) provides high spatial-resolution atmospheric parameters, which may improve the prediction precision of heavy rainfalls. In this paper, the impact of GNSS radio occultation on forecasting the heavy precipitation event is assessed for the extremely massive rainfall in Henan, China, on July 20, 2021. The GNSS radio occultation data from Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2), MetOp-A/B/C, Fengyun (FY)-3C GNOS are applied for assimilation in Weather Research and Forecasting Model Data Assimilation (WRFDA) of three-dimensional framework (3DVAR) system using the local refractivity operator. Control Experiment (CNTL) and RO are designed to examine the roles of GNSS radio occultation, and RO+GNOS is conducted to further evaluate the impact of GNSS RO data onboard FY-3C on this extreme rainfall. The fractions skill score (FSS) is used to quantify the accuracy of predicted precipitation at given thresholds. The 24-h forecast result shows that the experiments with assimilating GNSS radio occultation data produce better precipitation forecasts with regard to the distribution and the amount due to more precise initial conditions of the moisture field. In general, RO and RO+GNOS have similar increments for a more accurate humidity field near Henan and more explicit water vapor channels, and thus their predictions outperform CNTL. Compared with RO and CNTL, RO+GNOS exhibits the higher marked FSSs for heavy rainfall forecast at 50 mm and 100 mm thresholds, with average advancements of 7.76% and 32.55% for the 50 mm threshold, and 10.50% and 47.39% for 100 mm threshold, respectively. For the 48-h and 72-h forecasts, three experiments exhibit similar results that RO+GNOS gives the best performance in rainfall predictions, followed by RO and then CNTL. Overall results imply that GNSS radio occultation data has a noticeable enhancement for the prediction of this record-breaking rainfall, and data from GNOS onboard FY-3C plays an indispensable role.
Publisher: American Geophysical Union (AGU)
Date: 07-2023
DOI: 10.1029/2023JB026430
Abstract: Tracking the inelastic deformation of an aquifer is important to quantify the stress experienced by the aquifer system, so that the effects of the current extraction practices are put in the context of the hydrogeological settings of a region. However, transition of elastic to inelastic deformation is hard to be monitored, particularly in the Abarkuh Plain (AP) with a dry climate. In this study, we define the confined extent of aquifer system and track the spatial evolution of inelastic deformation based on the multi‐sensor Interferometric Synthetic Aperture Radar time series in the AP in central Iran from 2003 to 2020. Our results demonstrate that many locations with experiencing no significant inelastic deformation a few years ago are now deforming inelastically, leading to partially irreversible lowering of ground surface and loss of aquifer storage. Lithological data shows that total thickness of compacted clay units controls the extent and timing of observed inelastic deformation, while joint geodetic‐well data confirms that multi‐decadal dropping of head in the confined extents of aquifer system is driving the long‐term compaction. These results show that we are possibly near a tipping point between the sustainable conditions and permanent damage to underground water resources and the current decisions have the potential to permanently change the natural resources landscape.
Publisher: MDPI AG
Date: 27-06-2020
DOI: 10.3390/RS12132073
Abstract: Rapid flood mapping is crucial in hazard evaluation and forecasting, especially in the early stage of hazards. Synthetic aperture radar (SAR) images are able to penetrate clouds and heavy rainfall, which is of special importance for flood mapping. However, change detection is a key part and the threshold selection is very complex in flood mapping with SAR. In this paper, a novel approach is proposed to rapidly map flood regions and estimate the flood degree, avoiding the critical step of thresholding. It converts the change detection of thresholds to land cover backscatter classifications. Sentinel-1 SAR images are used to get the land cover backscatter classifications with the help of Sentinel-2 optical images using a supervised classifier. A pixel-based change detection is used for change detection. Backscatter characteristics and variation rules of different ground objects are essential prior knowledge for flood analysis. SAR image classifications of pre-flood and flooding periods both take the same input to make sense of the change detection between them. This method avoids the inaccuracy caused by a single threshold. A case study in Shouguang is tested by this new method, which is compared with the flood map extracted by Otsu thresholding and normalized difference water index (NDWI) methods. The results show that our approach can identify the flood beneath vegetation well. Moreover, all required data and data processing are simple, so it can be popularized in rapid flooding mapping in early disaster relief.
Publisher: Elsevier BV
Date: 09-2012
Publisher: American Geophysical Union (AGU)
Date: 07-2023
DOI: 10.1029/2022SW003347
Abstract: The low Earth orbit (LEO) satellite provides valuable direct observations for scientific investigation of the plasmasphere, while the plasmaspheric total electron content (PTEC) with a high temporal resolution cannot be precisely estimated due to fewer LEO satellites. In this paper, a novel joint method of radial basis function neural network—Kriging (RBF‐Kr) method is designed to construct the daily PTEC model using the Constellation Observing System for Meteorology, Ionosphere and Climate Global Positioning System observations during the low (2009) and high (2013) solar activity years. Compared with the original RBF method, the RBF‐Kr method reduces the mean absolute error and root mean square error from 0.77 to 0.60 TEC unit (TECU) and 0.99 to 0.80 TECU, respectively. The correlation coefficient (Corr) increased from 0.90 to 0.94. Furthermore, daily PTEC variations show that the PTEC at low latitudes is evenly distributed during equinox periods. The South American‐Atlantic Ocean sector has a peak and trough in PTEC during the December and June solstices. A certain symmetrical distribution of PTEC is observed in the latitudinal direction, and the symcenter moves toward the summer hemisphere. The duration of extremal PTEC at 60°W is observed, which lasted up to more than 80 days around the December solstice. An obvious correlation between the solar flux and PTEC is found with up to 0.86, indicating that daily PTEC variations are mainly related to solar activities.
Publisher: Elsevier BV
Date: 11-2016
Publisher: MDPI AG
Date: 24-03-2022
Abstract: The ionospheric response and the associated mechanisms to geomagnetic storms are very complex, particularly during the February 2014 multiphase geomagnetic storm. In this paper, the low-latitude ionosphere responses and their coupling mechanisms, during the February 2014 multiphase geomagnetic storm, are investigated from ground-based magnetometers and global navigation satellite system (GNSS), and space weather data. The residual disturbances between the total electron content (TEC) of the International GNSS Service (IGS) global ionospheric maps (GIMs) and empirical models are used to investigate the storm-time ionospheric responses. Three clear sudden storm commencements (SSCs) on 15, 20, and 23 February are detected, and one high speed solar wind (HSSW) event on 19 February is found with the absence of classical SSC features due to a prevalent magnetospheric convection. The IRI-2012 shows insufficient performance, with no distinction between the events and overestimating approximately 20 TEC units (TECU) with respect to the actual quiet-time TEC. Furthermore, the median average of the IGS GIMs TEC during February 2014 shows enhanced values in the southern hemisphere, whereas the IRI-2012 lacks this asymmetry. Three low-latitude profiles extracted from the IGS GIM data revealed up to 20 TECU enhancements in the differential TEC. From these profiles, longer-lasting TEC enhancements are observed at the dip equator profiles than in the profiles of the equatorial ionospheric anomaly (EIA) crests. Moreover, a gradual increase in the global electron content (GEC) shows approximately 1 GEC unit of differential intensification starting from the HSSW event, while the IGS GIM profiles lack this increasing gradient, probably located at higher latitudes. The prompt penetration electric field (PPEF) and equatorial electrojet (EEJ) indices estimated from magnetometer data show strong variability after all four events, except the EEJ’s Asian sector. The low-latitude ionosphere coupling is mainly driven by the variable PPEF, DDEF (disturbance dynamo electric fields), and Joule heating. The auroral electrojet causing eastward PPEF may control the EIA expansion in the Asian sector through the dynamo mechanism, which is also reflected in the solar-quiet current intensity variability.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2014
Publisher: Informa UK Limited
Date: 16-07-2010
Publisher: Elsevier BV
Date: 06-2014
Publisher: Springer Singapore
Date: 2017
Publisher: IEEE
Date: 08-2016
Publisher: Springer Berlin Heidelberg
Date: 18-10-2011
Publisher: Elsevier BV
Date: 09-2015
Publisher: IEEE
Date: 08-2016
Publisher: Springer Science and Business Media LLC
Date: 19-06-2019
Publisher: Elsevier BV
Date: 07-2019
Publisher: Elsevier BV
Date: 02-2021
Publisher: American Meteorological Society
Date: 11-2014
DOI: 10.1175/JTECH-D-13-00243.1
Abstract: The Gravity Field and Steady-State Ocean Circulation Explorer (GOCE) and satellite altimetry can provide very detailed and accurate estimates of the mean dynamic topography (MDT) and geostrophic currents in China’s marginal seas, such as, the newest high-resolution GOCE gravity field model GO-CONS-GCF-2-TIM-R4 and the new Centre National d’Etudes Spatiales mean sea surface model MSS_CNES_CLS_11 from satellite altimetry. However, errors and uncertainties of MDT and geostrophic current estimates from satellite observations are not generally quantified. In this paper, errors and uncertainties of MDT and geostrophic current estimates from satellite gravimetry and altimetry are investigated and evaluated in China’s marginal seas. The cumulative error in MDT from GOCE is reduced from 22.75 to 9.89 cm when compared to the Gravity Recovery and Climate Experiment (GRACE) gravity field model ITG-Grace2010 results in the region. The errors of the geostrophic currents from GRACE are smaller than from GOCE with the truncation degrees 90 and 120. However, when the truncation degree is higher than 150, the GRACE mean errors increase rapidly and become significantly larger than the GOCE results. The geostrophic velocities based on GOCE-TIM4 have higher accuracy and spatial resolution, and the mean error is about 12.6 cm s −1 , which is more consistent with the in situ drifter’s results than using GRACE data.
Publisher: Informa UK Limited
Date: 16-07-2010
Publisher: Springer Berlin Heidelberg
Date: 2015
Publisher: InTech
Date: 11-03-2015
DOI: 10.5772/58486
Publisher: MDPI AG
Date: 24-04-2019
DOI: 10.3390/RS11080982
Abstract: Unmanned Aerial Vehicle (UAV) platforms have rapidly developed as tools for remote mapping at very high spatial resolutions. They have recently gained in popularity in many application fields owing to the versatility of platforms and sensors, ease of deployment, and a steady increase in computational power. Obtaining highly detailed topography data over very small scales is one of the more typical application domains. Here, we demonstrate this application using Structure from Motion (SfM) processing over a small river floodplain in Howard County (Maryland, USA). Evaluation of the derived bare-earth terrain model with state-of-the art LiDAR shows a trivial bias of 1.6 cm and a root mean square deviation (RMSD) of 39 cm. We then applied this terrain model to extract floodplain and river cross-section geometries of a small stream, important during high-magnitude urban flash flood events, with the aim to assess its value for floodplain inundation mapping and first order characterization of in-channel hydraulics. Initial findings agree with traditional stream and floodplain classification theory and thus show very promising results for this type of UAV usage. We expect this type of application to gain more momentum in the near future with the ever-growing importance of more detailed data in order to increase resilience to flood risk, especially in urban areas.
Publisher: MDPI AG
Date: 24-06-2020
DOI: 10.3390/RS12122034
Abstract: Ocean surface wind speed is an essential parameter for typhoon monitoring and forecasting. However, traditional satellite and buoy observations are difficult to monitor the typhoon due to high cost and low temporal-spatial resolution. With the development of spaceborne GNSS-R technology, the cyclone global navigation satellite system (CYGNSS) with eight satellites in low-earth orbit provides an opportunity to measure the ocean surface wind speed of typhoons. Though observations are made at the extremely efficient spatial and temporal resolution, its accuracy and reliability are unclear in an actual super typhoon case. In this study, the wind speed variations over the life cycle of the 2018 Typhoon Mangkhut from CYGNSS observations were evaluated and compared with European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis-5 (ERA-5). The results show that the overall root-mean-square error (RMSE) of CYGNSS versus ECMWF was 4.12 m/s, the mean error was 1.36 m/s, and the correlation coefficient was 0.96. For wind speeds lower and greater than 15 m/s, the RMSE of CYGNSS versus ECMWF were 1.02 and 4.36 m/s, the mean errors were 0.05 and 1.61 m/s, the correlation coefficients were 0.91 and 0.90, and the average relative errors were 9.8% and 11.6%, respectively. When the typhoon reached a strong typhoon or super typhoon, the RMSE of CYGNSS with respect to ERA-5 from ECMWF was 5.07 m/s the mean error was 3.57 m/s the correlation coefficient was 0.52 and the average relative error was 11.0%. The CYGNSS estimation had higher precision for wind speeds below 15 m/s, but degraded when the wind speed was above 15 m/s.
Publisher: MDPI AG
Date: 28-01-2015
DOI: 10.3390/S150202944
Publisher: MDPI AG
Date: 26-01-2019
DOI: 10.3390/RS11030250
Abstract: The current cycle slip detection methods of Global Navigation Satellite System (GNSS) were mostly proposed on the basis of assuming the ionospheric delay varying smoothly over time. However, these methods can be invalid during active ionospheric periods, e.g., high Kp index value and scintillations, due to the significant increase of the ionospheric delay. In order to detect cycle slips during high ionospheric activities successfully, this paper proposes a method based on two modified Hatch–Melbourne–Wübbena combinations. The measurement noise in the Hatch–Melbourne–Wübbena combination is minimized by employing the optimally selected combined signals, while the ionospheric delay is detrended using a smoothing technique. The difference between the time-differenced ambiguity of the combined signal and this estimated ionospheric trend is adopted as the detection value, which can be free from ionospheric effect and hold the high precision of the combined signal. Five threshold determination methods are proposed and compared to decide the cycle slip from the magnitude aspect. This proposed method is tested with triple-frequency Global Navigation Satellite System observations collected under high ionospheric activities. Results show that the proposed method can correctly detect and fix cycle slips under disturbed ionosphere.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: IEEE
Date: 07-2018
Publisher: Springer Berlin Heidelberg
Date: 26-07-2011
Publisher: MDPI AG
Date: 12-09-2021
DOI: 10.3390/S21186123
Abstract: The significant wave height (SWH) of oceans is the main parameter in describing the sea state, which has been widely used in the establishment of ocean process models and the field of navigation and transportation. However, traditional methods such as satellite radar altimeters and buoys cannot achieve SWH estimations with high spatial and temporal resolution. Recently, the spaceborne Global Navigation Satellite System reflectometry (GNSS-R) has provided an opportunity to estimate SWH with a rapid global coverage and high temporal resolution observations, particularly with the Cyclone Global Navigation Satellite System (CYGNSS) mission. In this paper, SWH was estimated using the polynomial function relationship between SWH from ERA5 and Delay-Doppler Map Average (DDMA) as well as Leading Edge Slope (LES) from CYGNSS data. Then, the SWH estimated from CYGNSS data was validated by ERA-Interim data, AVISO data, and buoy data. The results showed that the average correlation coefficient of CYGNSS SWH was 0.945, and the average RMSE was 0.257 m when compared to the ERA-Interim SWH data. The RMSE was 0.423 m and the correlation coefficient was 0.849 when compared with the AVISO SWH. The correlation coefficient with the buoy data was 0.907, and the RMSE was 0.247 m. This method can provide suitable SWH estimation data for ocean dynamics research and ocean environment prediction.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Elsevier BV
Date: 07-2021
Publisher: Springer Berlin Heidelberg
Date: 2014
Publisher: Springer Berlin Heidelberg
Date: 2014
Publisher: Elsevier BV
Date: 07-2014
Publisher: Copernicus GmbH
Date: 06-03-2018
DOI: 10.5194/ISPRS-ARCHIVES-XLII-3-W4-239-2018
Abstract: Abstract. Turkey is located in Africa-Eurasia-Saudi Arabian plate converged areas with surrounding by the Black Sea and the Mediterranean Sea. Apart from its tectonic conditions, the climate is complexly varying according to regions. As an ex le while in the northern regions floods often endanger human life, and in the middle regions, drought is a serious situation. To understand the Earth system and its temporal changes, a reliable measurement of various geophysical processes and mass redistribution is needed, which are mostly related to the regional water cycle and coupling processes associated with a mass exchange between the oceans, the lands and the atmosphere at seasonal and inter-annual timescales. Nowadays, dense and continuous GPS (Global Positioning System) observations provide direct measurements to capture such signals. In this paper, continuous GPS coordinate time series and inter-annual height variations are obtained and investigated from Turkish CORS network called TUSAGA-Active with more than 140 stations from 01 Jan. 2010 to 01 Jan. 2016 processed by GAMIT/GLOBK software. Results show significant inter-annual variations of GPS height time series with a period of about 2.8 years at most GPS stations. Furthermore, some relationship between inter-annual height and rainfall as well as ENSO index will be further investigated, indicating that inter-annual height variations are mostly related to climate changes, such as drought. These results will contribute to understand continuous GPS measurement signals in Turkey as well as applications in near-real-time geohazards estimations.
Publisher: Elsevier BV
Date: 02-2021
Publisher: Elsevier BV
Date: 07-2010
Publisher: Elsevier BV
Date: 07-2010
Publisher: Springer Science and Business Media LLC
Date: 09-03-2021
DOI: 10.1007/S10291-021-01109-Y
Abstract: The differential code biases (DCBs) of the global positioning system (GPS) receiver onboard low-Earth orbit (LEO) satellites are commonly estimated by a local spherical symmetry assumption together with the known GPS satellite DCBs from ground-based observations. Nowadays, more and more LEO satellites are equipped with GPS receivers for precise orbit determination, which provides a unique chance to estimate both satellite and receiver DCBs without any ground data. A new method to estimate the GPS satellite and receiver DCBs using a network of LEO receivers is proposed. A multi-layer mapping function (MF) is used to combine multi-LEO satellite data at varying orbit heights. First, model simulations are conducted to compare the vertical total electron content (VTEC) derived from the multi-layer MF and the reference VTEC obtained from the empirical ionosphere model International Reference Ionosphere and Global Core Plasmasphere Model. Second, GPS data are collected from five LEO missions, including ten receivers used to estimate both the satellite and receiver DCBs simultaneously with the multi-layer MF. The results show that the GPS satellite DCB solutions obtained from space-based data are consistent with ground-based solutions provided by the Centre for Orbit Determination in Europe. The proposed normalization procedure combining topside observations from different LEO missions has the potential to improve the accuracies of satellite DCBs of Global Navigation Satellite Systems as well as the receiver DCBs onboard LEO satellites, although the number of LEO missions and spatial–temporal coverage of topside observations are limited.
Publisher: IEEE
Date: 11-07-2021
Publisher: IEEE
Date: 08-2014
Publisher: Elsevier BV
Date: 09-2023
Publisher: MDPI AG
Date: 26-01-2022
DOI: 10.3390/RS14030594
Abstract: A multi-frequency Global Navigation Satellite System (GNSS) provides greater opportunities for positioning and navigation applications, particularly the BeiDou Global Navigation Satellite System (BDS-3) satellites. However, multi-frequency signals import more pseudorange channels, which introduce more multi-channel Differential Code Biases (DCBs). The satellite and receiver DCBs from the new BDS-3 signals are not clear. In this study, 9 DCB types of the new BDS-3 signals from 30-days Multi-GNSS Experiment (MGEX) observations are estimated and investigated. Compared with the DCB values provided by the Chinese Academy of Science (CAS) products, the mean bias and root mean squares (RMS) error of new BDS-3 satellite DCBs are within ±0.20 and 0.30 ns, respectively. The satellite DCBs are mostly within ±0.40 ns with respect to the product of the Deutsches Zentrum für Luft- und Raumfahrt (DLR). The four sets of constructed closure errors and their mean values are within ±0.30 ns and ±0.15 ns, respectively. The mean standard deviation (STD) of the estimated satellite DCBs is less than 0.10 ns. In particular, our estimated satellite DCBs are more stable than DCB products provided by CAS and DLR. Unlike satellite DCBs, the receiver DCBs have poor compliance and show an obvious relationship with the geographic latitude when compared to the CAS products. The STDs of our estimated receiver DCBs are less than 1.00 ns. According to different types of receiver DCBs, the distribution of STDs indicates that the coefficient of the ionospheric correction has an influence on the stability of the receiver DCBs under the ionosphere with the same accuracy level. In addition, the type of receiver shows no regular effects on the stability of receiver DCBs.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Elsevier BV
Date: 06-2017
Publisher: IEEE
Date: 25-04-2022
Publisher: InTech
Date: 03-02-2012
DOI: 10.5772/28715
Publisher: Elsevier BV
Date: 12-2017
Publisher: Elsevier BV
Date: 05-2014
Publisher: Springer Science and Business Media LLC
Date: 11-01-2017
Publisher: Cambridge University Press (CUP)
Date: 23-11-2017
DOI: 10.1017/S0373463317000893
Abstract: Positioning and Navigation (PN) of Martian rovers still faces challenges due to limited observations. In this paper, the PN feasibilities of Mars rovers based on a Gravity-aided Odometry (GO) system are proposed and investigated in terms of numeric simulations and a case study. Statistical features of the Mars gravity field are studied to evaluate the feature ersity of the background map. The Iterative Closest Point (ICP) algorithm is introduced to match gravity measurements with the gravitational map. The trajectories of Mars Exploration Rovers (MER) and Mars Gravity Map 2011 (MGM2011) are used to complete the experiments. Several key factors of GO including odometry errors, measurement uncertainties, and grid resolution of the map are investigated to evaluate their influences on the positioning ability of the system. Simulated experiments indicate that the GO method could provide an alternative positioning solution for Martian surface rovers.
Publisher: American Geophysical Union (AGU)
Date: 06-2020
DOI: 10.1029/2019JA027703
Abstract: The ionosphere is very active and complex due to photo‐ionization from the solar activity, while traditional empirical models can only give a rough description of its actual variations. Nowadays, global ionosphere maps (GIMs) derived from denser Global Navigation Satellite Systems (GNSS) world‐tracking data provide an excellent total electron content (TEC) data set for global ionospheric research and modeling. In this paper, long‐tern variations of 16‐year (2003–2018) TEC time series from GIMs are investigated by using the principal mode analysis (PCA) technique. We analyze the resulting modes in the time‐spectral domain and parameterize the main contributions in terms of solar and magnetospheric forcing, local solar time (LST), and annual variations. The results show that the TEC variability is strongly dependent on the geographical location of the Earth's magnetic field, and the Earth's diurnal rotation modulates its spatial patterns of variability. The latitudinal asymmetry in the global distribution of TEC variations is due to the effects caused by the irregular shape of the Earth's magnetic field along with its diurnal rotation. The analyses of residuals show that periodicities are correlated to the solar wind speed and magnetospheric forcing, especially those located near the southern dip pole at the night side. Furthermore, we found a TEC anomaly at about 15° from the South magnetic dip at the night side, more prominent around 52°S 155°E.
Publisher: Frontiers Media SA
Date: 06-01-2023
DOI: 10.3389/FEART.2022.931545
Abstract: The atmospheric Lamb wave induced by the Hunga Tonga (South Pacific) volcanic eruption on 15 January 2022 was recorded as atmospheric pressure fluctuations at various meteorological stations around the globe, and persisted for several days after the eruption. This Lamb wave had not been reported from any eruption in the last two decades. In the present study, the barometric pressure change induced by the Lamb wave is used as a direct proxy to quantify the volcanic explosivity index (VEI) of this eruption. An empirical equation, which is used as a function of the size of the eruption and the distance of the barometric station from the source of eruption, determined from pressure-change data that the volume of the eruption was ∼8.6 km 3 . Accordingly, the VEI of the eruption is found to be 5. The VEI derived from the barometric pressure change is consistent with the VEI estimated through seismic waveforms, and hence can be considered a first-order parameter of the eruption.
Publisher: MDPI AG
Date: 09-11-2022
DOI: 10.3390/RS14225648
Abstract: Total phosphorus (TP) and total nitrogen (TN) reflect the state of eutrophication. However, traditional point-based water quality monitoring methods are time-consuming and labor-intensive, and insufficient to estimate and assess water quality at a large scale. In this paper, we constructed machine learning models for TP and TN inversion using measured data and satellite imagery band reflectance, and verified it by in situ data. Atmospheric correction was performed on the Landsat Top of Atmosphere (TOP) data by removing the effect of the adjacency effect and correcting differences between Landsat sensors. Then, using the established model, the TP and TN patterns in Dongting Lake with a spatial resolution of 30 m from 1996 to 2021 were derived for the first time. The annual and monthly spatio-temporal variation characteristics of TP and TN in Dongting Lake were investigated in details, and the influences of hydrometeorological elements on water quality variations were analyzed. The results show that the established empirical model can accurately estimate TP with coefficient (R2) ≥ 0.70, root mean square error (RMSE) ≤ 0.057 mg/L, mean relative error (MRE) ≤ 0.23 and TN with R2 ≥ 0.73, RMSE ≤ 0.48 mg/L and MRE ≤ 0.20. From 1996 to 2021, TP in Dongting Lake showed a downward trend and TN showed an upward trend, while the summer value was much higher than the other seasons. Furthermore, the influencing factors on TP and TN variations were investigated and discussed. Between 1996 and 2003, the main contributors to the change of water quality in Dongting Lake were external inputs such as water level and flow. The significant changes in water quantity and sediment characteristics following the operation of the Three Gorges Dam (TGD) in 2003 also had an impact on the water quality in Dongting Lake.
Publisher: Springer Science and Business Media LLC
Date: 24-06-2019
Publisher: Springer International Publishing
Date: 2016
Publisher: Elsevier BV
Date: 06-2014
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2016
Publisher: American Geophysical Union (AGU)
Date: 11-2019
DOI: 10.1029/2019JA026720
Abstract: Martian lower thermospheric variations are complex due to internal surface dust storms and external solar activities. However, limited Martian measurement data are restricted to observe and understand its variations in the past. In this paper, multisatellite accelerometer‐derived densities and the Mars Climate Database are used to investigate seasonal variations, gravity waves, and coupling effects with the internal and external inputs, including Mars Global Surveyor , Mars Reconnaissance Orbiter , Mars Odyssey , and Mars Atmosphere and Volatile EvolutioN Mission . The diurnal and seasonal structures are reconstructed by the data, and the phase of the cycles is formed by solar heating/ionizing processes. Both litude and phase are impacted by surface dust activities during autumn and winter, for which density increases about 1.5–3.5 times compared to spring and summer seasons. A parameterized model that includes a newly introduced dust index is proposed to well fit and reinterpret the seasonal cycles. Furthermore, the coupling process between internal atmospheric gravity waves ( IAGWs ) and dust activities are investigated and explained. During dust storm times/seasons, the IAGWs exhibit both narrower litude peaks and deposit their energy at higher altitudes relative to “clear sky” times. The IAGWs could extend their energies into higher layers beyond exobase due to a thermospheric layer expansion(i.e., density increase) during dust seasons.
Publisher: Springer Science and Business Media LLC
Date: 11-03-2020
Publisher: MDPI AG
Date: 21-04-2022
DOI: 10.3390/RS14092002
Abstract: Global navigation satellite system (GNSS) differential code bias (DCB) is one of main errors in ionospheric modeling and applications. Accurate estimation of multiple types of GNSS DCBs is important for GNSS positioning, navigation, and timing, as well as ionospheric modeling. In this study, a novel method of multi-GNSS DCB estimation is proposed without using an ionospheric function model and global ionosphere map (GIM), namely independent GNSS DCB estimation (IGDE). Firstly, ionospheric observations are extracted based on the geometry-free combination of dual-frequency multi-GNSS code observations. Secondly, the VTEC of the station represented by the weighted mean VTEC value of the ionospheric pierce points (IPPs) at each epoch is estimated as a parameter together with the combined receiver and satellite DCBs (RSDCBs). Last, the estimated RSDCBs are used as new observations, whose weight is calculated from estimated covariances, and thus the satellite and receiver DCBs of multi-GNSS are estimated. Nineteen types of multi-GNSS satellite DCBs are estimated based on 200-day observations from more than 300 multi-GNSS experiment (MGEX) stations, and the performance of the proposed method is evaluated by comparing with MGEX products. The results show that the mean RMS value is 0.12, 0.23, 0.21, 0.13, and 0.11 ns for GPS, GLONASS, BDS, Galileo, and QZSS DCBs, respectively, with respect to MGEX products, and the stability of estimated GPS, GLONASS, BDS, Galileo, and QZSS DCBs is 0.07, 0.06, 0.13, 0.11, and 0.11 ns, respectively. The proposed method shows good performance of multi-GNSS DCB estimation in low-solar-activity periods.
Publisher: IEEE
Date: 26-09-2020
Publisher: MDPI AG
Date: 06-08-2022
DOI: 10.3390/F13081245
Abstract: Extracting street trees from mobile Light Detection and Ranging (LiDAR) point clouds is still encountering challenges, such as low extraction accuracy and poor robustness in complex urban environment, and difficulty in the segmentation of overlapping trees. To solve these problems, this paper proposed a street tree extraction and segmentation method based on spatial geometric features of object primitives. In this paper, mobile LiDAR point clouds were first segmented into object primitives based on the proposed graph segmentation method, which can release the computation burden effectively. According to the spatial geometric features of the segmented object primitives, stem points were extracted. In doing so, the robustness and accuracy for stem detecting can be improved. Furthermore, voxel connectivity analysis and in idual tree optimization were combined successively. In doing so, the neighboring trees could be separated successfully. Four datasets located in Henan Polytechnic University, China, were used for validating the performance of the proposed method. The four mobile LiDAR point clouds contained 106, 45, 76, and 46 trees, respectively. The experimental results showed that the proposed method can achieve the performance of in idual tree separation in all the four testing plots. Compared to the other three methods, the proposed method can make a good balance between the commission and omission errors and achieved the highest average F1 scores.
Publisher: Elsevier BV
Date: 09-2014
Publisher: Optica Publishing Group
Date: 30-11-2022
DOI: 10.1364/AO.472382
Abstract: The correlated k -distribution (CKD) is a fast radiative transfer model and is often used in atmospheric absorption simulation. In the paper, we apply two automatic CKD methods to satellite brightness temperature simulations from the Fengyun 4A Advanced Geostationary Radiation Imager (AGRI) in infrared channels, namely, the finding point method (FPM) and the re-optimized method (ROM). In the calculation, we used Radiative Transfer for the Television Observation Satellite Operational Vertical Sounder (RTTOV) as the comparison, and we use line-by-line (LBL) integration as the reference. Compared with LBL in the brightness temperature simulation of real profiles, the errors of FPM in 7.1 µm and 13.5 µm channels are 0.22 K, − 0.13 K for mean error and 0.3128 K, 0.2184 K for root mean square error (RMSE), respectively, which are larger than that of RTTOV, with 0.16 K, 0.02 K, 0.2144 K, and 0.1226 K, respectively. In the other channels, the results show that of ROM has the highest accuracy and RTTOV has the lowest accuracy. In general, FPM and ROM can achieve very good accuracy in satellite infrared remote sensing.
Publisher: MDPI AG
Date: 27-09-2017
DOI: 10.3390/RS9101000
Publisher: CRC Press
Date: 22-08-2023
Publisher: Elsevier BV
Date: 02-2016
Publisher: Springer Science and Business Media LLC
Date: 03-12-2019
DOI: 10.1038/S41598-019-54581-5
Abstract: Geophysical processes of the pre-earthquake activities are difficult to be determined since less pre-seismic signal is observed directly. Crustal density changes derived from the periodical terrestrial gravimetry may provide meaningful deep information for the pre-earthquake cue. In this study, the crustal density changes following the 2016 M S 6.4 Menyuan earthquake are estimated using ground-based gravity-change data from 2011 to 2015 in the northeastern Tibetan Plateau. The results show that negative density changes dominate the region between the South Longshou Mountain fault and the Daban Mountain fault except the southeast of this region (the seismic region) during 2011–2012. Positive density changes appeared in the middle crust near the epicenter during 2012–2013 and in the upper and middle crust east of the epicenter approximately 1.5 years before the earthquake (2013–2014), and then negative density changes appeared under and northeast of the epicenter approximately four months before the earthquake (2014–2015). The state of the crustal materials near the seismic region changed from convergence to expansion, in turn, indicating that the characteristics of the deep seismogenic process was corresponding to Amos Nur’s 1974 dilatancy-fluid diffusion model.
Publisher: Elsevier BV
Date: 08-2016
Publisher: American Geophysical Union (AGU)
Date: 30-12-2023
DOI: 10.1029/2022JA030457
Abstract: Typhoon is one of the major hazards in ocean coastal areas, but traditional techniques are inadequate to monitor typhoons due to limited or high‐cost observations, like radio sounding and meteorological radar. Previous studies have found that typhoons can cause ionospheric disturbances, but the relationship and characteristics are still unclear. In this paper, about 400 stations observations of the Global Positioning System (GPS) network in Taiwan are used to extract ionospheric disturbances during multiple typhoons. The detailed characteristics of the ionospheric disturbances are investigated using a fourth‐order Butterworth filter following the 2016 Nepartak, 2019 Lekima, 2019 Mitag, and 2020 Hagupit typhoons. The results show that significant ionospheric disturbances were observed during the typhoons, and the larger disturbances are mostly located 400–1200 km far from the typhoon eye. The estimated horizontal propagation velocity of the ionospheric disturbances is about 127–194 m/s. The locations of the ionospheric disturbances between the typhoon eye and the landfall site are related to the typhoon path. The azimuth distribution of the ionospheric disturbance around the typhoon eye is affected by the GPS elevation angles. At 500–700 km from the typhoon eye, the mean ionospheric disturbances are 0.17 TECU (TEC Unit) and 0.15 TECU for super typhoon Nepartak and Lekima, and 0.13 TECU and 0.18 TECU for typhoon Mitag and Hagupit. The higher the intensity of the typhoon is, the greater the magnitude of the ionospheric disturbance is.
Publisher: Springer Science and Business Media LLC
Date: 04-2014
DOI: 10.1186/BF03352561
Abstract: The results of GPS positioning depend on both functional and stochastic models. In most of the current GPS processing programs, however, the stochastic model that describes the statistical properties of GPS observations is usually assumed that all GPS measurements have the same accuracy and are statistically independent. Such assumptions are unrealistic. Although there were only a few studies modeling the effects on the GPS relative positioning, they are restricted to short baselines and short session lengths. In this paper, the stochastic modeling for IGS long-baseline positioning (with 24-hour session) is analyzed in the GAMIT software by modified stochastic models. Results show that any mis-specifications of stochastic model result in unreliable GPS baseline results, and the deviation of baseline estimations reaches as much as 2 cm in the height component. Using the stochastic model of satellite elevation angle-based cosine function, the precision of GPS baseline estimations can be improved, and the GPS baseline component is closest to the reference values, especially GPS height.
Publisher: Elsevier BV
Date: 02-2015
Publisher: MDPI AG
Date: 21-01-2020
DOI: 10.3390/RS12030356
Abstract: Mean sea surface height (MSSH) is an important parameter, which plays an important role in the analysis of the geoid gap and the prediction of ocean dynamics. Traditional measurement methods, such as the buoy and ship survey, have a small cover area, sparse data, and high cost. Recently, the Global Navigation Satellite System-Reflectometry (GNSS-R) and the spaceborne Cyclone Global Navigation Satellite System (CYGNSS) mission, which were launched on 15 December 2016, have provided a new opportunity to estimate MSSH with all-weather, global coverage, high spatial-temporal resolution, rich signal sources, and strong concealability. In this paper, the global MSSH was estimated by using the relationship between the waveform characteristics of the delay waveform (DM) obtained by the delay Doppler map (DDM) of CYGNSS data, which was validated by satellite altimetry. Compared with the altimetry CNES_CLS2015 product provided by AVISO, the mean absolute error was 1.33 m, the root mean square error was 2.26 m, and the correlation coefficient was 0.97. Compared with the sea surface height model DTU10, the mean absolute error was 1.20 m, the root mean square error was 2.15 m, and the correlation coefficient was 0.97. Furthermore, the sea surface height obtained from CYGNSS was consistent with Jason-2′s results by the average absolute error of 2.63 m, a root mean square error ( RMSE ) of 3.56 m and, a correlation coefficient ( R ) of 0.95.
Publisher: IWA Publishing
Date: 26-11-2020
DOI: 10.2166/WCC.2018.104
Abstract: Evapotranspiration (ET) variations in the Yangtze River Basin (YRB) are influenced by environmental and climate changes related to planting of crops, forest vegetation, water use and other human activities. However, it is difficult to measure ET variations and analyse influencing factors in the YRB due to lack of in-situ measurements. In the present study, the ET variations were estimated and investigated in the whole, the upper, middle and lower reaches of the YRB using the Gravity Recovery and Climate Experiment (GRACE), optical remote sensing data and hydrological models based on a water balance method, which was validated by MODerate Resolution Imaging Spectroradiometer (MODIS) observations and models. Furthermore, GRACE-ET verified the drought events in 2006 and 2011. The long-term variation rate of GRACE-ET is 0.79 mm/yr. The spatial distribution of seasonal ET variations indicates that ET is highest in summer and lowest in autumn-winter. It also shows that the completion of the Three Gorges Project has certainly increased ET. Precipitation and temperature have the largest impact on the ET variations radiation and soil moisture have moderate effects. ET variations in the middle and lower reaches are greatly affected by precipitation, and temperature plays a more important role in the upper YRB reaches.
Publisher: IEEE
Date: 26-09-2020
Publisher: Wiley
Date: 04-01-2021
Publisher: Copernicus GmbH
Date: 10-12-2015
DOI: 10.5194/ISPRSARCHIVES-XL-1-W5-67-2015
Abstract: Abstract. In this study, we focus on sea level changes along the Black Sea coast. For this purpose, at same observation period the linear trends and the components of seasonal variations of sea level change are estimated at 12 tide gauge sites (Amasra, Igneada, Trabzon-II, Sinop, Sile, Poti, Batumi, Sevastopol, Tuapse, Varna, Bourgas, and Constantza) located along the Black Sea coast and available altimetric grid points closest to the tide gauge locations. The consistency of the results derived from both observations are investigated and interpreted. Furthermore, in order to compare the trends at the same location, it is interpolated from the trends obtained at the altimetric grid points in the defined neighbouring area with a diameter of 0.125° using a weighted average interpolation algorithm at each tide gauge site. For some tide gauges such as Sevastopol, Varna, and Bourgas, it is very likely that the trend estimates are not reliable because the time-spans overlapping the altimeter period are too short. At Sile, the long-term change for the time series of both data types do not give statistically significant linear rates. However, when the sites have long-term records, a general agreement between the satellite altimetry and tide gauge time series is observed at Poti (~20 years) and Tuapse (~18 years). On the other hand, the difference of annual phase between satellite altimetry and tide gauge results is from 1.32° to 71.48°.
Publisher: Elsevier BV
Date: 08-2018
Publisher: MDPI AG
Date: 11-03-2019
DOI: 10.3390/RS11050584
Abstract: The significant wave height (SWH) of the sea is an important parameter and plays an important role in the prediction of waves and ocean dynamics. However, traditional methods, e.g., buoys or traditional remote sensing techniques such as X-band radar image have small measurement range and high cost. Recently, Global Navigation Satellite System-Reflectometry (GNSS-R) has provided a new opportunity to estimate the SWH, especially the space-borne Cyclone-GNSS (CYGNSS) launched on December 15, 2016. The GNSS-R uses the GNSS-reflected signal received by the receiver to invert ground physical parameters with all-weather, global fast coverage, high resolution, high precision, high long-term stability, rich signal sources, passive detection, and strong concealment. In this paper, the global ocean significant wave height is estimated using space-borne CYGNSS GNSS-R data for the first time though the relationship between the square root of the signal-to-noise ratio (SNR) data of CYGNSS delayed Doppler map (DDM) and the SWH. Then, the estimated significant wave height is compared with the satellite altimeter and buoy data. Compared with the AVISO SWH observation, the standard deviation value reaches 0.3080 m and the correlation coefficient reaches 0.9473 m. The correlation coefficient with the buoy SWH observation is 0.9539 m and the standard deviation is 0.2761 m. The SWH estimations from CYGNSS can provide important support in ocean shipping development, marine environmental protection, marine disaster warning and forecasting.
Publisher: Elsevier BV
Date: 2016
Publisher: MDPI AG
Date: 16-01-2022
DOI: 10.3390/RS14020401
Abstract: The study of ionospheric disturbances associated with the two large strike-slip earthquakes in Indonesia was investigated, which are West Sumatra on 2 March 2016 (Mw = 7.8), and Palu on 28 September 2018 (Mw = 7.5). The anomalies were observed by measuring co-seismic ionospheric disturbances (CIDs) using the Global Navigation Satellite System (GNSS). The results show positive and negative CIDs polarization changes for the 2016 West Sumatra earthquake, depending on the position of the satellite line-of-sight, while the 2018 Palu earthquake shows negative changes only due to differences in co-seismic vertical crustal displacement. The 2016 West Sumatra earthquake caused uplift and subsidence, while the 2018 Palu earthquake was dominated by subsidence. TEC anomalies occurred about 10 to 15 min after the two earthquakes with litude of 2.9 TECU and 0.4 TECU, respectively. The TEC anomaly litude was also affected by the magnitude of the earthquake moment. The disturbance signal propagated with a velocity of ~1–1.72 km s−1 for the 2016 West Sumatra earthquake and ~0.97–1.08 km s−1 for the 2018 Palu mainshock earthquake, which are consistent with acoustic waves. The wave also caused an oscillation signal of ∼4 mHz, and their azimuthal asymmetry of propagation confirmed the phenomena in the Southern Hemisphere. The CID signal could be identified at a distance of around 400–1500 km from the epicenter in the southwestern direction.
Publisher: Springer Berlin Heidelberg
Date: 2015
Publisher: Elsevier BV
Date: 2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: IEEE
Date: 07-2019
Publisher: Springer Science and Business Media LLC
Date: 24-07-2023
DOI: 10.1186/S43020-023-00113-6
Abstract: Ice, snow, and liquid water on the surface of the Earth exert downward force onto the solid earth and deform the lithosphere typically in seasonal timescale. Space techniques, such as Global Navigation Satellite System (GNSS), made it possible to directly measure subtle displacements caused by loading. We can also observe such loads with time-variable gravity using gravity recovery and climate experiment satellites. These techniques made surface loads an attracting scientific target of modern geodesy. In this paper we briefly review the history of geophysical studies of surface loads through geodetic observations of crustal deformation and time-variable gravity. We also review advanced topics such as short-term crustal deformation due to severe meteorological episodes and monitoring of terrestrial water storages. We also present a few related topics such as the change of the obliquity of the Earth due to loads and artificial crustal subsidence signals caused by snow accretion onto GNSS antenna radomes.
Publisher: Elsevier BV
Date: 2022
Publisher: IEEE
Date: 06-2013
Publisher: MDPI AG
Date: 03-11-2021
DOI: 10.3390/RS13214432
Abstract: The Moon-Based Earth Radiation Observatory (MERO) is a new platform, which is expected to advance current Earth radiation budget (ERB) research with better observations. For the instrument design of a MERO system, ascertaining the spatial resolution and s ling scheme is important. However, current knowledge about this is still limited. Here we proposed a simulation method for the MERO-measured Earth top of atmosphere (TOA) outgoing shortwave radiation (OSR) and outgoing longwave radiation (OLR) fluxes and constructed the “true” Earth TOA OSR and OLR fluxes based on the Clouds and Earth’s Radiant Energy System (CERES) data. Then we used them to reveal the effects of spatial resolution and temporal scheme (s ling interval and the temporal s ling sequence) on the measurement error of a MERO. Our results indicate that the spatial s ling error in the unit of percentage reduces linearly as the spatial resolution varies from 1000 km to 100 km the rate is 2.5%/100 km for the Earth TOA OSR flux, which is higher than that (1%/100 km) of the TOA OLR flux. Besides, this rate becomes larger when the spatial resolution is finer than 40 km. It is also demonstrated that a s ling temporal sequence of starting time of 64 min with a s ling interval of 90 min is the optimal s ling scheme that results in the least temporal s ling error for the MERO system with a 40 km spatial resolution, note that this conclusion depends on the temporal resolution and quality of the data used to construct the “true” Earth TOA OSR and OLR fluxes. The proposed method and derived results in this study could facilitate the ascertainment of the optimal spatial resolution and s ling scheme of a MERO system under certain manufacturing budget and measurement error limit.
Publisher: Elsevier BV
Date: 12-2020
Publisher: Springer Science and Business Media LLC
Date: 13-07-2017
Publisher: Elsevier BV
Date: 07-2013
Publisher: Elsevier BV
Date: 12-2019
Publisher: Hindawi Limited
Date: 04-08-2019
DOI: 10.1155/2019/4780143
Abstract: Carrying global positioning system (GPS) radio occultation (RO) receiver, Chinese meteorological satellite Fengyun-3C (FY-3C) was launched on September 23, 2013, which provides new observation data for observations and studies of weather and climate change. In this paper, the results of FY-3C GPS RO atmospheric sounding are presented for the first time, including high-order ionospheric correction, atmospheric parameters estimation, and evaluation by COSMIC and radiosonde observations as well as applications in estimating gravity wave activities. It is found that the effect of the ionospheric correction residual on the phase delay is below 20 mm, which has minimal impact on bending angle estimation and generates differences of about 1 K in the average temperature profile. The difference between FY-3C and COSMIC temperatures at all heights is within 1°C, and the tropopause temperature and height have a good consistency. Deviations from Radiosonde measurements are within 2°C, and the tropopause temperature and height results also have a strong consistency. Furthermore, global gravity wave potential energy is estimated from FY-3C GPS RO, exhibiting similar behavior to results derived from COSMIC radio occultation measurements. The mean value of the gravity wave potential energy near the equator is 10 J/kg and decreases toward the two poles while in the northern hemisphere, it is stronger than that in the southern hemisphere.
Publisher: Elsevier BV
Date: 12-2013
Publisher: Springer Science and Business Media LLC
Date: 09-09-2019
Publisher: Wiley
Date: 16-10-2020
Publisher: Elsevier BV
Date: 02-2017
Publisher: Elsevier BV
Date: 07-2013
Publisher: Elsevier BV
Date: 09-2020
Publisher: American Geophysical Union (AGU)
Date: 2017
DOI: 10.1002/2016JA023727
Publisher: Copernicus GmbH
Date: 23-04-2014
DOI: 10.5194/ISPRSARCHIVES-XL-4-117-2014
Abstract: Abstract. Martian mineral detection and mapping can provide important information and constraints on Martian aqueous history, which can be used to assess the potential habitability of Mars. The key parameters to Martian aqueous alteration are the depth and extent of the Martian hydrous mineral. Therefore, it is important to know detailed minerals and chemical induction of the existence of water on the Martian surface at past or present. The Jezero crater located in the Nili Fossae region of Mars is the once-flooded crater, which has rich fan-delta deposit clays. It is a good case to study the clays and mineral components at Jezero crater, so as to know the geogloical processes and evolution on Mars. The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) aboard the Mars Reconnaissance Orbiter (MRO) is a visible and near infrared spectrometer with enhanced spectral resolution, which provides an opportunity to map detailed and large-area mineralogy on Mars. In this paper, CRISM nearinfrared spectral data are analyzed using the mixture tuned filtering (MTMF) along with spectral angle mapper (SAM), and mineral components at Martian Jezero region are recognized, including the phyllosilicate, carbonate, nitrates and tectosil. Some detailed characteristics and implications of minerals at Martian Jezero crater are further studied and discussed, including implications on Martian climate change and geological evolution.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2016
Publisher: Wiley
Date: 31-12-2020
Publisher: IEEE
Date: 07-2012
Publisher: MDPI AG
Date: 07-07-2018
DOI: 10.3390/RS10071083
Publisher: IEEE
Date: 07-2012
Publisher: American Geophysical Union (AGU)
Date: 09-2014
DOI: 10.1002/2014JA019825
Publisher: MDPI AG
Date: 06-07-2022
DOI: 10.3390/RS14143262
Abstract: The reflection of Global Navigation Satellite Systems (GNSS) signals, namely GNSS-Reflectometry (GNSS-R), has recently proven to be able to monitor land surface properties in the microwave spectrum, at a global scale, and with very low revisiting time. Moreover, this new technique has numerous additional advantages, including low cost, low power consumption, lightweight and small payloads, and near real-time massive data availability, as compared to conventional monostatic microwave remote sensing. However, the GNSS-R surface reflectivity values estimated through the bistatic radar equation, and the Fresnel coefficients have shown a lack of coincidence with real surface reflectivity data, mostly due to calibration issues. Previous studies have attempted to avoid this matter with direct regression methods between uncalibrated GNSS-R reflectivity data and external soil moisture content (SMC) products. However, calibration of GNSS-R reflectivity used in traditional inversion models is still a challenge, such as those to estimate SMC, freeze/thaw, or biomass. In this paper, a successful procedure for GNSS-R reflectivity calibration is established using data from the CYGNSS (Cyclone GNSS) constellation. The scale and bias parameters are estimated from the theoretical dielectric properties of water and dry sand, which are well-known and empirically validated values. We employ four calibration areas that provide maximum range limits of reflectivity, such as deserts and wetlands. The CYGNSS scale factor and the bias parameter resulted in a = 3.77 and b = 0.018, respectively. The derived scale and bias parameters are applied to the CYGNSS dataset, and the retrieved SMC values through the Fresnel reflection coefficients are in excellent agreement with the Soil Moisture Active Passive (SMAP) SMC product. Then, the SMAP SMC is used as a reference true value, and provides a standard linear regression with an R-square coefficient of 0.803, a root mean square error (RMSE) of 0.084, and a Pearson’s correlation coefficient of 0.896.
Publisher: Elsevier BV
Date: 03-2022
Publisher: MDPI AG
Date: 14-07-2022
DOI: 10.3390/RS14143382
Abstract: Medium-resolution remote sensing satellites have provided a large amount of long time series and full coverage data for Earth surface monitoring. However, the different objects may have similar spectral values and the same objects may have different spectral values, which makes it difficult to improve the classification accuracy. Semantic segmentation of remote sensing images is greatly facilitated via deep learning methods. For medium-resolution remote sensing images, the convolutional neural network-based model does not achieve good results due to its limited field of perception. The fast-emerging vision transformer method with self-attentively capturing global features well provides a new solution for medium-resolution remote sensing image segmentation. In this paper, a new multi-class segmentation method is proposed for medium-resolution remote sensing images based on the improved Swin UNet model as a pure transformer model and a new pre-processing, and the image enhancement method and spectral selection module are designed to achieve better accuracy. Finally, 10-categories segmentation is conducted with 10-m resolution Sentinel-2 MSI (Multi-Spectral Imager) images, which is compared with other traditional convolutional neural network-based models (DeepLabV3+ and U-Net with different backbone networks, including VGG, ResNet50, MobileNet, and Xception) with the same s le data, and results show higher Mean Intersection Over Union (MIOU) (72.06%) and better accuracy (89.77%) performance. The vision transformer method has great potential for medium-resolution remote sensing image segmentation tasks.
Publisher: Elsevier BV
Date: 10-2021
Publisher: Elsevier BV
Date: 2022
DOI: 10.2139/SSRN.4220561
Publisher: Cambridge University Press (CUP)
Date: 06-02-2017
DOI: 10.1017/S0373463316000874
Abstract: The precise autonomous navigation for deep space exploration by combination of multi-source observation data is a key issue for probe control and scientific applications. In this paper, the performance of an integrated Optical Celestial Navigation (OCN) and X-ray Pulsars Autonomous Navigation (XNAV) system is investigated for the orbit of Mars Pathfinder. Firstly, OCN and XNAV single systems are realised by an Unscented Kalman Filter (UKF). Secondly, the integrated system is simulated with a Federated Kalman Filter (FKF), which can do the information fusion of the two subsystems of UKF and inherits the advantages of each subsystem. Thirdly, the performance of our system is evaluated by analysing the relationship between observation errors and navigation accuracy. The results of the simulation experiments show that the biases between the nominal and our calculated orbit are within 5 km in all three axes under complex error conditions. This accuracy is also better than current ground-based techniques.
Publisher: Elsevier BV
Date: 11-2022
Publisher: Springer International Publishing
Date: 2014
Publisher: IEEE
Date: 07-2016
Publisher: Elsevier BV
Date: 2023
DOI: 10.2139/SSRN.4500573
Publisher: IEEE
Date: 21-11-2021
Publisher: IEEE
Date: 07-2019
Publisher: MDPI AG
Date: 31-08-2020
DOI: 10.3390/RS12172816
Abstract: Ocean bottom seismometer (OBS) can record both pressure and displacement data by modern marine seismic acquisitions with four-component (4C) sensors. Elastic full-waveform inversion (EFWI) has shown to recover high-accuracy parameter models from multicomponent seismic data. However, due to limitation of the standard elastic wave equation, EFWI can hardly simulate and utilize the pressure components. To remedy this problem, we propose an elastic full-waveform inversion method based on a modified acoustic-elastic coupled (AEC) equation. Our method adopts a new misfit function to account for both 1C pressure and 3C displacement data, which can easily adjust the weight of different data components and eliminate the differences in the order of magnitude. Owing to the modified AEC equation, our method can simultaneously generate pressure and displacement records and avoid explicit implementation of the boundary condition at the seabed. Besides, we also derive a new preconditioned truncated Gauss–Newton algorithm to consider the Hessian associated with ocean bottom seismic 4C data. We analyze the multiparameter sensitivity kernels of pressure and displacement components and use two numerical experiments to demonstrate that the proposed method can provide more accurate multiparameter inversions with higher resolution and convergence rate.
Publisher: Elsevier BV
Date: 09-2014
Publisher: InTech
Date: 29-05-2013
DOI: 10.5772/51698
Publisher: Springer Netherlands
Date: 31-08-2013
Publisher: Elsevier BV
Date: 04-2019
Publisher: Springer Netherlands
Date: 31-08-2013
Publisher: CRC Press
Date: 22-08-2023
Publisher: Springer Netherlands
Date: 31-08-2013
Publisher: Springer Netherlands
Date: 31-08-2013
Publisher: MDPI AG
Date: 26-01-2021
DOI: 10.3390/RS13030427
Abstract: Harmful algal blooms (hereafter HABs) pose significant threats to aquatic health and environmental safety. Although satellite remote sensing can monitor HABs at a large-scale, it is always a challenge to achieve both high spatial and high temporal resolution simultaneously with a single earth observation system (EOS) sensor, which is much needed for aquatic environment monitoring of inland lakes. This study proposes a multi-source remote sensing-based approach for HAB monitoring in Chaohu Lake, China, which integrates Terra/Aqua MODIS, Landsat 8 OLI, and Sentinel-2A/B MSI to attain high temporal and spatial resolution observations. According to the absorption characteristics and fluorescence peaks of HABs on remote sensing reflectance, the normalized difference vegetation index (NDVI) algorithm for MODIS, the floating algae index (FAI) and NDVI combined algorithm for Landsat 8, and the NDVI and chlorophyll reflection peak intensity index (ρchl) algorithm for Sentinel-2A/B MSI are used to extract HAB. The accuracies of the normalized difference vegetation index (NDVI), floating algae index (FAI), and chlorophyll reflection peak intensity index (ρchl) are 96.1%, 95.6%, and 93.8% with the RMSE values of 4.52, 2.43, 2.58 km2, respectively. The combination of NDVI and ρchl can effectively avoid misidentification of water and algae mixed pixels. Results revealed that the HAB in Chaohu Lake breaks out from May to November peaks in June, July, and August and more frequently occurs in the western region. Analysis of the HAB’s potential driving forces, including environmental and meteorological factors of temperature, rainfall, sunshine hours, and wind, indicated that higher temperatures and light rain favored this HAB. Wind is the primary factor in boosting the HAB’s growth, and the variation of a HAB’s surface in two days can reach up to 24.61%. Multi-source remote sensing provides higher observation frequency and more detailed spatial information on a HAB, particularly the HAB’s long-short term changes in their area.
Publisher: MDPI AG
Date: 05-02-2021
DOI: 10.3390/RS13040570
Abstract: With the development of spaceborne global navigation satellite system-reflectometry (GNSS-R), it can be used for terrestrial applications as a promising remote sensing tool, such as soil moisture (SM) retrieval. The reflected L-band GNSS signal from the land surface can simultaneously generate coherent and incoherent scattering, depending on surface roughness. However, the contribution of the incoherent component was directly ignored in previous GNSS-R land soil moisture content retrieval due to the hypothesis of its relatively small proportion. In this paper, a detection method is proposed to distinguish the coherence of land GNSS-R delay-Doppler map (DDM) from the cyclone global navigation satellite system (CYGNSS) mission in terms of DDM power-spreading features, which are characterized by different classification estimators. The results show that the trailing edge slope of normalized integrated time-delay waveform presents a better performance to recognize coherent and incoherent dominated observations, indicating that 89.6% of CYGNSS land observations are dominated by the coherent component. Furthermore, the impact of the land GNSS-Reflected DDM coherence on soil moisture retrieval is evaluated from 19-month CYGNSS data. The experiment results show that the influence of incoherent component and incoherent observations is marginal for CYGNSS soil moisture retrieval, and the RMSE of GNSS-R derived soil moisture reaches 0.04 cm3/cm3.
Publisher: MDPI AG
Date: 15-12-2021
DOI: 10.3390/RS13245093
Abstract: Global Navigation Satellite System (GNSS) Precise Point Positioning (PPP) enables the estimation the ionospheric vertical total electron content (VTEC) as well as the by-product of the satellite Pseudorange observable-specific signal bias (OSB). The single-frequency PPP models, with the ionosphere-float and ionosphere-free approaches in ionospheric studies, have recently been discussed by the authors. However, the multi-frequency observations can improve the performances of the ionospheric research compared with the single-frequency approaches. This paper presents three dual-frequency PPP approaches using the BeiDou Navigation Satellite System (BDS) B1I/B3I observations to investigate ionospheric activities. Datasets collected from the globally distributed stations are used to evaluate the performance of the ionospheric modeling with the ionospheric single- and multi-layer mapping functions (MFs), respectively. The characteristics of the estimated ionospheric VTEC and BDS satellite pseudorange OSB are both analyzed. The results indicated that the three dual-frequency PPP models could all be applied to the ionospheric studies, among which the dual-frequency ionosphere-float PPP model exhibits the best performance. The three dual-frequency PPP models all possess the capacity for ionospheric applications in the GNSS community.
Publisher: Springer Netherlands
Date: 31-08-2013
Publisher: Springer Netherlands
Date: 31-08-2013
Publisher: Springer Netherlands
Date: 31-08-2013
Publisher: CRC Press
Date: 22-08-2023
Publisher: Copernicus GmbH
Date: 15-03-2017
DOI: 10.5194/ANGEO-35-403-2017
Abstract: Abstract. GPS radio occultation can estimate ionospheric electron density and total electron content (TEC) with high spatial resolution, e.g., China's recent Fengyun-3C GPS radio occultation. However, high-order ionospheric delays are normally ignored. In this paper, the high-order ionospheric effects on electron density estimation from the Fengyun-3C GPS radio occultation data are estimated and investigated using the NeQuick2 ionosphere model and the IGRF12 (International Geomagnetic Reference Field, 12th generation) geomagnetic model. Results show that the high-order ionospheric delays have large effects on electron density estimation with up to 800 el cm−3, which should be corrected in high-precision ionospheric density estimation and applications. The second-order ionospheric effects are more significant, particularly at 250–300 km, while third-order ionospheric effects are much smaller. Furthermore, the high-order ionospheric effects are related to the location, the local time, the radio occultation azimuth and the solar activity. The large high-order ionospheric effects are found in the low-latitude area and in the daytime as well as during strong solar activities. The second-order ionospheric effects have a maximum positive value when the radio occultation azimuth is around 0–20°, and a maximum negative value when the radio occultation azimuth is around −180 to −160°. Moreover, the geomagnetic storm also affects the high-order ionospheric delay, which should be carefully corrected.
Publisher: MDPI AG
Date: 13-04-2019
DOI: 10.3390/RS11080901
Abstract: Big earthquakes often excite the acoustic resonance between the earth’s surface and the lower atmosphere. The perturbations can propagate upward into the ionosphere and trigger ionospheric anomalies detected by dual-frequency GPS observations, but coseismic ionospheric disturbance (CID) directivity and mechanism are not clear. In this paper, the ionospheric response to the Mw = 7.9 Alaska earthquake on 23 January 2018 is investigated from about 100 continuous GPS stations near the epicenter. The fourth-order zero-phase Butterworth band-pass filter with cutoffs of 2.2 mHz and 8 mHz is applied to obtain the ionospheric disturbances. Results show that the CIDs with an litude of up to 0.06 total electron content units (TECU) are detected about 10 min after the Alaska earthquake. The CIDs are as a result of the upward propagation acoustic waves triggered by the Rayleigh wave. The propagation velocities of TEC disturbances are around 2.6 km/s, which agree well with the wave propagation speed of 2.7 km/s detected by the bottom pressure records. Furthermore, the ionospheric disturbances following the 2018 Mw = 7.9 Alaska earthquake are inhomogeneous and directional which is rarely discussed. The magnitude of ionospheric disturbances in the western part of the epicenter is more obvious than in the eastern part. This phenomenon also corresponds to the data obtained from the seismographs and bottom pressure records (BPRs) at the eastern and western side of the epicenter.
Publisher: Springer Netherlands
Date: 31-08-2013
Publisher: Springer Netherlands
Date: 31-08-2013
Publisher: CRC Press
Date: 22-08-2023
Publisher: CRC Press
Date: 22-08-2023
Publisher: CRC Press
Date: 22-08-2023
Publisher: MDPI AG
Date: 23-06-2021
DOI: 10.3390/RS13132458
Abstract: The conversion between the line-of-sight slant total electron content (STEC) and the vertical total electron content (VTEC) depends on the mapping function (MF) under the widely used thin layer ionospheric model. The thin layer ionospheric height (TLIH) is an essential parameter of the MF, which affects the accuracy of the conversion between the STEC and VTEC. Due to the influence of temporal and spatial variations of the ionosphere, the optimal TLIH is not constant over the globe, particularly in the polar regions. In this paper, a new method for determining the optimal TLIH is proposed, which compares the mapping function values (MFVs) from the MF at different given TLIHs with the “truth” mapping values from the UQRG global ionospheric maps (GIMs) and the differential TEC (dSTEC) method, namely the dSTEC- and GIM-based thin layer ionospheric height (dG-TLIH) techniques. The optimal TLIH is determined using the dG-TLIH method based on GNSS data over the Antarctic and Arctic. Furthermore, we analyze the relationship between the optimal TLIH derived from the dG-TLIH method and the height of maximum density of the F2 layer (hmF2) based on COSMIC data in the polar regions. According to the dG-TLIH method, the optimal TLIH is mainly distributed between 370 and 500 km over the Arctic and between 400 and 500 km over the Antarctic in a solar cycle. In the Arctic, the correlation coefficient between the hmF2 and optimal TLIH is 0.7, and the deviation between them is 162 km. Meanwhile, in the Antarctic, the correlation coefficient is 0.60, with a phase lag of ~3 months, with the hmF2 leading the optimal TLIH, and the deviation between them is 177 km.
Publisher: Copernicus GmbH
Date: 11-12-2015
DOI: 10.5194/ISPRSARCHIVES-XL-1-W5-255-2015
Abstract: Abstract. Global Navigation Satellite System (GNSS) observations can precisely estimate the total zenith tropospheric delay (ZTD) and precipitable water vapour (PWV) for weather prediction and atmospheric research as a continuous and all-weather technique. However, apart from GNSS technique itself, estimations of ZTD and PWV are subject to effects of geophysical models with large uncertainties, particularly imprecise ocean tide models in Turkey. In this paper, GNSS data from Jan. 1st to Dec. 31st of 2014 are processed at 4 co-located GNSS stations (GISM, DIYB, GANM, and ADAN) with radiosonde from Turkish Met-Office along with several nearby IGS stations. The GAMIT/GLOBK software has been used to process GNSS data of 30-second s le using the Vienna Mapping Function and 10° elevation cut-off angle. Also tidal and non-tidal atmospheric pressure loadings (ATML) at the observation level are also applied in GAMIT/GLOBK. Several widely used ocean tide models are used to evaluate their effects on GNSS-estimated ZTD and PWV estimation, such as IERS recommended FES2004, NAO99b from a barotropic hydrodynamic model, CSR4.0 obtained from TOPEX/Poseidon altimetry with the model FES94.1 as the reference model and GOT00 which is again long wavelength adjustments of FES94.1 using TOPEX/Poseidon data at 0.5 by 0.5 degree grid. The ZTD and PWV computed from radiosonde profile observations are regarded as reference values for the comparison and validation. In the processing phase, five different strategies are taken without ocean tide model and with four aforementioned ocean tide models, respectively, which are used to evaluate ocean tide models effects on GNSS-estimated ZTD and PWV estimation through comparing with co-located Radiosonde. Results showed that ocean tide models have greatly affected the estimation of the ZTD in centimeter level and thus the precipitable water vapour in millimeter level, respectively at stations near coasts. The ocean tide model FES2004 that is the product of assimilation of the altimetric data of ERS2, TOPEX/POSEIDON and the data of a global tide gauge network, gave the most accurate results when compared to radiosonde with ±1.99 mm in PWV at stations near coastline. While other ocean tides models agree each other at millimeter level in PWV. However, at inland GNSS stations, ocean tide models have less effects on GNSS-estimated ZTD and PWV, e.g., with ±1.0 mm in ZTD and ±0.1 mm in PWV.
Publisher: Elsevier BV
Date: 03-2020
Publisher: Copernicus GmbH
Date: 17-12-2018
Abstract: Abstract. Temperature and ozone changes in the upper troposphere and lower stratosphere (UTLS) are important components and sensitive indicators of climate change. In this paper, variability and trends of temperature and ozone in the UTLS were investigated for the period 2002–2017 using the high quality, high vertical resolution GPS RO data, improved merged satellite data sets (SWOOSH and C3S) and reanalysis data sets (including the newest ERA5, MERRA2 and ERA-Interim). All three reanalyses show good agreement with the GPS RO measurements in absolute values, annual cycle as well as interannual variabilities of temperature. However, relatively large biases exist for the period 2002–2006, which reveals an evident discontinuity of temperature time series in reanalyses. Based on the multiple linear regression methods, a significant warming of 0.2–0.3 K/decade is found in most areas of the troposphere with stronger increase of 0.4–0.5 K/decade in mid-latitudes of both hemispheres. In contrast, the stratospheric temperature decreases at a rate of 0.1–0.3 K/decade except that in the lower most stratosphere (100–50 hPa) in the tropics and parts of mid-latitude in the Northern Hemisphere (NH). ERA5 shows improved quality compared with ERA-Interim and performs the best agreement with the GPS RO data for the recent trends of temperature. Similar with temperature, reanalyses ozone are also affected by the change of assimilated observations and methods. Negative trends of ozone are found in NH at 150–100 hPa while positive trends are evident in the tropical lower stratosphere. Asymmetric trends of ozone can be found for both hemispheres in the middle stratosphere, with significant ozone decrease in NH mid-latitudes and increase of ozone in the Southern Hemisphere (SH) mid-latitudes. According to model simulations, the temperature increase in the troposphere as well as ozone decrease in the NH stratosphere could be mainly connected to the increase of Sea Surface Temperature (SST) and subsequent changes of atmospheric circulations.
Publisher: Elsevier BV
Date: 08-2016
Publisher: American Geophysical Union (AGU)
Date: 02-2021
DOI: 10.1029/2020JA028915
Abstract: The low‐density cell structure in the high‐latitude thermosphere is referred to as the density depletion with respect to the adjacent area. Based on Gravity Recovery and Climate Experiment (GRACE) accelerometer data during the September 2017 geomagnetic storms, the thermospheric mass density at about 350 km are estimated and further investigated especially in the high‐latitude regions. At least two kinds of low‐density cells over the Southern Hemisphere (SH) are observed along the GRACE orbit. To understand the low‐density cell structures over the SH observed by GRACE, we investigate the underlying physical mechanism based on thermosphere‐ionosphere numerical simulations using Thermosphere‐Ionosphere Electrodynamic General Circulation Model and Global Ionosphere Thermosphere Model. According to the simulation results, the formation mechanism of the low‐density cell is attributed to the storm‐time vertical advection and horizontal velocity ergence driven by the auroral ion convection. The critical height of observable low‐density cells is shown to be not less than 350 km. The meridional spatial scale of observed low‐density cells over the SH are approximately or slightly larger than 1,500 km. Three low‐density cells, including two in the dawn sector and one in the night sector were observed about 1 hour after the direction of interplanetary magnetic field B Y component reversed. The occurrence of thermospheric low‐density structure is essential to be included in the empirical model during geomagnetic storm time.
Publisher: Oxford University Press (OUP)
Date: 26-09-2018
Publisher: Elsevier BV
Date: 08-2015
Publisher: MDPI AG
Date: 14-03-2022
DOI: 10.3390/S22062232
Abstract: Global Navigation Satellite Systems (GNSSs) can provide high-precision positioning services, which can be applied to fields including navigation and positioning, autonomous driving, unmanned aerial vehicles and so on. However, GNSS signals are easily disrupted in complex environments, which results in a positioning performance with a significantly inferior accuracy and lengthier convergence time, particularly for the single GNSS system. In this paper, multi-GNSS precise point positioning (PPP) with tightly integrating ultra-wide band (UWB) technology is presented to implement fast and precise navigation and positioning. The validity of the algorithm is evaluated by a set of GNSS and UWB data. The statistics indicate that multi-GNSS/UWB integration can significantly improve positioning performance in terms of the positioning accuracy and convergence time. The improvement of the positioning performance for the GNSS/UWB tightly coupled integration mainly concerns the north and east directions, and to a lesser extent, the vertical direction. Furthermore, the convergence performance of GNSS/UWB solution is analyzed by simulating GNSS signal interruption. The reliability and robustness of GNSS/UWB solution during GNSS signal interruption is verified. The results show that multi-GNSS/UWB solution can significantly improve the accuracy and convergence speed of PPP.
Publisher: MDPI AG
Date: 21-04-2022
DOI: 10.3390/S22093189
Abstract: The seafloor topography estimation is very important, while the bathymetry data and gravity data are scarce and uneven, which results in large errors in the inversion of the seafloor topography. In this paper, in order to reduce the influence of errors and improve the accuracy of seafloor inversion, the influence of different resolution data on the inversion topography in the Emperor Seamount Chain are investigated by combining ship water depth data and satellite gravity anomaly data released by SIO V29.1. Through the comparison of different resolution models, it is found that the choice of resolution affects the accuracy of the inversion terrain model. An external comparison is presented by using the international high-precision topography data and check points observations. The results show that with the increase in resolution, the fitting residuals obtained by the scale factor are optimized, and the precision of the terrain model is gradually approaching the S& S V19.1 and GEBCO-2020 models, but is better than the ETOPO1 and SRTM 30 models. By external validation using the check points, the standard deviation of the difference was reduced from 58.92 m to 47.01 m, and the correlation between the inverted terrain and the NGDC grid model was increased from 0.9545 to 0.9953. For recovering the Emperor Seamount Chain terrain, the relative error was gradually decreased with the improvement of resolution. The maximum relative error is reduced from 1.09 of 2′ topography to 0.74 of 10″ topography, and the average error is reduced from 0.04 to 0.01 with an improvement by 32.11%. The terrain error between the inverted terrain model and the NGDC grid model is gradually reduced, while the error percentage is increasing by 25.51% and 21.49% in the range of −50 to 50 m and −100 to 100 m, respectively. Furthermore, the sparse area can effectively reduce the terrain standard deviation and improve the terrain correlation by increasing the resolution through the analysis of different density subsets. The error was decreased most significantly in sparse and dense homogeneous regions with increasing resolution.
Publisher: Elsevier BV
Date: 11-2023
Publisher: CRC Press
Date: 22-10-2014
DOI: 10.1201/B17624-13
Publisher: IEEE
Date: 25-04-2022
Publisher: CRC Press
Date: 22-10-2015
DOI: 10.1201/B17624-14
Publisher: Elsevier BV
Date: 12-2012
Publisher: Elsevier BV
Date: 09-2022
Publisher: Elsevier BV
Date: 11-2019
Publisher: InTech
Date: 11-03-2015
DOI: 10.5772/60025
Publisher: MDPI AG
Date: 27-06-2022
Abstract: Solar system ephemeris is very important for pulsar timing and navigation. In order to explore the effect of different precision ephemerides on X-ray pulsar timing and navigation, the differences between timing and navigation results with four JPL Development Ephemerides based on the data of X-ray pulsar navigation-I (XPNAV-I) were compared and analyzed in this paper. For pulsar timing, the ephemeris has a systematic effect on time scale conversion (nanosecond difference), light-travel delay (millisecond difference) and timing residuals (microsecond difference), and the pulse profile phase can reflect the systematic deviation caused by different ephemerides in the timing calculation. The timing results show that it is necessary to compile the pulsar timing model based on the newer ephemeris. For navigation, based on the significant enhancement of pulse profile with orbit-dynamic (SEPO), the absolute error between simulation orbit and actual orbit is less than 2 km for each ephemeris, and the differences between simulation orbits are less than 1 km. The orbit position accuracy calculated by the ephemeris used in pulsar timing parameter calculation is the highest (DE200 in this paper), which explains the necessity of using a unified ephemeris in the calculation of timing and navigation with satisfying its internal self-consistency.
Publisher: Elsevier BV
Date: 07-2017
Publisher: Science China Press., Co. Ltd.
Date: 2002
DOI: 10.1360/02TB9342
Publisher: MDPI AG
Date: 05-04-2020
DOI: 10.3390/RS12071166
Abstract: The first 5.3 years of magnetic data from three Swarm satellites have been systematically analyzed, and possible co-seismic magnetic disturbances in the ionosphere were investigated just a few minutes after the occurrence of large earthquakes. We preferred to limit the investigation to a subset of earthquakes selected in function of depth and magnitude. After a systematic inspection of the available data around (in time and space) the seismic events, we found 12 Swarm satellite tracks with co-seismic disturbances possibly produced by ten earthquakes from Mw5.6 to Mw6.9. The distance of the satellite to the earthquake epicenter corresponds to the measured distance-time arrival of the disturbance from the surface to the ionosphere, confirming that the identified disturbances are most likely produced by the seismic events. Secondly, we found a good agreement with a model that combined a propagation of the disturbance to the F2 ionospheric layer with an acoustic gravity wave at a velocity of about (2.2 ± 0.3) km/s and a second faster phenomenon that transmits the disturbance from F2 layer to the Swarm satellite with a velocity of about (16 ± 3) km/s as an electromagnetic scattering propagation.
Publisher: Springer Science and Business Media LLC
Date: 12-2006
DOI: 10.1007/BF02910442
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: IEEE
Date: 21-11-2021
Publisher: IEEE
Date: 06-2011
Publisher: IEEE
Date: 07-2016
Publisher: IEEE
Date: 07-2016
Publisher: MDPI AG
Date: 17-07-2020
DOI: 10.3390/RS12142287
Abstract: The first Chinese altimetry satellite, Haiyang-2A (HY-2A), which was launched in 2011, has provided a large amount of sea surface heights which can be used to derive marine gravity field. This paper derived the vertical deflections and gravity disturbances using HY-2A observations for the major area of the whole Earth’s ocean from 60°S and 60°N. The results showed that the standard deviations (STD) of vertical deflections differences were 1.1 s and 3.5 s for the north component and the east component between HY-2A’s observations and those from EGM2008 and EIGEN-6C4, respectively. This indicates the accuracy of the east component was poorer than that of the north component. In order to clearly demonstrate contribution of HY-2A’s observations to gravity disturbances, reference models and the commonly used remove-restore method were not adopted in this study. Therefore, the results can be seen as ‘pure’ signals from HY-2A. Assuming the values from EGM2008 were the true values, the accuracy of the gravity disturbances was about −1.1 mGal in terms of mean value of the errors and 8.0 mGal in terms of the STD. This shows systematic errors if only HY-2A observations were used. An index of STD showed that the accuracy of HY-2A was close to the theoretical accuracy according to the vertical deflection products. To verify whether the systematic errors of gravity field were from the long wavelengths, the long-wavelength parts of HY-2A’s gravity disturbance with wavelengths larger than 500 km were replaced by those from EGM2008. By comparing with ‘pure’ HY-2A version of gravity disturbance, the accuracy of the new version products was improved largely. The systematic errors no longer existed and the error STD was reduced to 6.1 mGal.
Publisher: MDPI AG
Date: 22-11-2019
DOI: 10.3390/RS11232747
Abstract: Spaceborne Global Navigation Satellite Systems-Reflectometry (GNSS-R) can estimate the geophysical parameters by receiving Earth’s surface reflected signals. The CYclone Global Navigation Satellite System (CYGNSS) mission with eight microsatellites launched by NASA in December 2016, which provides an unprecedented opportunity to rapidly acquire ocean surface wind speed globally. In this paper, a refined spaceborne GNSS-R sea surface wind speed retrieval algorithm is presented and validated with the ground surface reference wind speed from numerical weather prediction (NWP) and cross-calibrated multi-platform ocean surface wind vector analysis product (CCMP), respectively. The results show that when the wind speed was less than 20 m/s, the RMS of the GNSS-R retrieved wind could achieve 1.84 m/s in the case where the NWP winds were used as the ground truth winds, while the result was better than the NWP-based retrieved wind speed with an RMS of 1.68 m/s when the CCMP winds were used. The two sets of inversion results were further evaluated by the buoy winds, and the uncertainties from the NWP-derived and CCMP-derived model prediction wind speed were 1.91 m/s and 1.87 m/s, respectively. The accuracy of inversed wind speeds for different GNSS pseudo-random noise (PRN) satellites and types was also analyzed and presented, which showed similar for different PRN satellites and different types of satellites.
Publisher: Elsevier BV
Date: 12-2013
Publisher: IEEE
Date: 21-11-2021
Publisher: Copernicus GmbH
Date: 26-06-2020
Abstract: Abstract. The differential code bias (DCB) of global navigation satellite systems (GNSS) is an important error source in ionospheric modeling, which was generally estimated as constants every day. However, the receiver DCB may be changing due to the varying space environments and temperatures. In this paper, the receiver DCB of BeiDou Navigation Satellite System (BDS) is estimated as the changing parameter within one day with epoch-by-epoch. The BDS receiver DCBs are analyzed from 30 days of multi-GNSS experiment observations. The comparison of estimated receiver DCB of BDS with the DCB provided by German Aerospace Center (DLR) and Chinese Academy of Sciences (CAS) shows a good agreement. The root mean square (RMS) values of receiver DCB are 0.43 and 0.80 ns with respect to DLR and CAS, respectively. In terms of the intra-day variability of receiver DCB, most of the receiver DCBs show relative stability within one day with the intra-day standard deviation (STD) of less than 1 ns. However, larger fluctuations with more than 2 ns of intra-day receiver DCB are found. Besides, the intra-day stability of receiver DCB calculated by the third-generation BDS (BDS-3) and the second-generation BDS (BDS-2) observations is compared. The result shows that the intra-day stability of BDS-3 receiver DCB is better than that of BDS-2 receiver DCB.
Publisher: Wiley
Date: 24-07-2022
Publisher: MDPI AG
Date: 16-11-2019
DOI: 10.3390/S19224994
Abstract: Snow is one of the most critical sources of freshwater, which influences the global water cycle and climate change. However, it is difficult to monitor global snow variations with high spatial–temporal resolution using traditional techniques due to their costly and labor-intensive nature. Nowadays, the Global Positioning System Interferometric Reflectometry (GPS-IR) technique can measure the average snow depth around a GPS antenna using its signal-to-noise ratio (SNR) data. Previous studies focused on the use of GPS data at sites located in flat areas or on very gentle slopes. In this contribution, we propose a strategy called the Tilted Surface Strategy (TSS), which uses the SNR data reflected only from the flat quadrants to estimate the snow depth instead of the conventional strategy, which employs all the SNR data reflected from the whole area around a GPS antenna. Three geodetic GPS sites from the Plate Boundary Observatory (PBO) project were chosen in this experimental study, of which GPS sites p683 and p101 were located on slopes with their gradients up to 18% and the site p025 was located on a flat area. Comparing the snow depths derived with the GPS-IR TSS method with the snow depth results provided with the GPS-PBO, i.e., GPS-IR with the conventional strategy, the Snowpack Telemetry (SNOTEL) network measurements and gridded Snow Data Assimilation System (SNODAS) estimates, it was found that the snow depths derived with the four methods had a good agreement, but the snow depth time series with the GPS-IR TSS method were closer to the SNOTEL measurements and the SNODAS estimates than those with GPS-PBO method. Similar observations were also obtained from the cumulative snowfall time series. Results generally indicated that for those GPS sites located on slopes, the TSS strategy works better.
Publisher: IEEE
Date: 12-2019
Publisher: MDPI AG
Date: 26-05-2023
DOI: 10.3390/RS15112774
Abstract: Playas, as the flattest landforms in semiarid and arid regions, are extremely sensitive to climate changes, such as changes in the hydrologic regime of the landscape. The changes in these landforms due to irrigation, anthropogenic activities, and climate change could be a source of disasters. In this study, we explored the spatial-temporal changes of the Abarkuh Playa in Central Iran using the time series of the Sentinel-1 backscatter dataset in the three scales. Our results showed that the western area of the Abarkuh Playa has been changed to other landforms with different characteristics, which is clear from all backscatter maps. The spatial-temporal analysis of the time series of backscatter data using the independent component analysis and time series of precipitation revealed that the backscatter variations were associated with direct rainfall across the playa and the surface was reacting to changes in the soil moisture content. The results of the power scale showed that the boundary of the playa could successfully be recognized as the oscillating pattern from other landforms in the study area. Moreover, the spatial-temporal analysis of backscatter in the power scale showed that different polarizations could reveal different patterns of surface changes for the playa.
Publisher: Cambridge University Press (CUP)
Date: 12-07-2018
DOI: 10.1017/S0373463318000462
Abstract: Tropospheric delay is one of the main error sources in Global Navigation Satellite System (GNSS) Precise Point Positioning (PPP). Zenith Hydrostatic Delay (ZHD) accounts for 90% of the total delay. This research focuses on the improvements of ZHD from tropospheric models and real meteorological data on the PPP solution. Multi-GNSS PPP experiments are conducted using the datasets collected at Multi-GNSS Experiments (MGEX) network stations. The results show that the positioning accuracy of different GNSS PPP solutions using the meteorological data for ZHD correction can achieve an accuracy level of several millimetres. The average convergence time of a PPP solution for the BeiDou System (BDS), the Global Positioning System (GPS), Global Navigation Satellite System of Russia (GLONASS), BDS+GPS, and BDS+GPS+GLONASS+Galileo are 55·89 min, 25·88 min, 33·30 min, 20·50 min and 15·71 min, respectively. The results also show that atmospheric parameters provided by real meteorological data have little effect on the horizontal components of positioning compared to the meteorological model, while in the vertical component, the positioning accuracy is improved by 90·6%, 33·0%, 22·2% and 19·8% compared with the standard atmospheric model, University of New Brunswick (UNB3m) model, Global Pressure and Temperature (GPT) model, and Global Pressure and Temperature-2 (GPT2) model and the convergence times are decreased 51·2%, 32·8%, 32·5%, and 32·3%, respectively.
Publisher: Wiley
Date: 24-07-2022
Publisher: Elsevier BV
Date: 11-2018
Publisher: Springer Science and Business Media LLC
Date: 12-06-2023
Publisher: IOP Publishing
Date: 17-04-2020
Publisher: MDPI AG
Date: 13-01-2021
DOI: 10.3390/RS13020256
Abstract: Being the highest and largest land mass of the earth, the Tibetan Plateau has a strong impact on the Asian climate especially on the Asian monsoon. With high downward solar radiation, the Tibetan Plateau is a climate sensitive region and the main water source for many rivers in South and East Asia. Although many studies have analyzed energy fluxes in the Tibetan Plateau, a long-term detailed spatio-temporal variability of all energy budget parameters is not clear for understanding the dynamics of the regional climate change. In this paper, satellite remote sensing and reanalysis data are used to quantify spatio-temporal trends of energy budget parameters, net radiation, latent heat flux, and sensible heat flux over the Tibetan Plateau from 2001 to 2019. The validity of both data sources is analyzed from in situ ground measurements of the FluxNet micrometeorological tower network, which verifies that both datasets are valid and reliable. It is found that the trend of net radiation shows a slight increase. The latent heat flux increases continuously, while the sensible heat flux decreases continuously throughout the study period over the Tibetan Plateau. Varying energy fluxes in the Tibetan plateau will affect the regional hydrological cycle. Satellite LE product observation is limited to certain land covers. Thus, for larger spatial areas, reanalysis data is a more appropriate choice. Normalized difference vegetation index proves a useful indicator to explain the latent heat flux trend. Despite the reduction of sensible heat, the atmospheric temperature increases continuously resulting in the warming of the Tibetan Plateau. The opposite trend of sensible heat flux and air temperature is an interesting and explainable phenomenon. It is also concluded that the surface evaporative cooling is not the indicator of atmospheric cooling/warming. In the future, more work shall be done to explain the mechanism which involves the complete heat cycle in the Tibetan Plateau.
Publisher: Springer Netherlands
Date: 31-08-2013
Publisher: Elsevier BV
Date: 05-2011
Publisher: Springer Netherlands
Date: 31-08-2013
Publisher: InTech
Date: 11-03-2015
DOI: 10.5772/58972
Publisher: IEEE
Date: 06-2013
Publisher: Springer Netherlands
Date: 31-08-2013
Publisher: SPIE
Date: 26-11-2014
DOI: 10.1117/12.2068776
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: American Geophysical Union (AGU)
Date: 04-2021
DOI: 10.1029/2020SW002645
Abstract: Thermospheric mass density (TMD) measurements are invaluable to accurately estimate and predict the position and velocity of orbiting objects in Low Earth Orbit (LEO). Existing observational methods and predictive models have some problems (e.g., accuracy, resolution, coverage, cost, etc.) to describe and forecast the actual air drag variations as required for practical applications. With the increasing number of LEO satellites equipped with high‐precision Global Navigation Satellite System (GNSS) receivers, the precise orbits can be used to obtain non‐gravitational accelerations, and therefore estimate TMD variations. In this study, TMD is estimated from the precise orbits of CAScade SmallSat and IOnospheric Polar Explorer (CASSIOPE) at one‐second time step, and the TMD variations following the February 2014 geomagnetic storm are investigated. Using this method, a more detailed description than previous methods and empirical models is given with short‐term TMD variations during geomagnetic storm conditions. The empirical model NRLMSISE‐00 shows less pronounced and more averaged variations, while CASSIOPE‐derived TMD can reflect the abrupt disturbances triggered by the geomagnetic storm. CASSIOPE TMD shows a correlation of 72.4% to the merging electric field E m index, while the NRLMSISE‐00 model shows a correlation of 42.1%.
Publisher: Elsevier BV
Date: 10-2023
Publisher: Informa UK Limited
Date: 11-2020
Publisher: MDPI AG
Date: 05-06-2017
DOI: 10.3390/S17061291
Publisher: Cambridge University Press (CUP)
Date: 09-07-2021
DOI: 10.1017/S0373463321000564
Abstract: Stochastic models are essential for precise navigation and positioning of the global navigation satellite system (GNSS). A stochastic model can influence the resolution of ambiguity, which is a key step in GNSS positioning. Most of the existing multi-GNSS stochastic models are based on the GPS empirical model, while differences in the precision of observations among different systems are not considered. In this paper, three refined stochastic models, namely the variance components between systems (RSM1), the variances of different types of observations (RSM2) and the variances of observations for each satellite (RSM3) are proposed based on the least-squares variance component estimation (LS-VCE). Zero-baseline and short-baseline GNSS experimental data were used to verify the proposed three refined stochastic models. The results show that, compared with the traditional elevation-dependent model (EDM), though the proposed models do not significantly improve the ambiguity resolution success rate, the positioning precision of the three proposed models has been improved. RSM3, which is more realistic for the data itself, performs the best, and the precision at elevation mask angles 20°, 30°, 40°, 50° can be improved by 4⋅6%, 7⋅6%, 13⋅2%, 73⋅0% for L1-B1-E1 and 1⋅1%, 4⋅8%, 16⋅3%, 64⋅5% for L2-B2-E5a, respectively.
Publisher: Copernicus GmbH
Date: 17-12-2018
Publisher: MDPI AG
Date: 17-01-2019
DOI: 10.3390/RS11020171
Abstract: Ionospheric delay is a significant error source in multi-GNSS positioning. We present different processing strategies to fully exploit the ionospheric delay effects on multi-frequency and multi-GNSS positioning performance, including standard point positioning (SPP) and precise point positioning (PPP) scenarios. Datasets collected from 10 stations over thirty consecutive days provided by multi-GNSS experiment (MGEX) stations were used for single-frequency SPP/PPP and dual-frequency PPP tests with quad-constellation signals. The experimental results show that for single-frequency SPP, the Global Ionosphere Maps (GIMs) correction achieves the best accuracy, and the accuracy of the Neustrelitz TEC model (NTCM) solution is better than that of the broadcast ionospheric model (BIM) in the E and U components. Eliminating ionospheric parameters by observation combination is equivalent to estimating the parameters in PPP. Compared with the single-frequency uncombined (UC) approach, the average convergence time of PPP with the external ionospheric models is reduced. The improvement in BIM-, NTCM- and GIM-constrained quad-constellation L2 single-frequency PPP was 15.2%, 24.8% and 28.6%, respectively. The improvement in convergence time of dual-frequency PPP with ionospheric models was different for different constellations and the GLONASS-only solution showed the least improvement. The improvement in the convergence time of BIM-, NTCM- and GIM-constrained quad-constellation L1/L2 dual-frequency PPP was 5.2%, 6.2% and 8.5%, respectively, compared with the UC solution. The positioning accuracy of PPP is slightly better with the ionosphere constraint and the performance of the GIM-constrained PPP is the best. The combination of multi-GNSS can effectively improve the positioning performance.
Publisher: IEEE
Date: 12-2019
Publisher: IEEE
Date: 08-2014
Publisher: Springer Science and Business Media LLC
Date: 03-2021
Publisher: IEEE
Date: 12-2019
Publisher: Elsevier BV
Date: 07-2010
Publisher: MDPI AG
Date: 15-01-2016
DOI: 10.3390/RS8010063
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Springer International Publishing
Date: 2023
Abstract: Upper-atmospheric processes under different space weather conditions are still not well understood, and the existing models are far away from the desired operational requirements due to the lack of in-situ measurements input. The ionospheric perturbation of electromagnetic signals affects the accuracy and reliability of Global Navigation Satellite Systems (GNSS), satellite communication infrastructures, and Earth observation techniques. Furthermore, the variable aerodynamic drag, due to variable thermospheric mass density, disturbs orbital tracking, collision analysis, and re-entry calculations of Low Earth Orbit (LEO) objects, including manned and unmanned artificial satellites. In this paper, we use the Principal Component Analysis (PCA) technique to study and compare the main driver-response relationships and spatial patterns of total electron content (TEC) estimates from 2003 to 2018, and total mass density (TMD) estimates at 475 km altitude from 2003 to 2015. Comparison of the first TEC and TMD PCA mode shows a very similar response to solar flux, but annual cycle shown by TEC is approximately one order of magnitude larger. A clear hemispheric asymmetry is shown in the global distribution of TMD, with higher values in the southern hemisphere than in the northern hemisphere. The hemispheric asymmetry is not visible in TEC. The persistent processes including a favorable solar wind input and particle precipitation over the southern magnetic dip may produce a higher thermospheric heating, which results in the hemispheric asymmetry in TMD.
Publisher: American Geophysical Union (AGU)
Date: 11-2021
DOI: 10.1029/2021JB022258
Abstract: Groundwater extraction rates exceeding recharge are occurring throughout Iran to sustain industrial and agricultural activities, resulting in land deformation in many areas, particularly in the Yazd‐Ardakan Plain (YAP) in central Iran's dry and desert regions. In this study, Interferometric Synthetic Aperture Radar (InSAR) time series analysis and statistical models are applied to characterize the controls on land subsidence in the YAP from 2003 to 2020. Our results reveal the existence of a northwest‐southeast elongated area of 234.45 km 2 experiencing subsidence at rates up to 15 cm/yr. In the YAP, the international Airport, railway, transit road, and several industrial and historical sites are threatened by the differential subsidence. Well data confirm that groundwater levels have decreased by 18 meters between 1974 and 2018, driving the compaction of sediments within the underlying aquifer system. Our statistical analysis shows that the thickness of a shallow, clay‐rich aquitard layer controls the extent of the observed subsidence and the Independent Component Analysis of the InSAR time series shows that inelastic compaction is dominated. This work reveals that current groundwater extraction practices in central Iran are not sustainable and result in permanent subsidence, ground fractures with impact on infrastructures, and a permanent decrease in water storage capacity.
Publisher: Elsevier BV
Date: 05-2011
Publisher: Springer Science and Business Media LLC
Date: 06-06-2019
Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-19809
Abstract: & & Applying a multi-parametric approach, we already investigated the preparatory phase of several medium and large (M6.0 ~ M8.3) earthquakes occurred in the last 6 years in different locations in the World. In some cases, a chain of processes from the lithosphere to atmosphere and ionosphere has been successfully detected (e.g. M7.8 Ecuador 2016: Akhoondzadeh, 2018, ASR, 0.1016/j.asr.2017.07.014 Italian seismic sequence (M6.5) 2016-2017: Marchetti et al., 2019, RSoE, 0.1016/j.rse.2019.04.033 M7.5 Indonesia 2018: Marchetti et al., 2019, JAES, 0.1016/j.jseaes.2019.104097). These analyses underline the importance to study all the & #8220 spheres& #8221 that surround the Earth as suggested by a Geosystemic approach (De Santis et al., 2019, Entropy, 0.3390/e21040412). To analyse the anomalies that occur in the atmosphere we typically calculate the mean and standard deviation of the & #8220 historical time series& #8221 of the investigated parameter based on around 40 years of data, and then we superpose the value of the same quantity in the earthquake year. If the value overpasses two standard deviations of the historical time series, we define this day arameter as anomalous. Applying the same methodology presented in previous works that studied climatological parameters such as skin temperature, total column water vapour, aerosols, and SO& sub& & /sub& , which & sub& & & /sub& seem to provide anomalies possibly related to the earthquake preparation phase (e.g. Piscini et al., 2017, PAGeoph, 0.1007/s00024-017-1597-8), here we investigate more atmospheric parameters proposed as possible precursors in the Lithosphere Atmosphere Ionosphere Coupling (LAIC) models (Pulinets and Ouzounov, 2011, JAES, 0.1016/j.jseaes.2010.03.005) such as methane and surface concentration of carbon monoxide. Other parameters, such as dimethylsulfide could be useful in other geophysical events, such as the volcano eruptions (Piscini et al. PAGeoph 2019, 0.1007/s00024-019-02147-x).& & & & In this study, we also apply a Worldwide Statistical Correlation (WSC), as it was successfully applied to Swarm satellites electromagnetic anomalies and earthquakes, providing some statistical evidence for such perturbations in ionosphere before the occurrence of M5.5+ earthquakes (De Santis et al., 2019, Sci. Rep., 0.1038/s41598-019-56599-1).& & & & The statistical approaches applied to these climatological data, provided by meteorological agencies such as ECMWF and NOAA, provides some interesting concentrations of atmospheric anomalies, preceding from days to several weeks the occurrence of the largest earthquakes from 1980 to 2017.& & & & The study of several chemical and physical (e.g. aerosol particles) components in the atmosphere, the involved physical processes, the chemical reactions and chemical constraints (such as the elements lifetime and interactions in the atmosphere) can help to distinguish which LAIC model is more reliable to produce the observed anomalies before the occurrence of a large earthquake.& & & & & & &
Publisher: Springer Science and Business Media LLC
Date: 04-2007
DOI: 10.1186/BF03353106
Abstract: The International Reference Ionosphere model 2001 (IRI-2001) is one of the most comprehensive empirical models of the ionosphere and has been widely used to estimate the electron density profiles in the altitude ranging from about 60 to 2000 km and the total electron content (TEC) at any given location, time and date, which reflect smooth-average global ionospheric behaviors. However, whether it provides normal actual estimations in the ionosphere over some regions should be tested with real observation data. In this paper, the three-dimensional ionospheric electron density profiles over South Korea in 2003 are obtained using the ionospheric tomography reconstruction technique with the permanent Korean GPS Network (KGN) data, and its validity is further verified by another independent ionosonde data. The GPS ionospheric reconstruction results are used to compare then results obtained with the IRI-2001 model in South Korea in terms of NmF2 and TEC. The monthly averaged diurnal values of these key parameters in January, April, July and October 2003 are considered to represent the winter, spring, summer and autumn seasons, respectively. Compared with the GPS reconstruction results, averaged monthly NmF2 medians from the IRI-2001 are overestimated in daytime and underestimated in nighttime for all seasons, but the deviation magnitudes in autumn and winter are smaller than in spring and summer. In addition, averaged monthly TEC medians from the IRI-2001 are overestimated in daytime in winter, but almost always underestimated in other seasons.
Publisher: American Society for Photogrammetry and Remote Sensing
Date: 2022
Abstract: Traditional urban scene-classification approaches focus on images taken either by satellite or in aerial view. Although single-view images are able to achieve satisfactory results for scene classification in most situations, the complementary information provided by other image views is needed to further improve performance. Therefore, we present a complementary information-learning model ( CILM ) to perform multi-view scene classification of aerial and ground-level images. Specifically, the proposed CILM takes aerial and ground-level image pairs as input to learn view-specific features for later fusion to integrate the complementary information. To train CILM , a unified loss consisting of cross entropy and contrastive losses is exploited to force the network to be more robust. Once CILM is trained, the features of each view are extracted via the two proposed feature-extraction scenarios and then fused to train the support vector machine classifier for classification. The experimental results on two publicly available benchmark data sets demonstrate that CILM achieves remarkable performance, indicating that it is an effective model for learning complementary information and thus improving urban scene classification.
Publisher: Elsevier BV
Date: 02-2017
Publisher: IEEE
Date: 12-2019
Publisher: CRC Press
Date: 22-08-2023
Publisher: Springer Berlin Heidelberg
Date: 2014
Publisher: Elsevier BV
Date: 04-2021
Publisher: CRC Press
Date: 22-08-2023
Publisher: IEEE
Date: 12-2019
Publisher: CRC Press
Date: 22-08-2023
Publisher: CRC Press
Date: 22-08-2023
Publisher: MDPI AG
Date: 11-07-2023
DOI: 10.3390/RS15143495
Abstract: The Great Lakes (GL) wetlands support a variety of rare and endangered animal and plant species. Thus, wetlands in this region should be mapped and monitored using advanced and reliable techniques. In this study, a wetland map of the GL was produced using Sentinel-1/2 datasets within the Google Earth Engine (GEE) cloud computing platform. To this end, an object-based supervised machine learning (ML) classification workflow is proposed. The proposed method contains two main classification steps. In the first step, several non-wetland classes (e.g., Barren, Cropland, and Open Water), which are more distinguishable using radar and optical Remote Sensing (RS) observations, were identified and masked using a trained Random Forest (RF) model. In the second step, wetland classes, including Fen, Bog, Sw , and Marsh, along with two non-wetland classes of Forest and Grassland/Shrubland were identified. Using the proposed method, the GL were classified with an overall accuracy of 93.6% and a Kappa coefficient of 0.90. Additionally, the results showed that the proposed method was able to classify the wetland classes with an overall accuracy of 87% and a Kappa coefficient of 0.91. Non-wetland classes were also identified more accurately than wetlands (overall accuracy = 96.62% and Kappa coefficient = 0.95).
Publisher: Elsevier BV
Date: 11-2007
Publisher: Research Square Platform LLC
Date: 05-01-2023
DOI: 10.21203/RS.3.RS-2391958/V1
Abstract: In terrestrial remote sensing applications, the spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) has demonstrated its worth. The application to land surface soil moisture (SSM) detection is particularly intriguing since it has the ability to provide fine-scale results to supplement traditional satellite-based active and passive missions. To date, many retrieval algorithms for spaceborne GNSS-R have been developed in order to produce SSM products. However, detailed product reliability and robustness evaluations are still absent. In this study, the satellite-based microwave radiometry product, the model-base product, and in-situ measurements from the Chinese soil moisture monitoring network with over 1800 ground stations during the year 2018 were used to evaluate the CYclone Global Navigation Satellite System (CYGNSS) mission Level-3 SSM products released by the University Corporation for Atmospheric Research (UCAR) and the University of Colorado at Boulder (CU). Typical relative skill metrics and triple collocation-based metrics, along with corresponding confidence intervals, are given to analyze the performance. According to the pixel-by-pixel validation and overall statistical findings, the results reveal that the current CYGNSS-based SSM exhibits low performance in southern China when compared to the radiometry-based data with a low R 2 (median R 2 =0.09) and the ubRMSD 0.055 cm 3 cm -3 , which is poorer than the results from SMAP against in-situ measurements (median R 2 =0.25, ubRMSD=0.046 cm 3 cm -3 ). To acquire better results to support the related operational applications in the future, the new enhanced retrieval algorithms and high-accuracy calibration referenced data must be used.
Publisher: Elsevier BV
Date: 2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Springer Science and Business Media LLC
Date: 24-09-2022
Publisher: Elsevier BV
Date: 02-2020
Publisher: Elsevier BV
Date: 2020
Publisher: MDPI AG
Date: 08-06-2021
DOI: 10.3390/RS13122241
Abstract: Chlorophyll-a (Chl-a), total nitrogen (TN), and total phosphorus (TP) are important indicators to evaluate water environmental quality. Monitoring water quality and its variability can help control water pollution. However, traditional monitoring techniques of water quality are time-consuming and laborious, and can mostly conduct with s le point-to-point at the edge of lakes and rivers. In this study, an empirical (regression-based) model is proposed to retrieve Chl-a, TN, and TP concentrations in the Yangtze River by Landsat-8 images from 2014 to 2020. The spatial-temporal distribution and variability of water quality in the whole Yangtze River are analyzed in detail. Furthermore, the driving forces of water quality variations are explored. The results show that the mean absolute percentage error (MAPE) of the water quality parameters are 25.88%, 4.3%, and 8.37% for Chl-a, TN, and TP concentrations, respectively, and the root mean square errors (RMSE) are 0.475 μg/L, 0.110 mg/L, and 0.01 mg/L, respectively. The concentrations of Chl-a, TN, and TP in the upstream of the Yangtze River are lower than those in the midstream and downstream. These water quality parameters have a seasonal cycle with a maximum in summer and minimum in winter. The hydrological and meteorological factors such as water level, flow, temperature, and precipitation are positively correlated with Chl-a, TN, and TP concentrations. The larger the impervious surface and cropland area, the greater the cargo handling capacity (CHC), higher ratio of TP to TN will further pollute the water. The methods and results provide essential information to evaluate and control water pollution in the Yangtze River.
Publisher: MDPI AG
Date: 20-06-2021
DOI: 10.3390/W13121704
Abstract: Poyang Lake, Dongting Lake, and Taihu Lake are the largest freshwater lakes in the middle and lower reaches of the Yangtze River, China. In recent years, the eutrophication level of lakes has increased with the development of the social economy and caused many environmental and social problems. The concentrations of total nitrogen (TN) and total phosphorus (TP) are the key indicators of the degree of eutrophication, but the traditional ground monitoring methods are not capable of capturing such parameters in whole lakes with high spatial-temporal resolution. In this paper, empirical models are established and evaluated between the TN and TP and remote sensing spectral factors in the three lakes using Landsat 8 Operational Land Imager (OLI) satellite data and in-situ data. The results show that the inversion accuracy is higher than 75%. The TN and TP concentrations in the three lakes are inversed based on the Google Earth Engine (GEE) platform from 2014 to 2020 and their spatial-temporal variations are analyzed. The results show that the concentrations of TN and TP in Poyang Lake were decreased by 5.99% and 7.13% over 7 years, respectively, and the TN in Dongting Lake was decreased by 5.25% while the TP remained stable. The temporal changes in TN and TP concentrations displayed seasonal variations. A low concentration was observed in summer and high concentrations were in spring and winter. The average concentrations of TN and TP in Taihu Lake were higher than that of the other two lakes. The TP concentration was increased by 17.3% over 7 years, while the TN concentration remained almost stable. The variation in TN in Taihu Lake was the same as the growth cycle of algae, with higher value in spring and winter and lower value in summer, while the concentration of TP was lower in spring and winter and higher in summer. The spatial distribution of TN and TP concentrations in the three major lakes was significantly affected by human activities, and the concentrations of TN and TP were higher in areas near cities and agricultural activities.
Publisher: MDPI AG
Date: 10-11-2020
DOI: 10.3390/RS12223679
Abstract: Global Navigation Satellite System-Reflectometry (GNSS-R) as a microwave remote sensing technique can retrieve the Earth’s surface parameters using the GNSS reflected signal from the surface. These reflected signals convey the surface features and therefore can be utilized to detect certain physical properties of the reflecting surface such as soil moisture content (SMC). Up to now, a serial of electromagnetic models (e.g., bistatic radar and Fresnel equations, etc.) are employed and solved for SMC retrieval. However, due to the uncertainty of the physical characteristics of the sites, complexity, and nonlinearity of the inversion process, etc., it is still challenging to accurately retrieve the soil moisture. The popular machine learning (ML) methods are flexible and able to handle nonlinear problems. It can dig out and model the complex interactions between input and output and ultimately make good predictions. In this paper, two typical ML methods, specifically, random forest (RF) and support vector machine (SVM), are employed for SMC retrieval from GNSS-R data of self-designed experiments (in situ and airborne). A comprehensive simulated dataset involving different types of soil is constructed firstly to represent the complex interactions between the variables (reflectivity, elevation angle, dielectric constant, and SMC) for the requirement of training ML regression models. Correspondingly, the main task of soil moisture retrieval (regression) is addressed. Specifically, the post-processed data (reflectivity and elevation angle) from sensor acquisitions are used to make predictions by these two adopted ML methods and compared with the commonly used GNSS-R retrieval method (electromagnetic models). The results show that the RF outperforms the SVM method, and it is more suitable for handling the inversion problem. Moreover, the RF regression model built by the comprehensive dataset demonstrates satisfactory accuracy and strong universality, especially when the soil type is not uniform or unknown. Furthermore, the typical task of detecting water/soil (classification) is discussed. The ML algorithms demonstrate a high potential and efficiency in SMC retrieval from GNSS-R data.
Publisher: IEEE
Date: 08-2014
Publisher: Springer Science and Business Media LLC
Date: 10-2006
Publisher: Springer Science and Business Media LLC
Date: 12-07-2008
Publisher: Elsevier BV
Date: 11-2018
Publisher: Springer Science and Business Media LLC
Date: 11-04-2023
Publisher: IOP Publishing
Date: 17-02-2021
Abstract: The accuracy of Global Navigation Satellite System (GNSS) observations is affected by many factors, such as different systems, frequencies, carriers and pseudoranges, all of which also vary with different situations. Therefore, it is challenging to establish an accurate stochastic model for multi-GNSS positioning in theory, particularly for the additional BeiDou-3 Global Navigation Satellite System (BDS-3). In practical applications, the real stochastic model needs to be estimated based on the characteristics of the observations themselves. We evaluated the influence of BDS-3 on the positioning results using 46 sites distributed around the world and proposed an improved stochastic model for multi-GNSS single point positioning (SPP) based on the least-squares variance component estimation (LS-VCE). The results show that when the BDS-3 observations are added, the positioning precision and accuracy are significantly improved. By using the improved LS-VCE method in GPS/BDS dual system positioning, the accuracy of E, N and U directions are 0.373, 0.498 and 1.044 m, respectively, when compared to the traditional method with 0.502, 0.533 and 1.333 m. The proposed stochastic model improves the multi-GNSS SPP accuracy without significantly increasing the calculation time. Furthermore, reliable results are obtained for all epochs with the improved LS-VCE model.
Publisher: IEEE
Date: 07-2019
Publisher: MDPI AG
Date: 26-10-2022
DOI: 10.3390/W14213401
Abstract: As discussed in the first part of this review paper, Remote Sensing (RS) systems are great tools to study various oceanographic parameters. Part I of this study described different passive and active RS systems and six applications of RS in ocean studies, including Ocean Surface Wind (OSW), Ocean Surface Current (OSC), Ocean Wave Height (OWH), Sea Level (SL), Ocean Tide (OT), and Ship Detection (SD). In Part II, the remaining nine important applications of RS systems for ocean environments, including Iceberg, Sea Ice (SI), Sea Surface temperature (SST), Ocean Surface Salinity (OSS), Ocean Color (OC), Ocean Chlorophyll (OCh), Ocean Oil Spill (OOS), Underwater Ocean, and Fishery are comprehensively reviewed and discussed. For each application, the applicable RS systems, their advantages and disadvantages, various RS and Machine Learning (ML) techniques, and several case studies are discussed.
Publisher: MDPI AG
Date: 23-07-2020
DOI: 10.3390/RS12152361
Abstract: The process of soil freezing and thawing refers to the alternating phase change of liquid water and solid water in the soil, accompanied by a large amount of latent heat exchange. It plays a vital role in the land water process and is an important indicator of climate change. The Tibetan Plateau in China is known as the “roof of the world”, and it is one of the most prominent physical characteristics is the freezing and thawing process of the soil. For the first time, this paper utilizes the spaceborne GNSS-R mission, i.e., CYGNSS (Cyclone Global Navigation Satellite System), to study the feasibility of monitoring the soil freeze-thaw (FT) cycles on the Tibetan Plateau. In the theoretical analysis part, model simulations show that there are abrupt changes in soil permittivities and surface reflectivities as the soil FT occurs. The CYGNSS reflectivities from January 2018 to January 2020 are compared with the SMAP FT state. The relationship between CYGNSS reflectivity and SMAP soil moisture within this time series is analyzed and compared. The results show that the effect of soil moisture on reflectivity is very small and can be ignored. The periodic oscillation change of CYGNSS reflectivity is almost the same as the changes in SMAP FT data. Freeze-thaw conversion is the main factor affecting CYGNSS reflectivity. The periodical change of CYGNSS reflectivity in the 2 years indicates that it is mainly caused by soil FT cycles. It is feasible to use CYGNSS to monitor the soil FT cycles in the Tibetan Plateau. This research expands the current application field of CYGNSS and opens a new chapter in the study of cryosphere using spaceborne GNSS-R with high spatial-temporal resolution.
Publisher: MDPI AG
Date: 26-10-2022
DOI: 10.3390/W14213400
Abstract: Oceans cover over 70% of the Earth’s surface and provide numerous services to humans and the environment. Therefore, it is crucial to monitor these valuable assets using advanced technologies. In this regard, Remote Sensing (RS) provides a great opportunity to study different oceanographic parameters using archived consistent multitemporal datasets in a cost-efficient approach. So far, various types of RS techniques have been developed and utilized for different oceanographic applications. In this study, 15 applications of RS in the ocean using different RS techniques and systems are comprehensively reviewed and discussed. This study is ided into two parts to supply more detailed information about each application. The first part briefly discusses 12 different RS systems that are often employed for ocean studies. Then, six applications of these systems in the ocean, including Ocean Surface Wind (OSW), Ocean Surface Current (OSC), Ocean Wave Height (OWH), Sea Level (SL), Ocean Tide (OT), and Ship Detection (SD), are provided. For each application, the applicable RS systems, their advantages and disadvantages, various RS and Machine Learning (ML) techniques, and several case studies are discussed. The other nine applications, including Iceberg, Sea Ice (SI), Sea Surface temperature (SST), Ocean Surface Salinity (OSS), Ocean Color (OC), Ocean Chlorophyll (OCh), Ocean Oil Spill (OOS), Underwater Ocean, and Fishery, are provided in Part II of this study.
Publisher: Elsevier BV
Date: 11-2018
Publisher: Springer Science and Business Media LLC
Date: 05-2019
Publisher: IOP Publishing
Date: 18-03-2014
Publisher: Informa UK Limited
Date: 12-2012
Publisher: Springer Science and Business Media LLC
Date: 20-09-2009
Publisher: InTech
Date: 29-05-2013
DOI: 10.5772/54568
Publisher: Elsevier BV
Date: 03-2019
Publisher: InTech
Date: 11-03-2015
DOI: 10.5772/58922
Publisher: Elsevier BV
Date: 09-2017
Publisher: Elsevier BV
Date: 07-2004
Publisher: Elsevier BV
Date: 09-2016
Publisher: Elsevier BV
Date: 02-2009
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: IEEE
Date: 07-2019
Publisher: Informa UK Limited
Date: 2003
DOI: 10.1007/BF02826747
Publisher: MDPI AG
Date: 11-01-2021
DOI: 10.3390/RS13020223
Abstract: In idual tree extraction is an important process for forest resource surveying and monitoring. To obtain more accurate in idual tree extraction results, this paper proposed an in idual tree extraction method based on transfer learning and Gaussian mixture model separation. In this study, transfer learning is first adopted in classifying trunk points, which can be used as clustering centers for tree initial segmentation. Subsequently, principal component analysis (PCA) transformation and kernel density estimation are proposed to determine the number of mixed components in the initial segmentation. Based on the number of mixed components, the Gaussian mixture model separation is proposed to separate canopies for each in idual tree. Finally, the trunk stems corresponding to each canopy are extracted based on the vertical continuity principle. Six tree plots with different forest environments were used to test the performance of the proposed method. Experimental results show that the proposed method can achieve 87.68% average correctness, which is much higher than that of other two classical methods. In terms of completeness and mean accuracy, the proposed method also outperforms the other two methods.
Publisher: MDPI AG
Date: 11-05-2023
DOI: 10.3390/RS15102526
Abstract: Total nitrogen (TN) and total phosphorus (TP) are important indicators of water quality. Although water quality can be obtained with high accuracy using traditional measurement methods, the cost is high and the area is limited. In the past a single-satellite remote sensing system was normally used to estimate water quality at a large scale, while bands were fewer with limited accuracy. In this paper, inversion models for TN and TP are obtained and validated in the main stream of the Yangtze River using multi-source remote sensing data. The joint inversion models for TN and TP have higher accuracy (R2=0.81 and 0.86, RMSE=0.51 and 0.10 mg L−1) than the single-satellite inversion models (R2=0.61−0.62 and 0.59−0.75, RMSE=0.41−0.61 and 0.07−0.12 mg L−1). Using these models, water quality changes in the Yangtze River are obtained from 2019 to 2021. It is found that TN and TP in the upstream and downstream are high. In spring and autumn, the water quality is poor. The water quality in the Yangtze River is mostly Class III with improvement. Furthermore, it is found that TN and TP are negatively correlated with the water level, temperature and flow in Jiujiang. The p value between water quality and the water level is higher than for other factors, with −0.76 and −0.64 for TN and TP, respectively.
Publisher: American Geophysical Union (AGU)
Date: 11-2016
DOI: 10.1002/2016JA022594
Publisher: Elsevier BV
Date: 07-2018
Publisher: Elsevier BV
Date: 07-2013
Publisher: MDPI AG
Date: 24-02-2020
DOI: 10.3390/RS12040746
Abstract: Typhoons often occur and may cause huge loss of life and damage of infrastructures, but they are still difficult to precisely monitor and predict by traditional in-situ measurements. Nowadays, ionospheric disturbances at a large-scale following typhoons can be monitored using ground-based dual-frequency Global Positioning System (GPS) observations. In this paper the responses of ionospheric total electron content (TEC) to Typhoon Maria on 10 July 2018 are studied by using about 150 stations of the GPS network in Taiwan. The results show that two significant ionospheric disturbances on the southwest side of the typhoon eye were found between 10:00 and 12:00 UTC. This was the stage of severe typhoon and the ionospheric disturbances propagated at speeds of 118.09 and 186.17 m/s, respectively. Both traveling ionospheric disturbances reached up to 0.2 TECU and the litudes were slightly different. The change in the filtered TEC time series during the typhoon was further analyzed with the azimuth. It can be seen that the TEC disturbance anomalies were primarily concentrated in a range of between −0.2 and 0.2 TECU and mainly located at 135–300° in the azimuth, namely the southwest side of the typhoon eye. The corresponding frequency spectrum of the two TEC time series was about 1.6 mHz, which is consistent with the frequency of gravity waves. Therefore, the upward propagating gravity wave was the main cause of the traveling ionospheric disturbance during Typhoon Maria.
Publisher: IEEE
Date: 06-2014
Publisher: Elsevier BV
Date: 12-2012
Publisher: MDPI AG
Date: 20-11-2020
DOI: 10.3390/S20226655
Abstract: Laser time transfer is of great significance in timing and global time synchronization. However, the temperature drift may occur and affect the delay of the electronics system, optic generation and detection system. This paper proposes a post-processing method for the compensation of temperature-induced system delay, which does not require any changes to the hardware setup. The temperature drift and time stability of the whole system are compared with and without compensation. The results show that the propagation delay drift as high as 240 ps caused by temperature changes is compensated. The temperature drift coefficient was diminished down to ~0.05 ps/°C from ~20.0 ps/°C. The system precision was promoted to ~2 ps from ~11 ps over a time period of 80,000 s. This method performs significant compensation of single-photon laser time transfer system propagation drift and will help to establish an ultra-stable laser time transfer link in space applications.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Elsevier BV
Date: 03-2016
Publisher: Elsevier BV
Date: 03-2013
Publisher: MDPI AG
Date: 10-01-2019
DOI: 10.3390/RS11020120
Abstract: Water is arguably our most precious resource, which is related to the hydrological cycle, climate change, regional drought events, and water resource management. In Turkey, besides traditional hydrological studies, Terrestrial Water Storage (TWS) is poorly investigated at a continental scale, with limited and sparse observations. Moreover, TWS is a key parameter for studying drought events through the analysis of its variation. In this paper, TWS variation, and thus drought analysis, spatial mass distribution, long-term mass change, and impact on TWS variation from the parameter scale (e.g., precipitation, rainfall rate, evapotranspiration, soil moisture) to the climatic change perspective are investigated. GRACE (Gravity Recovery and Climate Experiment) Level 3 (Release05-RL05) monthly land mass data of the Centre for Space Research (CSR) processing center covering the period from April 2002 to January 2016, Global Land Data Assimilation System (GLDAS: Mosaic (MOS), NOAH, Variable Infiltration Capacity (VIC)), and Tropical Rainfall Measuring Mission (TRMM-3B43) models and drought indices such as self-calibrating Palmer Drought Severity (SCPDSI), El Niño–Southern Oscillation (ENSO), and North Atlantic Oscillation (NAO) are used for this purpose. Turkey experienced serious drought events interpreted with a significant decrease in the TWS signal during the studied time period. GRACE can help to better predict the possible drought nine months before in terms of a decreasing trend compared to previous studies, which do not take satellite gravity data into account. Moreover, the GRACE signal is more sensitive to agricultural and hydrological drought compared to meteorological drought. Precipitation is an important parameter affecting the spatial pattern of the mass distribution and also the spatial change by inducing an acceleration signal from the eastern side to the western side. In Turkey, the La Nina effect probably has an important role in the meteorological drought turning into agricultural and hydrological drought.
Publisher: Elsevier BV
Date: 10-2022
Publisher: American Geophysical Union (AGU)
Date: 09-2021
DOI: 10.1029/2020JA028995
Abstract: Co‐seismic ionospheric disturbance (CID) may provide insights on understanding the coupled nature of earthquake–atmosphere geophysical processes. In this study, the CIDs following the M w 7.7 Jamaica earthquake on January 28, 2020 are detected about 12 min after the main shock by the dual‐frequency Global Positioning System measurements. Significant CIDs at two azimuths are observed from satellite PRN03, 04 and 26 with spreading out at 3.54, 3.51 and 3.48 km/s respectively, which are close to the spreading speeds of Rayleigh waves recorded by the seismographs. The significant CID signals are found in south near‐field area and southwest far‐field area. Furthermore, CID characteristics are analyzed in terms of litude, elevation and azimuth angle, waveform, and frequency domain. Results show that CIDs are observed by PRN03, 04 and 26 at low elevation angles ( °) in infrasonic wave frequency domain and the average negative litudes of CIDs observed by PRN26 are larger than −0.08 TECU, while the CID litudes observed by PRN03 and PRN04 are about −0.05 and −0.07 TECU, respectively. Moreover, the azimuthal asymmetry of CID litude in SW and SE azimuths and different initial polarities in disturbance signals are found and discussed from tectonic and nontectonic factors. The relations among CID, Rayleigh wave and focal mechanism are interpreted. The upward propagating secondary acoustic wave triggered by the seismic Rayleigh wave from earthquake is the main source of CIDs. These results confirm that strike‐slip earthquake can also generate pronounced co‐seismic ionospheric disturbances.
Publisher: Elsevier BV
Date: 12-2015
Publisher: Wiley
Date: 18-01-2021
Publisher: MDPI AG
Date: 05-08-2022
DOI: 10.3390/RS14153772
Abstract: Snow plays an important role in the water cycle and global climate change, and the accurate monitoring of changes in snow depth is an important task. However, monitoring snow properties is still challenging and unclear, particularly in the Tibetan Plateau, which has rough land and uneven terrain. The traditional monitoring methods have some limitations in monitoring snow depth changes, and the Global Navigation Satellite System-Reflectometry (GNSS-R) provides a new opportunity for snow monitoring. This paper employed data from the Cyclone Global Navigation Satellite System (CYGNSS) to discover the effect of snow properties. Firstly, the observations of CYGNSS were used to find the sensitive to snow properties, and the relationships between signal to noise ratio (SNR), leading edge slope (LES), surface reflectivity (SR), and snow depth were studied and analyzed, respectively. It is found that the correlation between the first two parameters and snow depth is poor, while SR can indicate the changes in snow depth, and is proposed as an indicator of SR change, namely, surface reflectivity–difference ratio factor (SR–DR factor). Furthermore, the long-time series data in the Tibetan Plateau (2018–2019) are used to analyze its effects on the time series of the SR–DR factor, while the influences of the soil freeze/thaw (F/T) process and soil moisture are excluded during the analysis. The results indicate that the SR–DR factor can be a good indicator and discriminator for snow depth. Our work shows that space-borne GNSS-R has the potential for the monitoring of snow properties.
Publisher: IEEE
Date: 07-2017
Publisher: Elsevier BV
Date: 08-2022
Publisher: MDPI AG
Date: 12-02-2020
DOI: 10.3390/RS12040614
Abstract: The understanding of land surface-atmosphere energy exchange is extremely important for predicting climate change and weather impacts, particularly the influence of soil moisture content (SMC) on hydrometeorological and ecological processes, which are also linked to human activities. Unfortunately, traditional measurement methods are expensive and cumbersome over large areas, whereas measurements from satellite active and passive microwave sensors have shown advantages for SMC monitoring. Since the launch of the first passive microwave satellite in 1978, more and more progresses have been made in monitoring SMC from satellites, e.g., the Soil Moisture Active and Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) missions in the last decade. Recently, new methods using signals of opportunity have been emerging, highlighting the Global Navigation Satellite Systems-Reflectometry (GNSS-R), which has wide applications in Earth’s surface remote sensing due to its numerous advantages (e.g., revisiting time, global coverage, low cost, all-weather measurements, and near real-time) when compared to the conventional observations. In this paper, a detailed review on the current SMC measurement techniques, retrieval approaches, products, and applications is presented, particularly the new and promising GNSS-R technique. Recent advances, future prospects and challenges are given and discussed.
Publisher: American Geophysical Union (AGU)
Date: 08-2021
DOI: 10.1029/2021JA029540
Abstract: Long‐term thermospheric mass density disturbances due to magnetospheric forcing are not clear due to a lack of measurement data and imprecise models. In this study, the Global Navigation Satellite System (GNSS) precise orbits of CAScade SmallSat and IOnospheric Polar Explorer (CASSIOPE) are used to infer high‐resolution thermospheric mass densities between the years 2014 and 2020. The CASSIOPE densities are comprehensively validated at altitudes from 325 to 425 km at intervals of 25 km with the High Accuracy Satellite Drag Model (HASDM) density database, and further compared with the Naval Research Laboratory Mass Spectrometer and Incoherent Scatter Radar Exosphere/2000 (NRLMSISE‐00) and the Jacchia‐Bowman/2008 (JB2008) empirical models. The CASSIOPE densities are very similar to the HASDM and JB2008 densities, while the NRLMSISE‐00 largely overestimates (∼150%) during low solar‐flux conditions. For density values above ∼10 −12 kg/m 3 , the correlation of CASSIOPE with HASDM is ∼5% better than the models, and the standard deviation is within 10% of the background density. For density values below ∼10 −12 kg/m 3 , systematic errors have shown to reduce the precision of the CASSIOPE densities. By setting geomagnetic contributions to zero in the models, the density disturbances due to magnetospheric forcing are isolated from the CASSIOPE time‐series, allowing investigation into the correlations and time‐delay responses to the models and to the merging electric field (E m ). A new linear dependence of the time delay to the E m was found and then parameterized in this study. Time delays occurred at the 4–7 h range during geomagnetic storms, and at 9–11 h during quiet conditions neither had significant dependence on altitude. The results represent the validation of the first high‐resolution thermospheric mass density estimates inferred from commercial‐off‐the‐shelf GNSS receivers.
Publisher: MDPI AG
Date: 14-05-2019
Abstract: Extreme precipitation has often occurred in Southeastern China, while the possible mechanism is not clear. In order to bridge the scale gap between large-scale circulation and extreme precipitation, in this paper, the k-means clustering technique—a common method of weather-type (WT) analysis—was applied to regional 850-hPa wind fields. The reasonable determination of k values can make the later WT analyses more reliable. Thus, the Davies–Bouldin (BD) criterion index is used in the clustering process, and the optimal value of the k was determined. Then, we obtain and analyze the frequency, persistence, and progression of WTs. The rule of transitions from one WT to another may help explain some of the physical processes in winter. We found a special evolutionary chain (WT3→WT1→WT2→WT5→WT3) that can be used to explain the cold wave weather process in winter. Different WTs in the evolutionary chain correspond well to different stages of the cold wave weather process (gestation (WT3), outbreak (WT1), eastward withdrawal (WT2), and extinction (WT5)). In addition, we found that there are obvious differences in precipitation between December and February. After reassembling five kinds of WTs, two modes are formed: dry WTs and wet WTs. Our research shows that the intraseasonal variation of precipitation can be attributed to the fluctuation between the wet and dry WTs, and the different phases of teleconnection can correspond well with it. For ex le, the relative frequencies of wet WTs are higher in February. These WTs correspond to the positive phase of the WP and ENSO, the negative phase of the EA and EU, and the strong MJO state of the second, third, and eighth phase. Our work has well established the relationship between synoptic scale and large-scale circulation, which provides a reference for climate model simulation and future climate prediction.
Publisher: Elsevier BV
Date: 05-2011
Publisher: MDPI AG
Date: 06-03-2023
Abstract: Spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) has been proven to be a cost-effective and efficient tool for monitoring the Earth’s surface soil moisture (SSM) with unparalleled spatial and temporal resolution. However, the accuracy and reliability of GNSS-R SSM estimation are affected by surface vegetation and roughness. In this study, the sensitivity of delay Doppler map (DDM)-derived effective reflectivity to SSM is analyzed and validated. The in idual effective reflectivity is projected onto the 36 km × 36 km Equal-Area Scalable Earth-Grid 2.0 (EASE-Grid2) to form the observation image, which is used to construct a global GNSS-R SSM retrieval model with the SMAP SSM serving as the reference value. In order to improve the accuracy of retrieved SSM from CYGNSS, the effective reflectivity is corrected using vegetation opacity and roughness coefficient parameters from SMAP products. Additionally, the impacts of vegetation and roughness on the estimated SSM were comprehensively evaluated. The results demonstrate that the accuracy of SSM retrieved by GNSS-R is improved with correcting vegetation over different types of vegetation-covered areas. The retrieval algorithm achieves an accuracy of 0.046 cm3cm−3, resulting in a mean improvement of 4.4%. Validation of the retrieval algorithm through in situ measurements confirms its stable.
Publisher: Elsevier BV
Date: 03-2013
Publisher: MDPI AG
Date: 31-10-2020
DOI: 10.3390/RS12213569
Abstract: The tropospheric delay and gradients can be estimated using Global Positioning System (GPS) observations after removing the ionospheric delay, which has been widely used for atmospheric studies and forecasting. However, high-order ionospheric (HOI) delays are generally ignored in GPS processing to estimate atmospheric parameters. In this study, HOI effects on GPS-estimated tropospheric delay and gradients are investigated from two weeks of GPS data in June 2011 at selected GPS stations in Turkey. Results show that HOI effects are up to 6 mm on zenith tropospheric delay (ZTD), 4 mm on the North-South (NS) gradient and 12 mm on the East-West (EW) gradient during this period, but can reach over 30 mm in slant tropospheric delays. Furthermore, the HOI effects on tropospheric delay and gradient are larger in the daytime than the nighttime. Furthermore, HOI effects on tropospheric delay are further investigated on low and high solar activity days. The HOI effects on GPS estimated tropospheric delay and gradients in high solar activity days are higher than those in low solar activity days.
Publisher: American Society for Photogrammetry and Remote Sensing
Date: 09-2022
Abstract: Economic development and climate change drive the land use and land cover (LULC) change globally. Annual robust maps of LULC are critical for studying climate change and land–climate interaction. However, the current existing methods for optimizing and expanding the publicly available China land cover data set (CLCD) are limited. In this article, 30-m annual LULC changes are obtained from 1990 to 2020 in the Yangtze River basin (YRB). The results show an overall accuracy rate of 82.66% and better performances on Geo-Wiki test s les when compared to similar products. Based on our 30-m annual LULC data set, the drastic LULC changes are found in YRB over a 30-year period, where impervious surface area more than tripled, cropland area decreased by 6.12%, and water area decreased by 6.09%. In addition, through the geographically and temporally weighted regression method, a fitting model with a goodness of fit of 0.91 well reveals that human activity plays a driving role in the LULC change of YRB.
Publisher: Oxford University Press (OUP)
Date: 17-02-2015
DOI: 10.1093/GJI/GGV016
Publisher: MDPI AG
Date: 09-07-2020
DOI: 10.3390/RS12142200
Abstract: Geomagnetic storms are extreme space weather events, which have considerable impacts on the ionosphere and power transmission systems. In this paper, the ionospheric responses to the geomagnetic storm on 22 June 2015, are analyzed from ground-based and satellite-based Global Navigation Satellite System (GNSS) observations as well as observational data of digital ionosondes, and the main physical mechanisms of the ionospheric disturbances observed during the geomagnetic storm are discussed. Salient positive and negative storms are observed from vertical total electron content (VTEC) based on ground-based GNSS observations at different stages of the storm. Combining topside observations of Low-Earth-Orbit (LEO) satellites (GRACE and MetOp satellites) with different orbital altitudes and corresponding ground-based observations, the ionospheric responses above and below the orbits are studied during the storm. To obtain VTEC from the slant TEC between Global Positioning System (GPS) and LEO satellites, we employ a multi-layer mapping function, which can effectively reduce the overall error caused by the single-layer geometric assumption where the horizontal gradient of the ionosphere is not considered. The results show that the topside observations of the GRACE satellite with a lower orbit can intuitively detect the impact caused by the fluctuation of the F2 peak height (hmF2). At the same time, the latitude range corresponding to the peak value of the up-looking VTEC on the event day becomes wider, which is the precursor of the Equatorial Ionization Anomaly (EIA). However, no obvious response is observed in the up-looking VTEC from MetOp satellites with higher orbits, which indicates that the VTEC responses to the geomagnetic storm mainly take place below the orbit of MetOp satellites.
Publisher: IEEE
Date: 06-2014
Publisher: Elsevier BV
Date: 07-2008
Publisher: IEEE
Date: 08-2014
Publisher: MDPI AG
Date: 17-05-2017
DOI: 10.20944/PREPRINTS201705.0130.V1
Abstract: GNSS have been widely used in navigation, positioning and timing. Nowadays, the multipath errors previously considered detrimental may be re-utilized for the remote sensing of geophysical parameters (soil moisture, vegetation and snow depth), e.g. GPS- Multipath Reflectometry (GPS-MR). In this paper, a new element describing bistatic scattering properties of vegetation is incorporated into the traditional GPS-MR model. This new element is the first-order radiative transfer equation model. The new forward GPS multipath simulator is able to explicitly link the vegetation parameters with GPS multipath observables (signal-to-noise-ratio (SNR), code pseudorange and carrier phase observables). The trunk layer and its corresponding scattering mechanisms are ignored since GPS-MR is not suitable for high forest monitoring due to the coherence of direct and reflected signals. Based on this new model linking the GPS observables (SNR, phase and pseudorange) with detailed vegetation parameters, the developed simulator can present how the GPS signals (L1 and L2 carrier frequencies, C/A, P(Y) and L2C modulations) are transmitted (scattered and absorbed) through vegetation medium and received by GPS receivers. Simulation results show that wheat will decrease the litudes of GPS multipath observables, if we increase the vegetation moisture contents or the scatters sizes (stem or leaf), the litudes of GPS multipath observables (SNR, phase and code) decrease. Although the Specular-Ground component dominates the total specular scattering, vegetation covered ground soil moisture has almost no effects on the final multipath signatures. Our simulated results are consistent with published results for environmental parameter detections with GPS-MR.
Publisher: Springer Science and Business Media LLC
Date: 25-02-2019
Publisher: IEEE
Date: 21-11-2021
Publisher: MDPI AG
Date: 29-01-2022
DOI: 10.3390/S22031071
Abstract: Low Earth Orbit (LEO) satellites can be used for remote sensing and gravity field recovery, while precise orbit determination (POD) is vital for LEO satellite applications. However, there are some systematic errors when using the LEO satellite orbits released by different agencies in multi-satellite-based applications, e.g., Swarm and Gravity Recovery and Climate Experiment-Follow-On (GRACE-FO), as different GNSS precise orbit and clock products are used as well as processing strategies and software. In this paper, we performed undifferenced kinematic PODs for Swarm and GRACE-FO satellites simultaneously over a total of 14 days by using consistent International Global Navigation Satellite System (GNSS) Service (IGS) precise orbit and clock products. The processing strategy based on an undifferenced ionosphere-free combination and a least squares method was applied for Swarm and GRACE-FO satellites. Furthermore, the quality control for the kinematic orbits was adopted to mitigate abrupt position offsets. Moreover, the accuracy of the kinematic orbits solution was evaluated by carrier phase residual analysis and Satellite Laser Ranging (SLR) observations, as well as comparison with official orbits. The results show that the kinematic orbits solution is better than 4 cm, according to the SLR validation. With quality control, the accuracy of the kinematic orbit solution is improved by 2.49 % for the Swarm-C satellite and 6.98 % for the GRACE-D satellite when compared with their precise orbits. By analyzing the accuracy of the undifferenced kinematic orbit solution, the reliability of the LEO orbit determination is presented in terms of processing strategies and quality control procedures.
Publisher: Copernicus GmbH
Date: 20-05-2019
Abstract: Abstract. Temperature and ozone changes in the upper troposphere and lower stratosphere (UTLS) are important components of climate change. In this paper, variability and trends of temperature and ozone in the UTLS are investigated for the period 2002–2017 using high-quality, high vertical resolution Global Navigation Satellite System radio occultation (GNSS RO) data and improved merged satellite data sets. As part of the Stratosphere-troposphere Processes And their Role in Climate (SPARC) Reanalysis Intercomparison Project (S-RIP), three reanalysis data sets, including the ERA-I, MERRA2 and the recently released ERA5, are evaluated for their representation of temperature and ozone in the UTLS. The recent temperature and ozone trends are updated with a multiple linear regression (MLR) method and related to sea surface temperature (SST) changes based on model simulations made with NCAR's Whole Atmosphere Community Climate Model (WACCM). All reanalysis temperatures show good agreement with the GNSS RO measurements in both absolute value and annual cycle. Interannual variations in temperature related to Quasi-Biennial Oscillation (QBO) and the El Niño–Southern Oscillation (ENSO) processes are well represented by all reanalyses. However, evident biases can be seen in reanalyses for the linear trends of temperature since they are affected by discontinuities in assimilated observations and methods. Such biases can be corrected and the estimated trends can be significantly improved. ERA5 is significantly improved compared to ERA-I and shows the best agreement with the GNSS RO temperature. The MLR results indicate a significant warming of 0.2–0.3 K per decade in most areas of the troposphere, with a stronger increase of 0.4–0.5 K per decade at midlatitudes of both hemispheres. In contrast, the stratospheric temperature decreases at a rate of 0.1–0.3 K per decade, which is most significant in the Southern Hemisphere (SH). Positive temperature trends of 0.1–0.3 K per decade are seen in the tropical lower stratosphere (100–50 hPa). Negative trends of ozone are found in the Northern Hemisphere (NH) at 150–50 hPa, while positive trends are evident in the tropical lower stratosphere. Asymmetric trends of ozone can be found in the midlatitudes of two hemispheres in the middle stratosphere, with significant ozone decrease in the NH and increase in ozone in the SH. Large biases exist in reanalyses, and it is still challenging to do trend analysis based on reanalysis ozone data. According to single-factor-controlled model simulations with WACCM, the temperature increase in the troposphere and the ozone decrease in the NH stratosphere are mainly connected to the increase in SST and subsequent changes of atmospheric circulations. Both the increase in SSTs and the decrease in ozone in the NH contribute to the temperature decrease in the NH stratosphere. The increase in temperature in the lower stratospheric tropics may be related to an increase in ozone in that region, while warming SSTs contribute to a cooling in that area.
Publisher: American Geophysical Union (AGU)
Date: 08-05-2007
DOI: 10.1029/2006JD007772
Publisher: IEEE
Date: 07-2019
Publisher: MDPI AG
Date: 20-07-2021
DOI: 10.3390/RS13142844
Abstract: Cyclone Global Navigation Satellite System (CyGNSS) data have been used for generating several intermediate products, such as surface reflectivity (Γ), to facilitate a wide variety of land remote sensing applications. The accuracy of Γ relies on precise knowledge of the effective instantaneous radiative power (EIRP) of the transmitted GNSS signals in the direction of the specular reflection point, the precise knowledge of zenith antenna patterns which in turn affects estimates of EIRP, the good knowledge of receive antenna patterns etc. However, obtaining accurate estimates on these parameters completely is still a challenge. To solve this problem, in this paper, an effective method is proposed for calibrating the CyGNSS Γ product in a track-wise manner. Here, two different criteria for selecting data to calibrate and three reference options as targets of the calibrating data are examined. Accordingly, six calibration schemes corresponding to six different combinations are implemented and the resulting Γ products are assessed by (1) visual inspection and (2) evaluation of their associated soil moisture retrieval results. Both visual inspection and retrieval validation demonstrate the effectiveness of the proposed schemes, which are respectively demonstrated by the immediate removal/fix of track-wisely noisy data and obvious enhancement of retrieval accuracy with the calibrated Γ. Moreover, the schemes are tested using all the available CyGNSS level 1 version 3.0 data and the good results obtained from such a large volume of data further illustrate their robustness. This work provides an effective and robust way to calibrate the CyGNSS Γ result, which will further improve relevant remote sensing applications in the future.
Publisher: Springer Science and Business Media LLC
Date: 18-07-2009
Publisher: Elsevier BV
Date: 07-2003
Publisher: Elsevier BV
Date: 07-2023
Publisher: MDPI AG
Date: 08-08-2022
DOI: 10.3390/RS14153838
Abstract: Change detection between images of pre-flood and flooding periods is a critical process for flood mapping using satellite images. Flood mapping from SAR images is based on backscattering coefficient differences. The change rules of the backscattering coefficient with different flooding depths of ground objects are essential prior knowledge for flood mapping, while their absence greatly limits the precision. Therefore, minimizing the backscattering coefficient differences caused by non-flood factors is of great significance for improving the accuracy of flood mapping. In this paper, non-flood factor influences, i.e., monthly variations of ground objects and polarization and satellite orbits, on the backscattering coefficient are studied with multi-temporal Sentinel-1 images for five ground objects in Kouzi Village, Shouguang City, Shandong Province, China. Sentinel-1 images in different rainfalls are used to study the variation of the backscattering coefficient with flooding depths. Since it is difficult to measure the flooding depth of historical rainfall events, a hydrological analysis based on the Geographic Information System (GIS) and Remote Sensing (RS) is used to estimate the flooding depth. The results showed that the monthly variations of the maximum backscattering coefficients of farmland and construction and the backscattering coefficient differences caused by the satellite orbit were larger than the minimum backscattering coefficient differences caused by inundation. The flood extraction rules of five objects based on Sentinel-1 were obtained and analyzed, which improved flood extraction knowledge from qualitative to semi-quantitative analysis.
Publisher: MDPI AG
Date: 24-12-2020
DOI: 10.3390/RS13010045
Abstract: Soil moisture is the most active part of the terrestrial water cycle, and it is a key variable that affects hydrological, bio-ecological, and bio-geochemical processes. Microwave remote sensing is an effective means of monitoring soil moisture, but the existing conventional radiometers and single-station radars cannot meet the scientific needs in terms of temporal and spatial resolution. The emergence of GNSS-R (Global Navigation Satellite Systems Reflectometry) technology provides an alternative method with high temporal and spatial resolution. An important application field of GNSS-R is soil moisture monitoring, but it is still in the initial stage of research, and there are many uncertainties and open issues. Based on a review of the current state-of-the-art of soil moisture retrieval using GNSS-R, this paper points out the limitations of existing research in observation geometry, polarization, and coherent and non-coherent scattering. The smooth surface reflectivity model, the random rough surface scattering model, and the first-order radiation transfer equation model of the vegetation, which are in the form of bistatic and full polarization, are employed. Simulations and analyses of polarization, observation geometry (scattering zenith angle and scattering azimuth angle), Brewster angle, coherent and non-coherent component, surface roughness, and vegetation effects are carried out. The influence of the EIRP (Effective Isotropic Radiated Power) and the RFI (Radio Frequency Interference) on soil moisture retrieval is briefly discussed. Several important development directions for space-borne GNSS-R soil moisture retrieval are pointed out in detail based on the microwave scattering model.
Publisher: IEEE
Date: 07-2018
Publisher: Elsevier BV
Date: 02-2016
Publisher: Elsevier BV
Date: 03-2013
Publisher: CRC Press
Date: 22-10-2014
DOI: 10.1201/B17624
Publisher: Copernicus GmbH
Date: 28-10-2020
DOI: 10.5194/ANGEO-38-1115-2020
Abstract: Abstract. The differential code bias (DCB) of the Global Navigation Satellite System (GNSS) is an important error source in ionospheric modeling, which was generally estimated as constants every day. However, the receiver DCB may be changing due to the varying spatial environments and temperatures. In this paper, a method based on the global ionospheric map (GIM) of the Center for Orbit Determination in Europe (CODE) is presented to estimate the BeiDou Navigation Satellite System (BDS) receiver DCB with epoch-by-epoch estimates. The BDS receiver DCBs are analyzed from 30 d of Multi-GNSS Experiment observations. The comparison of estimated receiver DCB of BDS with the DCB provided by the German Aerospace Center (DLR) and the Chinese Academy of Sciences (CAS) shows a good agreement. The root-mean-square (rms) values of receiver DCB are 0.43 and 0.80 ns with respect to the DLR and CAS estimates, respectively. In terms of the intraday variability of receiver DCB, most of the receiver DCBs show relative stability within 1 d with the intraday standard deviation (SD) of less than 1 ns. However, larger fluctuations with more than 2 ns of intraday receiver DCB are found. Besides, the intraday stability of receiver DCB calculated by the third-generation BDS (BDS-3) and the second-generation BDS (BDS-2) observations is compared. The result shows that the intraday stability of BDS-3 receiver DCB is better than that of BDS-2 receiver DCB.
Publisher: IEEE
Date: 07-2011
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Springer Science and Business Media LLC
Date: 19-03-2019
Publisher: Elsevier BV
Date: 02-2016
Publisher: MDPI AG
Date: 19-04-2022
DOI: 10.3390/RS14091961
Abstract: Soil moisture (SM) has normally been estimated based on a linear relationship between SM and the surface reflectivity (Γ) from the spaceborne Global Navigation Satellite System (GNSS)-Reflectometry, while it usually relies on inputs of SM data without considering vegetation optical depth (VOD/τ) effects. In this study, a new scheme is proposed for retrieving soil moisture from the Cyclone GNSS (CyGNSS) data. The variation of CyGNSS-derived ΔΓ is modeled as a function of both variations in SM and VOD (ΔSM and Δτ). For retrieving SM, ancillary τ data can be obtained from the Soil Moisture Active Passive (SMAP) mission. In addition to this option, a model for simulating Δτ is suggested as an alternative. Experimental evaluation is performed for the time span from August 2019 to July 2021. Excellent agreements between the final retrievals and referenced SMAP SM products are achieved for both training (1-year period) and test (1-year duration) sets. On the whole, overall correlation coefficients (r) of 0.97 and 0.95 and root-mean-square errors (RMSEs) of 0.024 and 0.028 cm3/cm3 are obtained based on models using the SMAP and simulated Δτ, respectively. The model without τ generates an r of 0.95 and an RMSE of 0.031 cm3/cm3. The efficiency and necessity of considering τ are thus confirmed by its enhancement based on correlation and RMSE against the one without τ, and the usefulness of approximating Δτ by sinusoidal functions is also validated. Influences of SM statistics in terms of mean and variance on the retrieval accuracy are evaluated. This work unveils the interaction between CyGNSS data, SM, and τ and demonstrates the feasibility of integrating the Δτ approximation function into a bilinear regression model to obtain SM results.
Publisher: InTech
Date: 03-02-2012
DOI: 10.5772/1134
Publisher: IEEE
Date: 07-2016
Publisher: IEEE
Date: 07-2016
Publisher: Elsevier BV
Date: 05-2018
Publisher: Elsevier BV
Date: 2016
Publisher: IEEE
Date: 12-2013
Publisher: Elsevier BV
Date: 07-2003
Publisher: Springer Science and Business Media LLC
Date: 22-04-2022
Publisher: InTech
Date: 29-05-2013
DOI: 10.5772/3439
Publisher: MDPI AG
Date: 09-05-2020
DOI: 10.3390/RS12091506
Abstract: Soil moisture is an important factor affecting the global climate and environment, which can be monitored by microwave remote sensing all day and under all weather conditions. However, existing monostatic radars and microwave radiometers have their own limitations in monitoring soil moisture with shallower depths. The emerging remote sensing of signal of opportunity (SoOp) provides a new method for soil moisture monitoring, but only an experimental perspective was proposed at present, and its mechanism is not clear. In this paper, based on the traditional surface scattering models, we employed the polarization synthesis method, the coordinate transformation, and the Mueller matrix, to develop bistatic radar circular polarization models that are suitable for SoOP remote sensing. Using these models as a tool, the bistatic scattering versus the observation frequency, soil moisture, scattering zenith angle, and scattering azimuth at five different circular polarizations (LR, HR, VR, + 45° R, and −45° R) are simulated and analyzed. The results show that the developed models can determine the optimal observation combination of polarizations and observation angle. The systematic analysis of the scattering characteristics of random rough surfaces provides an important guiding significance for the design of space-borne payloads, the analysis of experimental data, and the development of backward inversion algorithms for more effective SoOP remote sensing.
Publisher: Elsevier BV
Date: 10-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Elsevier BV
Date: 08-2004
Publisher: Copernicus GmbH
Date: 12-06-2023
Abstract: Abstract. Differential code bias (DCB) is one of the Global Positioning System (GPS) errors, which affects the calculation of total electron content (TEC) and ionospheric modeling. In the past, DCB was normally estimated as a constant in one day, while DCB of low Earth orbit (LEO) satellite GPS receiver may have large variations within one day due to complex space environments and highly dynamic orbit conditions. In this study, daily and hourly DCBs of Meteorological Operational (MetOp) satellites GPS receivers are calculated and evaluated using spherical harmonic function (SHF) and local spherical symmetry (LSS) assumption. The results demonstrated that both approaches could obtain accurate and consistent DCB values. The estimated daily DCB standard deviation (STD) is within 0.1 ns in accordance with the LSS assumption and is numerically less than the standard deviation of the reference value provided by the COSMIC Data Analysis and Archive Center (CDAAC). The average error's absolute value is within 0.2 ns with respect to the provided DCB reference value. As for the SHF method, the DCB's standard deviation is within 0.1 ns, which is also less than the standard deviation of the CDAAC reference value. The average error of the absolute value is within 0.2 ns. The estimated hourly DCB with LSS assumptions suggested that calculated results of MetOpA, MetOpB, and MetOpC are, respectively, 0.5 ns to 3.1 ns, -1.1 ns to 1.5 ns, and -1.3 ns to 0.7 ns. The root mean square error (RMSE) is less than 1.2 ns, and the STD is under 0.6 ns. According to the SHF method, the results of MetOpA, MetOpB, and MetOpC are 1 ns to 2.7 ns, - 1 ns to 1 ns, and - 1.3 ns to 0.6 ns, respectively. The RMSE is under 1.3 ns and STD is less than 0.5 ns. The STD for solar active days is less than 0.43 ns, 0.49 ns, and 0.44 ns, respectively, with the LSS assumption, and the appropriate fluctuation ranges are 2.0 ns, 2.2 ns, and 2.2 ns. The variation ranges for the SHF method are 1.5 ns, 1.2 ns, and 1.2 ns, respectively, while the STD is under 0.28 ns, 0.35 ns, and 0.29 ns.
Publisher: IEEE
Date: 07-2016
Publisher: IEEE
Date: 17-07-2022
Publisher: IEEE
Date: 07-2016
Publisher: American Geophysical Union (AGU)
Date: 2017
DOI: 10.1002/2016JF003926
Publisher: Cambridge University Press (CUP)
Date: 08-2012
DOI: 10.1017/S1743921313013100
Abstract: The upper atmosphere of Venus is not shielded by planetary magnetic field from direct interaction with the solar wind. The interaction of shocked solar wind and the ionosphere results in ionopause. Magnetic barrier, the inner region of dayside magnetosheath with the dominated magnetic pressure deflects the solar wind instead of the ionopause at solar maximum. Therefore, the structure and interaction of venusian ionosphere is very complex. Although the Venus Express (VEX) arrived at Venus in April 2006 provides more knowledge on the Venusian ionosphere and plasma environment, compared to Pioneer Venus Orbiter (PVO) with about 14 years of observations, some important details are still unknown (e.g., long Venusian bow shock variations and effects). In this paper, the bow shock positions of Venus are determined and analyzed from magnetometer (MAG) and ASPERA-4 of the Venus Express mission from May 28, 2006 to August 17, 2010. Results show that the altitude of BS was mainly affected by SZA (solar zenith angle) and Venus bow shocks inbound and outbound are asymmetry.
Publisher: MDPI AG
Date: 13-07-2021
DOI: 10.3390/RS13142756
Abstract: PPP using Kalman filter typically takes half an hour to achieve high positioning precision, which is required for small movements detection. Many dataset gaps due to temporary GPS receiver signal loss challenge the feasibility of PPP in GPS applications for kinematic precise positioning. Additional convergence time is needed before PPP reaches the required precision again. In this study, Partial parameters were estimated by using the position and ZWD as prior constraint. The solved partial parameters were applied to initialize the Kalman filter for PPP instantaneous re-convergence. A set of bridge GPS data with logging gaps were used to validate the re-convergence performance of improved PPP. The results show that the displacements from position-constrained PPP with initialized variance are 0.14 m, 0.09 m and 0.05 m, which are much better than those from standard PPP. The precision of displacement from position- and ZWD-constrained PPP with initialized variance is slightly improved when compared with that from position-constrained PPP with initialized variance at all 3 surveying points. The bridge experiment verifies that the displacement time series of improved PPP instantaneously converges at the first epoch of all signal reacquired, in contrast, standard PPP deviates by meters. This finding suggests that improved PPP can successfully deal with the GPS data logging gaps for instantaneous convergence.
Publisher: Elsevier BV
Date: 07-2018
Publisher: IEEE
Date: 07-2016
Publisher: Elsevier BV
Date: 12-2017
Publisher: MDPI AG
Date: 30-01-2022
Abstract: The coronavirus disease of 2019 (COVID-19) pandemic is currently a global challenge, with 210 countries, including Indonesia, seeking to minimize its spread. Therefore, this study aims to determine the spatiotemporal spread pattern of this virus in Surabaya using various data on confirmed cases from 28 April to 26 October 2021. It also aims to determine the relationship between pollutant parameters, such as carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3), as well as the government’s high social restrictions policy in Java-Bali. Several methods, such as the weighted mean center, directional distribution, Getis–Ord Gi*, Moran’s I, and geographically weighted regression, were used to identify the spatial spread pattern of the virus. The weighted mean center indicated that the epicenter location of the outbreak moved randomly. The directional distribution demonstrated a decrease of 21 km2 at the end of the study phase, which proved that its spread has significantly reduced in Surabaya. Meanwhile, the Getis–Ord Gi* results demonstrated that the eastern and southern parts of the study region were highly infected. Moran’s I demonstrate that COVID-19 cases clustered during the spike. The geographically weighted regression model indicated a number of influence zones in the northeast, northwest, and a few in the southwest parts at the peak of R2 0.55. The relationship between COVID-19 cases and air pollution parameters proved that people living at the outbreak’s center have low pollution levels due to lockdown. Furthermore, the lockdown policy reduced CO, NO2, SO2, and O3. In addition, increase in air pollutants namely, NO2, CO, SO2 and O3, was recorded after 7 weeks of lockdown implementation (started from 18 August).
Publisher: IEEE
Date: 07-2016
Publisher: Copernicus GmbH
Date: 28-10-2019
DOI: 10.5194/ANGEO-37-989-2019
Abstract: Abstract. Short-term upper atmosphere variations due to magnetospheric forcing are very complex, and neither well understood nor capably modeled due to limited observations. In this paper, mass density variations from 10 years of GRACE observations (2003–2013) are isolated via the parameterization of annual, local solar time (LST), and solar cycle fluctuations using a principal component analysis (PCA) technique. The resulting residual disturbances are investigated in terms of magnetospheric drivers. The magnitude of high-frequency (δ 10 d) disturbances reveals unexpected dependencies on the solar cycle, seasonal, and an asymmetric behavior with smaller litudes in June in the south polar region (SPR). This seasonal modulation might be related to the Russell–McPherron (RM) effect. Meanwhile, we find a similar pattern, although less pronounced, in the northern and equatorial regions. A possible cause of this latitudinal asymmetry might be the irregular shape of the Earth's magnetic field (with the north dip pole close to Earth's rotation axis, and the south dip pole far from that axis). After accounting for the solar cycle and seasonal dependencies by regression analysis to the magnitude of the high-frequency perturbations, the parameterization in terms of the disturbance geomagnetic storm-time index Dst shows the best correlation, whereas the geomagnetic variation Am index and merging electric field Em are the best predictors in terms of time delay. We test several mass density models, including JB2008, NRLMSISE-00, and TIEGCM, and find that they are unable to completely reproduce the seasonal and solar cycle trends found in this study, and show a clear overestimation of about 100 % during low solar activity periods.
Publisher: Elsevier BV
Date: 07-2019
Publisher: Springer Berlin Heidelberg
Date: 2015
Publisher: MDPI AG
Date: 23-12-2019
DOI: 10.3390/RS12010068
Abstract: The third generation of China’s BeiDou Navigation Satellite System (BDS-3) began to provide global services on 27 December, 2018. Differential code bias (DCB) is one of the errors in precise BDS positioning and ionospheric modeling, but the impacts on BDS-2 satellites and receiver DCB are unknown after joining BDS-3 observations. In this paper, the BDS-3 DCBs are estimated and analyzed using the Multi-Global Navigation Satellite System (GNSS) Experiment (MGEX) observations during the period of day of year (DOY) 002–031, 2019. The results indicate that the estimated BDS-3 DCBs have a good agreement with the products provided by the Chinese Academy of Sciences (CAS) and Deutsche Zentrum für Luft- und Raumfahrt (DLR). The differences between our results and the other two products are within ±0.2 ns, with Standard Deviations (STDs) of mostly less than 0.2 ns. Furthermore, the effects on satellite and receiver DCB after adding BDS-3 observations are analyzed by BDS-2 + BDS-3 and BDS-2-only solutions. For BDS-2 satellite DCB, the values of effect are close to 0, and the effect on stability of DCB is very small. In terms of receiver DCB, the value of effect on each station is related to the receiver type, but their mean value is also close to 0, and the stability of receiver DCB is better when BDS-3 observations are added. Therefore, there is no evident systematic bias between BDS-2 and BDS-2 + BDS-3 DCB.
Publisher: Elsevier BV
Date: 05-2021
Publisher: CRC Press
Date: 22-10-2014
DOI: 10.1201/B17624-9
Publisher: American Geophysical Union (AGU)
Date: 10-2014
DOI: 10.1002/2014JA020135
Publisher: IOP Publishing
Date: 06-2021
DOI: 10.1088/1755-1315/799/1/012023
Abstract: The receiver differential code bias (DCB) is one of the main errors in GNSS navigation and positioning as well as ionospheric monitoring. In this paper, we present a new method to estimate the receiver differential code bias (DCB) using Multi-GNSS observations in Southeast Asia. Different from the traditional method by using ionosphere modeling or Global ionospheric map (GIM), the total electron content (TEC) of station in the new method is estimated directly together with the receiver DCB. The data of one year with 34 stations were used to evaluate the performance of the presented method. The results show a good agreement between our estimated receiver DCBs and the MGEX DCB products and the RMS of eight types of GNSS receiver DCB are mostly less than 1ns with respect to the MGEX products. Finally, the stability of GNSS receiver DCB was analysed for eight stations located in Southeast Asia as ex les. The result indicates that those stations were relatively stable with mostly less than 1ns of STD of receiver DCB. Moreover, no evidence of latitudinal and receiver type dependencies of the stability of receiver DCB for those selected stations was found.
Publisher: InTech
Date: 11-03-2015
DOI: 10.5772/59988
Publisher: MDPI AG
Date: 22-12-2017
DOI: 10.3390/RS10010014
Publisher: American Geophysical Union (AGU)
Date: 12-2019
DOI: 10.1029/2019JA027065
Abstract: The first regional total electron content (TEC) model over the entire African region (known as AfriTEC model) using empirical observations is developed and presented. Artificial neural networks were used to train TEC observations obtained from Global Positioning System receivers, both on ground and onboard the Constellation Observing System for Meteorology, Ionosphere, and Climate satellites for the African region from years 2000 to 2017. The neural network training was implemented using inputs that enabled the networks to learn diurnal variations, seasonal variations, spatial variations, and variations that are connected with the level of solar activity, for quiet geomagnetic conditions (−20 nT ≤ Dst ≤ 20 nT). The effectiveness of three solar activity indices (sunspot number, solar radio flux at 10.7‐cm wavelength [F10.7], and solar ultraviolet [UV] flux at 1 AU) for the neural network trainings was tested. The F10.7 and UV were more effective, and the F10.7 was used as it gave the least errors on the validation data set used. Equatorial anomaly simulations show a reduced occurrence during the June solstice season. The distance of separation between the anomaly crests is typically in the range from about 11.5 ± 1.0° to 16.0 ± 1.0°. The separation is observed to widen as solar activity levels increase. During the December solstice, the anomaly region shifts southwards of the equinox locations in year 2012, the trough shifted by about 1.5° and the southern crest shifted by over 2.5°.
Publisher: CRC Press
Date: 22-10-2014
DOI: 10.1201/B17624-2
Publisher: MDPI AG
Date: 09-05-2019
DOI: 10.3390/RS11091103
Abstract: The monitoring of water storage variations is essential not only for the management of water resources, but also for a better understanding of the impact of climate change on hydrological cycle, particularly in Tibet. In this study, we estimated and analyzed changes of the total water budget on the Tibetan Plateau from the Gravity Recovery And Climate Experiment (GRACE) satellite mission over 15 years prior to 2017. To suppress overall leakage effect of GRACE monthly solutions in Tibet, we applied a forward modeling technique to reconstruct hydrological signals from GRACE data. The results reveal a considerable decrease in the total water budget at an average annual rate of −6.22 ± 1.74 Gt during the period from August 2002 to December 2016. In addition to the secular trend, seasonal variations controlled mainly by annual changes in precipitation were detected, with maxima in September and minima in December. A rising temperature on the plateau is likely a principal factor causing a continuous decline of the total water budget attributed to increase melting of mountain glaciers, permafrost, and snow cover. We also demonstrate that a substantial decrease in the total water budget due to melting of mountain glaciers was partially moderated by the increasing water storage of lakes. This is evident from results of ICESat data for selected major lakes and glaciers. The ICESat results confirm a substantial retreat of mountain glaciers and an increasing trend of major lakes. An increasing volume of lakes is mainly due to an inflow of the meltwater from glaciers and precipitation. Our estimates of the total water budget on the Tibetan Plateau are affected by a hydrological signal from neighboring regions. Probably the most significant are aliasing signals due to ground water depletion in Northwest India and decreasing precipitation in the Eastern Himalayas. Nevertheless, an integral downtrend in the total water budget on the Tibetan Plateau caused by melting of glaciers prevails over the investigated period.
Publisher: Springer Science and Business Media LLC
Date: 04-2021
DOI: 10.1186/S40562-021-00182-Y
Abstract: Signals of Opportunity Reflectometry (SoOp-R) employs the communication system, GNSS (Global Navigation Satellite System) constellation and other potential Signals of Opportunity (SoOp) as the transmitters. In recent years, it has gained increased interests. Several experiments have been carried out, however it is still in the initial development stage. Theoretical predictions of SoOp Reflectometry for land surface parameters detection, such as soil moisture and vegetation biomass, should be carried out simultaneously. Meanwhile, at present less works are paid attention to the polarization study of the polarizations. The first-order radiative transfer equation models are employed here and they are developed according to the wave synthesis technique to get the various polarization combinations. Using the two models as analysis tools, we simulate the bistatic scattering at all potential SoOp Reflectometry bands, i.e., P-, L-, C- and X-band for circular polarizations and linear polarizations. While the original commonly used microwave scattering models are linear polarizations, here we compare the difference. Although the models can simulate bistatic scattering at any incident angles and scattering angles. Four special observation geometry are taken into considerations during the analysis. Using the developed models as tools, the developed models establish the relationship between the land surface parameters (such as soil moisture, soil roughness and vegetation water content, diameters et al.) and bistatic radar cross section. The forward scattering models developed here enables the understanding of the effects of different geophysical parameters and transmitter–receiver observation scenarios on the bisatic scattering at any polarization combinations for any potential SoOP reflectometry bands. Robust retrieval methods for soil moisture and vegetation biomass can benefit from the forward scattering models.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: CRC Press
Date: 22-10-2014
DOI: 10.1201/B17624-3
Publisher: American Geophysical Union (AGU)
Date: 2021
DOI: 10.1029/2020JA028378
Abstract: Internal gravity waves (IGWs) play an important role in the planetary atmospheres, which transfer energy and momentum from the lower layers to the upper atmosphere. However, the IGW perturbations and behaviors are not clear in the Mars upper atmosphere, particularly for the horizontal internal gravity waves (hIGWs). In this study, the hIGWs in the upper atmosphere of Mars are estimated and investigated for the first time using both accelerometer (ACC)‐derived mass density and Neutral Gas and Ion Mass Spectrometer‐measured neutral density from Mars Atmosphere and Volatile EvolutioN (MAVEN) mission. The results show that the litudes of hIGWs variations are significantly affected by the dust storms and increase with the altitudes. The larger litudes are triggered in Martian Year (MY) 34 during a global dust event. The characteristics of Ar and CO 2 hIGWs variations are similar. Furthermore, the trend of the CO perturbations seems to follow the CO 2 . However, the dust storms play little role in shaping hIGWs of atomic O. The hIGWs show the stable waveform with the increasing altitudes.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: American Meteorological Society
Date: 11-2008
Abstract: Water vapor plays a key role in the global hydrologic cycle and in climatic change. However, the distribution and variability of water vapor in the troposphere are not understood well—in particular, in China with the complex Tibetan Plateau and the influence of the Asian and Pacific monsoons. In this paper, continuous global positioning system (GPS) observations for 2004–07 in China are used to produce precipitable water vapor (PWV) measurements these measurements constitute the first investigation of PWV distribution and variability over China. It has been found that the stronger water vapor values are in southeastern China and the lower water vapor values are in northwestern China. These distributions are mainly affected by the latitude, topographical features, the season, and the monsoon. Water vapor variations over China are mainly dominated by seasonal variations. The strong seasonal cycles are in summer with maximum water vapor and in winter with minimum water vapor. The PWV in southeastern China has an annual litude of about 15 mm, much larger than in northwestern China at about 4 mm, and meanwhile the time of peak water vapor content is one month earlier than in other regions, probably because of the known rainy season (mei-yu). In addition, significant diurnal variations of water vapor are found over all GPS stations, with a mean litude of about 0.7 mm, and the peak value occurs around noon or midnight, depending on geographic location and topographical features. The semidiurnal cycle is weaker, with a mean litude of about 0.3 mm, and the first peak PWV value appears around noon.
Publisher: MDPI AG
Date: 09-08-2013
DOI: 10.3390/RS5084006
Publisher: MDPI AG
Date: 11-07-2019
DOI: 10.3390/RS11141655
Abstract: Global navigation satellite system (GNSS)-reflectometry is a type of remote sensing technology and can be applied to soil moisture retrieval. Until now, various GNSS-R soil moisture retrieval methods have been reported. However, there still exist some problems due to the complexity of modeling and retrieval process, as well as the extreme uncertainty of the experimental environment and equipment. To investigate the behavior of bistatic GNSS-R soil moisture retrieval process, two ground-truth measurements with different soil conditions were carried out and the performance of the input variables was analyzed from the mathematical statistical aspect. Moreover, the feature of XGBoost method was utilized as well. As a recently developed ensemble machine learning method, the XGBoost method just emerged for the classification of remote sensing and geographic data, to investigate the characterization of the input variables in the GNSS-R soil moisture retrieval. It showed a good correlation with the statistical analysis of ground-truth measurements. The variable contributions for the input data can also be seen and evaluated. The study of the paper provides some experimental insights into the behavior of the GNSS-R soil moisture retrieval. It is worthwhile before establishing models and can also help with understanding the underlying GNSS-R phenomena and interpreting data.
Publisher: American Geophysical Union (AGU)
Date: 10-2018
DOI: 10.1029/2017JA025001
Publisher: IEEE
Date: 07-2006
Publisher: IEEE
Date: 08-2014
Publisher: InTech
Date: 11-03-2015
DOI: 10.5772/58886
Publisher: Elsevier BV
Date: 12-2013
Publisher: InTech
Date: 11-03-2015
DOI: 10.5772/59975
Publisher: American Society for Photogrammetry and Remote Sensing
Date: 12-2022
Abstract: The permanganate index (COD Mn ), defined as a comprehensive index to measure the degree of surface water pollution by organic matter and reducing inorganic matter, plays an important role in indicating water pollution and evaluating aquatic ecological health. However, remote sensing monitoring of water quality is presently focused mainly on phytoplankton, suspended particulate matter, and yellow substance, while there is still great uncertainty in the retrieval of COD Mn . In this study, the Landsat-8 surface reflectance data set from Google Earth Engine and in situ COD Mn measurements were matched. The support vector regression (SVR) machine learning model was calibrated using the matchups. With the SVR model, this study estimates the COD Mn in Hongze Lake, presents the historical spatiotemporal COD Mn distributions, and discusses the affecting factors of the change trend of the COD Mn in Hongze Lake. The results showed that the SVR model adequately estimated COD Mn , with a sum squared error of 1.49 mg 2 /L 2 , a coefficient of determination ( R 2 ) of 0.95, and a root mean square error of 0.15 mg/L. COD Mn in Hongze Lake was high in general and showed a decreasing trend in the past decade. Huai River, Xinsu River, and Huaihongxin River were still the main sources of oxygen-consuming pollutants in Hongze Lake. The wetland natural reserve near Yugou had a significant effect on reducing COD Mn . This study provides not only a scientific reference for the management of COD Mn in Hongze Lake, but also a feasible scheme for remote sensing monitoring of COD Mn in inland water.
Publisher: IEEE
Date: 12-2013
Publisher: Elsevier BV
Date: 12-2013
Publisher: Springer Science and Business Media LLC
Date: 05-2006
DOI: 10.1186/BF03351950
Abstract: Monitoring the variation of the crustal strain is a key issue to understand the physical process of crustal tectonic activities. In this paper, GPS data for the period from March 2000 to February 2004 were analyzed to quantitatively investigate the plate deformation patterns and distributions in the South Korean peninsula. The results show two anomalous rates of strain accumulation in South Korea, a W-E compression accumulation of crustal strain in the East and West parts, and a N-S extension strain accumulation in the middle part along the longitude of about 127.5°E. In addition, the GPS-derived seismic moment accumulation rate is significant and consistent with recent historic earthquakes and fault zones in South Korea. The most anomalous seismic moment rates are in the middle part (about 127.3°E, 35.5°N), North edge (about 128.0°E, 38.0°N) and Northeast part (about 128.5°E, 37.3°N) of South Korea, indicating a high earthquake risk.
Publisher: Copernicus GmbH
Date: 15-12-2021
Abstract: Abstract. In the last decades, Global navigation satellite systems (GNSS) have provided an exceptional opportunity to retrieve atmospheric parameters globally through GNSS radio occultation (GNSS-RO). In this paper, data of 12 GNSS-RO missions from June 2001 to November 2020 with high resolution were used to investigate the possible widening of the tropical belt along with the probable drivers and impacts in both hemispheres. Applying both lapse rate tropopause (LRT) and cold point tropopause (CPT) definitions, the global tropopause height shows increase of approximately 36 m/decade and 60 m/decade, respectively. Moreover, the tropical edge latitude (TEL) estimated based on two tropopause height metrics, in the northern hemisphere (NH) and southern hemisphere (SH), are different from each other. For the first metric, subjective method, the tropical width from GNSS has expansion behavior in NH with ~ 0.41°/decade and a minor expansion in SH with ~ 0.08°/decade. In case of ECMWF Reanalysis v5 (ERA5) there is no significant contraction in both NH and SH. For Atmospheric Infrared Sounder (AIRS), there are expansion behavior in NH with ~ 0.34°/decade and strong contraction in SH with ~ −0.48°/decade. Using the second metric, objective method, the tropical width from GNSS has expansion in NH with ~ 0.13°/decade, and no significant expansion in SH. In case of ERA5, there is no significant signal in NH while SH has a minor contraction. AIRS has an expansion with ~ 0.13°/decade in NH, and strong contraction in SH with ~ −0.37°/decade. The variability of tropopause parameters (temperature and height) is maximum around the TEL locations at both hemispheres. The total column ozone (TCO) shows increasing rates globally, and the rate of increase at the SH is higher than that of the NH. There is a good agreement between the spatial and temporal patterns of TCO variability and the TEL location estimated from GNSS LRT height. Carbon dioxide (CO2), and Methane (CH4), the most important greenhouse gases (GHGs) and the main drivers of global warming, have a global increasing rate and the increasing rate of the NH is similar to that of the SH. The spatial pattern in the NH is located more pole ward than its equivalent at the SH. Both surface temperature and precipitation increase in time and have strong correlation with GNSS LRT height. Both show higher increasing rates at the NH, while the precipitation at the SH has slight decrease and the surface temperature increases. The surface temperature shows a spatial pattern with strong variability, which broadly agrees with the TEL locations. The spatial pattern of precipitation shows northward occurrence. In addition, Standardized Precipitation Evapotranspiration Index (SPEI) has no direct connection with the TEL behavior.
Publisher: IEEE
Date: 03-11-2021
Publisher: Wiley
Date: 04-01-2021
Publisher: MDPI AG
Date: 27-04-2020
DOI: 10.3390/S20092465
Abstract: The traditional altimetry satellite, which is based on pulse-limited radar altimeter, only measures ocean surface heights along tracks hence, leads to poorer accuracy in the east component of the vertical deflections compared to the north component, which in turn limits the final accuracy of the marine gravity field inversion. Wide-swath altimetry using radar interferometry can measure ocean surface heights in two dimensions and, thus, can be used to compute vertical deflections in an arbitrary direction with the same accuracy. This paper aims to investigate the impact of Interferometric Radar Altimeter (InRA) errors on gravity field inversion. The error propagation between gravity anomalies and InRA measurements is analyzed, and formulas of their relationship are given. By giving a group of possible InRA parameters, numerical simulations are conducted to analyze the accuracy of gravity anomaly inversion. The results show that the accuracy of the gravity anomalies is mainly influenced by the phase errors of InRA and the errors of gravity anomalies have a linear approximation relationship with the phase errors. The results also show that the east component of the vertical deflections has almost the same accuracy as the north component.
Publisher: Wiley
Date: 06-2017
DOI: 10.1002/JOC.5153
Publisher: IEEE
Date: 21-11-2021
Publisher: Hindawi Limited
Date: 08-05-2019
DOI: 10.1155/2019/3647473
Abstract: In the past two decades, global navigation satellite system-reflectometry (GNSS-R) has emerged as a new remote sensing technique for soil moisture monitoring. Some experiments showed that the antenna of V polarization is more favorable to receive the reflected signals, and the interference pattern technique (IPT) was used for soil moisture and retrieval of other geophysical parameters. Meanwhile, the lower satellite elevation angles are most impacted by the multipath. However, electromagnetic theoretical properties are not clear for GNSS-R soil moisture retrieval. In this paper, the advanced integral equation model (AIEM) is employed using the wave-synthesis technique to simulate different polarimetric scatterings in the specular directions. Results show when the incident angles are larger than 70°, scattering at RR polarization (the transmitted signal is right-hand circular polarization (RHCP), while the received one is also RHCP) is larger than that at LR polarization (the transmitted signal is RHCP, while the received one is left-hand circular polarization (LHCP)), while scattering at LR polarization is larger than that at RR polarization for the other incident angles (1°∼70°). There is an apparent dip for VV and VR scatterings due to the Brewster angle, which will result in the notch in the final receiving power, and this phenomenon can be used for soil moisture retrieval or vegetation corrections. The volumetric soil moisture (vms) effects on their scattering are also presented. The larger soil moisture will result in lower scattering at RR polarization, and this is very different from the scattering of the other polarizations. It is interesting to note that the surface correlation function only affects the litudes of the scattering coefficients at much less level, but it has no effects on the angular trends of RR and LR polarizations.
Publisher: Informa UK Limited
Date: 19-06-2023
Publisher: MDPI AG
Date: 16-03-2020
DOI: 10.3390/RS12060951
Abstract: The differential code bias (DCB) of the Global Navigation Satellite Systems (GNSS) receiver should be precisely corrected when conducting ionospheric remote sensing and precise point positioning. The DCBs can usually be estimated by the ground GNSS network based on the parameterization of the global ionosphere together with the global ionospheric map (GIM). In order to reduce the spatial-temporal complexities, various algorithms based on GIM and local ionospheric modeling are conducted, but rely on station selection. In this paper, we present a recursive method to estimate the DCBs of Global Positioning System (GPS) satellites based on a recursive filter and independent reference station selection procedure. The satellite and receiver DCBs are estimated once per local day and aligned with the DCB product provided by the Center for Orbit Determination in Europe (CODE). From the statistical analysis with CODE DCB products, the results show that the accuracy of GPS satellite DCB estimates obtained by the recursive method can reach about 0.10 ns under solar quiet condition. The influence of stations with bad performances on DCB estimation can be reduced through the independent iterative reference selection. The accuracy of local ionospheric modeling based on recursive filter is less than 2 Total Electron Content Unit (TECU) in the monthly median sense. The performance of the recursive method is also evaluated under different solar conditions and the results show that the local ionospheric modeling is sensitive to solar conditions. Moreover, the recursive method has the potential to be implemented in the near real-time DCB estimation and GNSS data quality check.
Publisher: Springer Science and Business Media LLC
Date: 30-09-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2009
Publisher: MDPI AG
Date: 30-10-2023
DOI: 10.3390/W15213802
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: IEEE
Date: 06-2018
Publisher: Elsevier BV
Date: 08-2021
Publisher: Copernicus GmbH
Date: 06-03-2018
DOI: 10.5194/ISPRS-ARCHIVES-XLII-3-W4-83-2018
Abstract: Abstract. Sea level rise causes devastating effects on coastal habitats. For ex le, coastal erosion and saltwater intrusion are major threats for the Black Sea coasts. So, determining sea level changes in the Black Sea is important in terms of coastal risk assessment and coastal planning. In this study, present-day sea level change in the Black Sea is estimated from satellite altimetry and gravity measurements. Altimetry data demonstrate that the Black Sea level has risen at an average rate of 2.5 ± 0.5 mm/year from January 1993 to May 2017. During this period, inter-annual variability of the non-seasonal sea level change is quite strong. Furthermore, mass contribution to this change for the period 2002–2017 has been detected as 2.3 ± 1.0 mm/year from the Gravity Recovery And Climate Experiment (GRACE) mascon solutions.
Publisher: Copernicus GmbH
Date: 10-08-2021
DOI: 10.5194/ISPRS-ARCHIVES-XLIV-M-3-2021-63-2021
Abstract: Abstract. Scene classification plays an important role in remote sensing field. Traditional approaches use high-resolution remote sensing images as data source to extract powerful features. Although these kind of methods are common, the model performance is severely affected by the image quality of the dataset, and the single modal (source) of images tend to cause the mission of some scene semantic information, which eventually degrade the classification accuracy. Nowadays, multi-modal remote sensing data become easy to obtain since the development of remote sensing technology. How to carry out scene classification of cross-modal data has become an interesting topic in the field. To solve the above problems, this paper proposes using feature fusion for cross-modal scene classification of remote sensing image, i.e., aerial and ground street view images, expecting to use the advantages of aerial images and ground street view data to complement each other. Our cross- modal model is based on Siamese Network. Specifically, we first train the cross-modal model by pairing different sources of data with aerial image and ground data. Then, the trained model is used to extract the deep features of the aerial and ground image pair, and the features of the two perspectives are fused to train a SVM classifier for scene classification. Our approach has been demonstrated using two public benchmark datasets, AiRound and CV-BrCT. The preliminary results show that the proposed method achieves state-of-the-art performance compared with the traditional methods, indicating that the information from ground data can contribute to aerial image classification.
Publisher: Elsevier BV
Date: 07-2020
Publisher: Wiley
Date: 07-09-2010
Publisher: American Society for Photogrammetry and Remote Sensing
Date: 04-2023
Abstract: Terrestrial water storage (TWS) plays a vital role in climatological and hydrological processes. Most of the developed drought indices from the Gravity Recovery and Climate Experiment (GRACE) over Africa neglected the influencing roles of in idual water storage components in calculating the drought index and thus may either underestimate or overestimate drought characteristics. In this paper, we proposed a Weighted Water Storage Deficit Index for drought assessment over the major river basins in Africa (i. e., Nile, Congo, Niger, Zambezi, and Orange) with accounting for the contribution of each TWS component on the drought signal. We coupled the GRACE data and WaterGAP Global Hydrology Model through utilizing the component contribution ratio as the weight. The results showed that water storage components demonstrated distinctly different contributions to TWS variability and thus drought signal response in onset and duration. The most severe droughts over the Nile, Congo, Niger, Zambezi, and Orange occurred in 2006, 2012, 2006, 2006, and 2003, respectively. The most prolonged drought of 84 months was observed over the Niger basin. This study suggests that considering the weight of in idual components in the drought index provides more reasonable and realistic drought estimates over large basins in Africa from GRACE.
Publisher: Elsevier BV
Date: 11-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2015
Publisher: Oxford University Press (OUP)
Date: 12-05-2016
DOI: 10.1093/GJI/GGW182
Publisher: Elsevier BV
Date: 10-2015
Location: China
Location: China
Location: Korea, Republic of
No related grants have been discovered for Shuanggen Jin.