ORCID Profile
0000-0003-2809-2376
Current Organisation
University of Technology Sydney
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Ecological Impacts of Climate Change | Ecological Applications | Photogrammetry and Remote Sensing | Environmental Monitoring | Terrestrial Ecology | Ecosystem Function | Landscape Ecology |
ANZSRC Socio-Economic Objective (SEO)
Effects of Climate Change and Variability on Australia (excl. Social Impacts) | Flora, Fauna and Biodiversity at Regional or Larger Scales | Environmental Health | Remnant Vegetation and Protected Conservation Areas at Regional or Larger Scales | Ecosystem Assessment and Management of Forest and Woodlands Environments | Ecosystem Assessment and Management of Sparseland, Permanent Grassland and Arid Zone Environments | Climate Variability (excl. Social Impacts) | Forest and Woodlands Water Management | Health Protection and/or Disaster Response
Related Links
Publications
Groundwater-dependent ecosystems: recent insights, new techniques and an ecosystem-scale threshold response
Publisher: Copernicus GmbH
Date: 04-05-2015
DOI: 10.5194/HESSD-12-4677-2015
Abstract: Abstract. Groundwater-dependent ecosystems (GDEs) are at risk globally due to unsustainable levels of groundwater extraction, especially in arid and semi-arid regions. In this review, we examine recent developments in the ecohydrology of GDEs with a focus on three knowledge gaps: (1) how do we locate GDEs, (2) how much water is transpired from shallow aquifers by GDEs and (3) what are the responses of GDEs to excessive groundwater extraction? The answers to these questions will determine water allocations that are required to sustain functioning of GDEs and to guide regulations on groundwater extraction to avoid negative impacts on GDEs. We discuss three methods for identifying GDEs: (1) fluctuations in depth-to-groundwater that are associated with diurnal variations in transpiration, (2) stable isotope analysis of water sources in the transpiration stream and (3) remote sensing methods. We then discuss several methods for estimating rates of GW use, including direct measurement using sapflux or eddy covariance technologies, estimation of a climate wetness index within a Budyko framework, spatial distribution of ET using remote sensing, groundwater modelling and stable isotopes. Remote sensing methods often rely on direct measurements to calibrate the relationship between vegetation indices and ET. ET from GDEs is also determined using hydrologic models of varying complexity, from the "White method" to fully coupled, variable saturation models. Combinations of methods are typically employed to obtain clearer insight into the components of groundwater discharge in GDEs, such as the proportional importance of transpiration vs. evaporation (e.g., using stable isotopes) or from groundwater vs. rainwater sources. Groundwater extraction can have severe consequences on structure and function of GDEs. In the most extreme cases, phreatophytes experience crown dieback and death following groundwater drawdown. We provide a brief review of two case studies of the impacts of GW extraction and discuss the use of C isotope ratios in xylem to reveal past influences of GW extraction. We conclude with a discussion of a depth-to-groundwater threshold in mesic and semi-arid GDEs. Across this threshold, significant changes occur in ecosystem structure and function.
Response of dryland vegetation under extreme wet events with satellite measures of greenness and fluorescence
Publisher: Elsevier BV
Date: 10-2022
DOI: 10.1016/J.SCITOTENV.2022.156860
Abstract: Extreme wet events in central Australia triggered large vegetation responses that contributed greatly to large global land carbon sink anomalies. There remain significant uncertainties on the extent to which these events over dryland vegetation can be monitored and assessed with satellite data. In this study, we investigated the vegetation responses of the major Australian semiarid biomes to two extreme wet events utilizing multi-satellite observations of (1) solar-induced chlorophyll fluorescence (SIF), as a proxy for photosynthetic activity and (2) the enhanced vegetation index (EVI), as a measure of canopy chlorophyll or greenness. We related these satellite observations with gross primary productivity (GPP) estimated from eddy covariance tower sites, as a performance benchmark. The C
Optical characterization of the Brazilian Savanna physiognomies for improved land cover monitoring of the cerrado biome: preliminary assessments from an airborne campaign over an LBA core site
Publisher: Elsevier BV
Date: 02-2200
The AusPollen partnership project
Publisher: Elsevier BV
Date: 11-2022
DOI: 10.1016/J.ENVRES.2022.113762
Abstract: Allergic rhinitis affects half a billion people globally, including a fifth of the Australian population. As the foremost outdoor allergen source, ambient grass pollen exposure is likely to be altered by climate change. The AusPollen Partnership aimed to standardize pollen monitoring and examine broad-scale biogeographical and meteorological factors influencing interannual variation in seasonality of grass pollen aerobiology in Australia. Daily airborne grass and other pollen concentrations in four eastern Australian cities separated by over 1700 km, were simultaneously monitored using Hirst-style s lers following the Australian Interim Pollen and Spore Monitoring Standard and Protocols over four seasons from 2016 to 2020. The grass seasonal pollen integral was determined. Gridded rainfall, temperature, and satellite-derived grassland sources up to 100 km from the monitoring site were analysed. The complexity of grass pollen seasons was related to latitude with multiple major summer-autumn peaks in Brisbane, major spring and minor summer peaks in Sydney and Canberra, and single major spring peaks occurring in Melbourne. The subtropical site of Brisbane showed a higher proportion of grass out of total pollen than more temperate sites. The magnitude of the grass seasonal pollen integral was correlated with pasture greenness, rainfall and number of days over 30 °C, preceding and within the season, up to 100 km radii from monitoring sites. Interannual fluctuations in Australian grass pollen season magnitude are strongly influenced by regional biogeography and both pre- and in-season weather. This first continental scale, Southern Hemisphere standardized aerobiology dataset forms the basis to track shifts in pollen seasonality, bio ersity and impacts on allergic respiratory diseases.
Monitoring Savanna Vegetation Phenology Using Advanced Himawari Imager
Publisher: IEEE
Date: 11-07-2021
Land cover conversion and degradation analyses through coupled soil~plant biophysical parameters derived from hyperspectral eo-1 hyperion
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2003
Radiative transfer in shrub savanna sites in Niger: preliminary results from HAPEX-Sahel. 1. Modelling surface reflectance using a geometric-optical approach
Publisher: Elsevier BV
Date: 07-1994
Estimating Net Primary Productivity of Croplands in Indo-Gangetic Plains Using GOME-2 Sun-Induced Fluorescence and MODIS NDVI
Publisher: Current Science Association
Date: 25-03-2018
A modified soil adjusted vegetation index
Publisher: Elsevier BV
Date: 05-1994
Interpretation of vegetation indices derived from multi-temporal SPOT images
Publisher: Elsevier BV
Date: 04-1993
Accurate Measurement of Tropical Forest Canopy Heights and Aboveground Carbon Using Structure From Motion
Publisher: MDPI AG
Date: 17-04-2019
DOI: 10.3390/RS11080928
Abstract: Unmanned aerial vehicles are increasingly used to monitor forests. Three-dimensional models of tropical rainforest canopies can be constructed from overlapping photos using Structure from Motion (SfM), but it is often impossible to map the ground elevation directly from such data because canopy gaps are rare in rainforests. Without knowledge of the terrain elevation, it is, thus, difficult to accurately measure the canopy height or forest properties, including the recovery stage and aboveground carbon density. Working in an Indonesian ecosystem restoration landscape, we assessed how well SfM derived the estimates of the canopy height and aboveground carbon density compared with those from an airborne laser scanning (also known as LiDAR) benchmark. SfM systematically underestimated the canopy height with a mean bias of approximately 5 m. The linear models suggested that the bias increased quadratically with the top-of-canopy height for short, even-aged, stands but linearly for tall, structurally complex canopies ( m). The predictions based on the simple linear model were closely correlated to the field-measured heights when the approach was applied to an independent survey in a different location ( R 2 = 67% and RMSE = 1.85 m), but a negative bias of 0.89 m remained, suggesting the need to refine the model parameters with additional training data. Models that included the metrics of canopy complexity were less biased but with a reduced R 2 . The inclusion of ground control points (GCPs) was found to be important in accurately registering SfM measurements in space, which is essential if the survey requirement is to produce small-scale restoration interventions or to track changes through time. However, at the scale of several hectares, the top-of-canopy height and above-ground carbon density estimates from SfM and LiDAR were very similar even without GCPs. The ability to produce accurate top-of-canopy height and carbon stock measurements from SfM is game changing for forest managers and restoration practitioners, providing the means to make rapid, low-cost surveys over hundreds of hectares without the need for LiDAR.
Spectral response of a plant canopy with different soil backgrounds
Publisher: Elsevier BV
Date: 02-1985
Characteristics of Greening along Altitudinal Gradients on the Qinghai–Tibet Plateau Based on Time-Series Landsat Images
Publisher: MDPI AG
Date: 17-05-2022
DOI: 10.3390/RS14102408
Abstract: The Qinghai–Tibet Plateau (QTP) is ecologically fragile and is especially sensitive to climate change. Previous studies have shown that the vegetation on the QTP is undergoing overall greening with variations along altitudinal gradients. However, the mechanisms that cause the differences in the spatiotemporal patterns of vegetation greening among different types of terrain and vegetation have not received sufficient attention. Therefore, in this study, we used a Landsat NDVI time-series for the period 1992–2020 and climate data to observe the effects of terrain and vegetation types on the spatiotemporal patterns in vegetation greening on the QTP and to analyze the factors driving this greening using the geographical detector and the velocity of the vertical movement of vegetation greenness isolines. The results showed the following: (1) The vertical movement of the vegetation greenness isolines was affected by the temperature and precipitation at all elevations. The precipitation had a more substantial effect than the temperature below 3000 m. In contrast, above 3000 m, the temperature had a greater effect than the precipitation. (2) The velocity of the vertical movement of the vegetation greenness isolines of woody plants was higher than that of herbaceous plants. (3) The influence of slope on the vertical movement of vegetation greenness isolines was more significant than that of the aspect. The results of this study provided details of the spatiotemporal differences in vegetation greening between different types of terrain and vegetation at a 30-m scale as well as of the underlying factors driving this greening. These results will help to support ecological protection policies on the QTP.
Assessing Soil Erosion Hazards Using Land-Use Change and Landslide Frequency Ratio Method: A Case Study of Sabaragamuwa Province, Sri Lanka
Publisher: MDPI AG
Date: 07-05-2020
DOI: 10.3390/RS12091483
Abstract: This study aims to identify the vulnerable landscape areas using landslide frequency ratio and land-use change associated soil erosion hazard by employing geo-informatics techniques and the revised universal soil loss equation (RUSLE) model. Required datasets were collected from multiple sources, such as multi-temporal Landsat images, soil data, rainfall data, land-use land-cover (LULC) maps, topographic maps, and details of the past landslide incidents. Landsat satellite images from 2000, 2010, and 2019 were used to assess the land-use change. Geospatial input data on rainfall, soil type, terrain characteristics, and land cover were employed for soil erosion hazard classification and mapping. Landscape vulnerability was examined on the basis of land-use change, erosion hazard class, and landslide frequency ratio. Then the erodible hazard areas were identified and prioritized at the scale of river distribution zones. The image analysis of Sabaragamuwa Province in Sri Lanka from 2000 to 2019 indicates a significant increase in cropping areas (17.96%) and urban areas (3.07%), whereas less dense forest and dense forest coverage are significantly reduced (14.18% and 6.46%, respectively). The average annual soil erosion rate increased from 14.56 to 15.53 t/ha/year from year 2000 to 2019. The highest landslide frequency ratios are found in the less dense forest area and cropping area, and were identified as more prone to future landslides. The river distribution zones Athtanagalu Oya (A-2), Kalani River-south (A-3), and Kalani River- north (A-9), were identified as immediate priority areas for soil conservation.
Retrieval of crop biophysical parameters from Sentinel-2 remote sensing imagery
Publisher: Elsevier BV
Date: 08-2019
Grassland Phenology and Meteorology Co-Influence Grass Pollen Counts in Victoria, Australia
Publisher: Environmental Health Perspectives
Date: 24-09-2018
An isoline-based translation technique of spectral vegetation index using eo-1 hyperion data
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2003
Global-scale analysis of vegetation indices for moderate resolution monitoring of terrestrial vegetation
Publisher: SPIE
Date: 17-12-1999
DOI: 10.1117/12.373090
Vegetation Dynamics
Publisher: Cambridge University Press
Date: 31-12-2015
Abstract: Understanding ecosystem structure and function requires familiarity with the techniques, knowledge and concepts of the three disciplines of plant physiology, remote sensing and modelling. This is the first textbook to provide the fundamentals of these three domains in a single volume. It then applies cross-disciplinary insights to multiple case studies in vegetation and landscape science. A key feature of these case studies is an examination of relationships among climate, vegetation structure and vegetation function, to address fundamental research questions. This book is for advanced students and researchers who need to understand and apply knowledge from the disciplines of plant physiology, remote sensing and modelling. It allows readers to integrate and synthesise knowledge to produce a holistic understanding of the structure, function and behaviour of forests, woodlands and grasslands.
A spatially explicit land surface phenology data product for science, monitoring and natural resources management applications
Publisher: Elsevier BV
Date: 02-2015
Reviews and syntheses: Australian vegetation phenology: New insights from satellite remote sensing and digital repeat photography
Publisher: Copernicus GmbH
Date: 13-09-2016
Abstract: Abstract. Phenology is the study of periodic biological occurrences and can provide important insights into the influence of climatic variability and change on ecosystems. Understanding Australia's vegetation phenology is a challenge due to its erse range of ecosystems, from savannas and tropical rainforests to temperate eucalypt woodlands, semi-arid scrublands, and alpine grasslands. These ecosystems exhibit marked differences in seasonal patterns of canopy development and plant life-cycle events, much of which deviates from the predictable seasonal phenological pulse of temperate deciduous and boreal biomes. Many Australian ecosystems are subject to irregular events (i.e. drought, flooding, cyclones, and fire) that can alter ecosystem composition, structure, and functioning just as much as seasonal change. We show how satellite remote sensing and ground-based digital repeat photography (i.e. phenocams) can be used to improve understanding of phenology in Australian ecosystems. First, we examine temporal variation in phenology on the continental scale using the enhanced vegetation index (EVI), calculated from MODerate resolution Imaging Spectroradiometer (MODIS) data. Spatial gradients are revealed, ranging from regions with pronounced seasonality in canopy development (i.e. tropical savannas) to regions where seasonal variation is minimal (i.e. tropical rainforests) or high but irregular (i.e. arid ecosystems). Next, we use time series colour information extracted from phenocam imagery to illustrate a range of phenological signals in four contrasting Australian ecosystems. These include greening and senescing events in tropical savannas and temperate eucalypt understorey, as well as strong seasonal dynamics of in idual trees in a seemingly static evergreen rainforest. We also demonstrate how phenology links with ecosystem gross primary productivity (from eddy covariance) and discuss why these processes are linked in some ecosystems but not others. We conclude that phenocams have the potential to greatly improve the current understanding of Australian ecosystems. To facilitate the sharing of this information, we have formed the Australian Phenocam Network (phenocam.org.au/).
A novel red‐edge spectral index for retrieving the leaf chlorophyll content
Publisher: Wiley
Date: 18-10-2022
Abstract: The leaf chlorophyll content (Chl leaf ) is a crucial vegetation parameter in carbon cycle modelling and agricultural monitoring at local, regional and global scales. The red‐edge spectral region is sensitive to variations in Chl leaf. An increasing number of sensors are capable of s ling red‐edge bands, providing opportunities to estimate Chl leaf . However, the contributions of canopy/foliar/soil factors are always combined in the reflectance signal, which limits the generalizability of vegetation index (VI)‐based Chl leaf inversions. This study aims to propose a new red‐edge chlorophyll index to decouple the effects of the canopy and soil background from the Chl leaf estimation. The chlorophyll sensitive index (CSI) was proposed, and the regression equations between the CSI and Chl leaf were acquired using PROSAIL (PROSPECT + SAIL) and the 4‐Scale‐PROSPECT model. Sensitivity analyses showed that the CSI is resistant to variations in the canopy structure and soil background. Validation results obtained using 308 ground‐measured s les over nine sites world‐wide revealed that CSI improves the Chl leaf retrieval accuracy (root mean square error (RMSE = 9.39 μg cm −2 ) compared with the existing Medium Resolution Imaging Spectrometer (MERIS) terrestrial chlorophyll index (MTCI RMSE = 13.00 μg cm −2 ). Moreover, the CSI method steadily achieves a highly accurate inversion under different LAI and Chl leaf conditions. Based on the CSI regression method, a Chl leaf product with a 30‐m/10‐day resolution across China was generated. The CSI is sensitive to Chl leaf but resistant to canopy structure and soil moisture parameters, and it has the potential to explicitly retrieve leaf‐scale biochemistry in ecosystem modelling and ecological applications.
An Integrated Field and Remote Sensing Method for Mapping Seagrass Species, Cover, and Biomass in Southern Thailand
Publisher: MDPI AG
Date: 30-03-2016
DOI: 10.3390/RS8040292
Comparison of vegetation index compositing scenarios: BRDF versus maximum VI approaches
Publisher: IEEE
Date: 1996
Leaf Area Index Estimates Using Remotely Sensed Data and BRDF Models in a Semiarid Region
Publisher: Elsevier BV
Date: 07-2000
Urban−rural gradients reveal joint control of elevated CO2 and temperature on extended photosynthetic seasons
Publisher: Springer Science and Business Media LLC
Date: 24-06-2019
DOI: 10.1038/S41559-019-0931-1
Abstract: Photosynthetic phenology has large effects on the land-atmosphere carbon exchange. Due to limited experimental assessments, a comprehensive understanding of the variations of photosynthetic phenology under future climate and its associated controlling factors is still missing, despite its high sensitivities to climate. Here, we develop an approach that uses cities as natural laboratories, since plants in urban areas are often exposed to higher temperatures and carbon dioxide (CO
Terrestrial carbon sinks in the Brazilian Amazon and Cerrado region predicted from MODIS satellite data and ecosystem modeling
Publisher: Copernicus GmbH
Date: 16-01-2009
Abstract: Abstract. A simulation model based on satellite observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate monthly carbon fluxes in terrestrial ecosystems of Brazilian Amazon and Cerrado regions over the period 2000–2004. Net ecosystem production (NEP) flux for atmospheric CO2 in the region for these years was estimated. Consistently high carbon sink fluxes in terrestrial ecosystems on a yearly basis were found in the western portions of the states of Acre and Rondônia and the northern portions of the state of Pará. These areas were not significantly impacted by the 2002–2003 El Niño event in terms of net annual carbon gains. Areas of the region that show periodically high carbon source fluxes from terrestrial ecosystems to the atmosphere on yearly basis were found throughout the state of Maranhão and the southern portions of the state of Amazonas. As demonstrated though tower site comparisons, NEP modeled with monthly MODIS Enhanced Vegetation Index (EVI) inputs closely resembles the measured seasonal carbon fluxes at the LBA Tapajos tower site. Modeling results suggest that the capacity for use of MODIS Enhanced Vegetation Index (EVI) data to predict seasonal uptake rates of CO2 in Amazon forests and Cerrado woodlands is strong.
Assessment of Phenologic Variability in Amazon Tropical Rainforests Using Hyperspectral Hyperion and MODIS Satellite Data
Publisher: CRC Press
Date: 26-02-2008
A Technique for Reflectance Calibration of Airborne Hyperspectral Spectrometer Data Using a Broad, Multiband Radiometer
Publisher: CRC Press
Date: 26-02-2008
Impacts of spatial heterogeneity patterns on long-term trends of Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature time series
Publisher: SPIE-Intl Soc Optical Eng
Date: 31-01-2020
Drought rapidly diminishes the large net CO2 uptake in 2011 over semi-arid Australia
Publisher: Springer Science and Business Media LLC
Date: 25-11-2016
DOI: 10.1038/SREP37747
Abstract: Each year, terrestrial ecosystems absorb more than a quarter of the anthropogenic carbon emissions, termed as land carbon sink. An exceptionally large land carbon sink anomaly was recorded in 2011, of which more than half was attributed to Australia. However, the persistence and spatially attribution of this carbon sink remain largely unknown. Here we conducted an observation-based study to characterize the Australian land carbon sink through the novel coupling of satellite retrievals of atmospheric CO 2 and photosynthesis and in-situ flux tower measures. We show the 2010–11 carbon sink was primarily ascribed to savannas and grasslands. When all biomes were normalized by rainfall, shrublands however, were most efficient in absorbing carbon. We found the 2010–11 net CO 2 uptake was highly transient with rapid dissipation through drought. The size of the 2010–11 carbon sink over Australia (0.97 Pg) was reduced to 0.48 Pg in 2011–12, and was nearly eliminated in 2012–13 (0.08 Pg). We further report evidence of an earlier 2000–01 large net CO 2 uptake, demonstrating a repetitive nature of this land carbon sink. Given a significant increasing trend in extreme wet year precipitation over Australia, we suggest that carbon sink episodes will exert greater future impacts on global carbon cycle.
Passive microwave and optical index approaches for estimating surface conductance and evapotranspiration in forest ecosystems
Publisher: Elsevier BV
Date: 11-2015
Optical–Biophysical Relationships of Vegetation Spectra without Background Contamination
Publisher: Elsevier BV
Date: 12-2000
Reply to Magnani et al.: Linking large-scale chlorophyll fluorescence observations with cropland gross primary production
Publisher: Proceedings of the National Academy of Sciences
Date: 03-06-2014
Multisensor reflectance and vegetation index comparisons of Amazon tropical forest phenology with hyperspectral Hyperion data
Publisher: SPIE
Date: 13-09-2007
DOI: 10.1117/12.734974
Overview of the radiometric and biophysical performance of the MODIS vegetation indices
Publisher: Elsevier BV
Date: 11-2002
Effects of Tropical Forest Degradation on Amazon Forest Phenology
Publisher: IEEE
Date: 26-09-2020
Methodology for Bare Soil Detection and Discrimination by Landsat TM Image
Publisher: Bentham Science Publishers Ltd.
Date: 29-05-2009
Investigation of soil influences in AVHRR red and near-infrared vegetation index imagery
Publisher: Informa UK Limited
Date: 06-1991
Derivation of a MODIS-compatible enhanced vegetation index from visible infrared imaging radiometer suite spectral reflectances using vegetation isoline equations
Publisher: SPIE-Intl Soc Optical Eng
Date: 16-12-2013
Analysis and optimization of the MODIS leaf area index algorithm retrievals over broadleaf forests
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2005
Vegetation change monitoring with spectral indices: the importance of view and sun angle standardized data
Publisher: SPIE
Date: 17-12-1999
DOI: 10.1117/12.373099
Growth Analysis of Cottons with Differing Maturities1
Publisher: Wiley
Date: 1987
Relationship between evapotranspiration and precipitation pulses in a semiarid rangeland estimated by moisture flux towers and MODIS vegetation indices
Publisher: Elsevier BV
Date: 08-2007
Structural complexity biases vegetation greenness measures
Publisher: Springer Science and Business Media LLC
Date: 14-09-2023
A Radiative Transfer Model for Patchy Landscapes Based on Stochastic Radiative Transfer Theory
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2020
Forest understory characterization at regional levels with satellite data: a conceptual approach
Publisher: SPIE
Date: 11-12-1998
DOI: 10.1117/12.332757
Evaluation of the importance of nonlinear spectral mixing in coniferous forests
Publisher: SPIE
Date: 11-12-1998
DOI: 10.1117/12.332758
A feedback based modification of the NDVI to minimize canopy background and atmospheric noise
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-1995
DOI: 10.1109/36.377946
Sun-Angle Effects on Remote-Sensing Phenology Observed and Modelled Using Himawari-8
Publisher: MDPI AG
Date: 23-04-2020
DOI: 10.3390/RS12081339
Abstract: Satellite remote sensing of vegetation at regional to global scales is undertaken at considerable variations in solar zenith angle (SZA) across space and time, yet the extent to which these SZA variations matter for the retrieval of phenology remains largely unknown. Here we examined the effect of seasonal and spatial variations in SZA on retrieving vegetation phenology from time series of the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) across a study area in southeastern Australia encompassing forest, woodland, and grassland sites. The vegetation indices (VI) data span two years and are from the Advanced Himawari Imager (AHI), which is onboard the Japanese Himawari-8 geostationary satellite. The semi-empirical RossThick-LiSparse-Reciprocal (RTLSR) bidirectional reflectance distribution function (BRDF) model was inverted for each spectral band on a daily basis using 10-minute reflectances acquired by H-8 AHI at different sun-view geometries for each site. The inverted RTLSR model was then used to forward calculate surface reflectance at three constant SZAs (20°, 40°, 60°) and one seasonally varying SZA (local solar noon), all normalised to nadir view. Time series of NDVI and EVI adjusted to different SZAs at nadir view were then computed, from which phenological metrics such as start and end of growing season were retrieved. Results showed that NDVI sensitivity to SZA was on average nearly five times greater than EVI sensitivity. VI sensitivity to SZA also varied among sites (biome types) and phenological stages, with NDVI sensitivity being higher during the minimum greenness period than during the peak greenness period. Seasonal SZA variations altered the temporal profiles of both NDVI and EVI, with more pronounced differences in magnitude among NDVI time series normalised to different SZAs. When using VI time series that allowed SZA to vary at local solar noon, the uncertainties in estimating start, peak, end, and length of growing season introduced by local solar noon varying SZA VI time series, were 7.5, 3.7, 6.5, and 11.3 days for NDVI, and 10.4, 11.9, 6.5, and 8.4 days for EVI respectively, compared to VI time series normalised to a constant SZA. Furthermore, the stronger SZA dependency of NDVI compared with EVI, resulted in up to two times higher uncertainty in estimating annual integrated VI, a commonly used remote-sensing proxy for vegetation productivity. Since commonly used satellite products are not generally normalised to a constant sun-angle across space and time, future studies to assess the sun-angle effects on satellite applications in agriculture, ecology, environment, and carbon science are urgently needed. Measurements taken by new-generation geostationary (GEO) satellites offer an important opportunity to refine this assessment at finer temporal scales. In addition, studies are needed to evaluate the suitability of different BRDF models for normalising sun-angle across a broad spectrum of vegetation structure, phenological stages and geographic locations. Only through continuous investigations on how sun-angle variations affect spatiotemporal vegetation dynamics and what is the best strategy to deal with it, can we achieve a more quantitative remote sensing of true signals of vegetation change across the entire globe and through time.
Scaling effects on area-averaged fraction of vegetation cover derived using a linear mixture model with two-band spectral vegetation index constraints
Publisher: SPIE-Intl Soc Optical Eng
Date: 19-05-2014
Productivity and evapotranspiration of two contrasting semiarid ecosystems following the 2011 global carbon land sink anomaly
Publisher: Elsevier BV
Date: 04-2016
Integrating Remote Sensing and Ground Methods to Estimate Evapotranspiration
Publisher: Informa UK Limited
Date: 06-06-2007
Parameterization of an ecosystem light-use-efficiency model for predicting savanna GPP using MODIS EVI
Publisher: Elsevier BV
Date: 11-2014
An Analysis of Angle-Based With Ratio-Based Vegetation Indices
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2006
The Moderate Resolution Imaging Spectroradiometer (MODIS): land remote sensing for global change research
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-1998
DOI: 10.1109/36.701075
Spectral Mixtures
Publisher: CRC Press
Date: 22-12-2005
Terrestrial total water storage dynamics of Australia's recent dry and wet events
Publisher: IEEE
Date: 07-2015
Land surface phenology indicators retrieved across diverse ecosystems using a modified threshold algorithm
Publisher: Elsevier BV
Date: 03-2023
Separation of soil-plant spectral mixtures by factor analysis
Publisher: Elsevier BV
Date: 06-1986
A systems based modification of the NDVI to minimize soil and atmospheric noise
Publisher: IEEE
Date: 1994
A comparison of vegetation indices over a global set of TM images for EOS-MODIS
Publisher: Elsevier BV
Date: 03-1997
Terrestrial Carbon Sinks for the United States Predicted from MODIS Satellite Data and Ecosystem Modeling
Publisher: American Meteorological Society
Date: 08-2007
DOI: 10.1175/EI228.1
Abstract: A simulation model based on satellite observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate monthly carbon fluxes in terrestrial ecosystems of the conterminous United States over the period 2001–04. Predicted net ecosystem production (NEP) flux for atmospheric CO2 in the United States was estimated as annual net sink of about +0.2 Pg C in 2004. Regional climate patterns were reflected in the predicted annual NEP flux from the model, which showed extensive carbon sinks in ecosystems of the southern and eastern regions in 2003–04, and major carbon source fluxes from ecosystems in the Rocky Mountain and Pacific Northwest regions in 2003–04. As demonstrated through tower site comparisons, net primary production (NPP) modeled with monthly MODIS enhanced vegetation index (EVI) inputs closely resembles both the measured high- and low-season carbon fluxes. Modeling results suggest that the capacity of the NASA Carnegie Ames Stanford Approach (CASA) model to use 8-km resolution MODIS EVI data to predict peak growing season uptake rates of CO2 in irrigated croplands and moist temperate forests is strong.
Assessing the Impact of Extreme Droughts on Dryland Vegetation by Multi-Satellite Solar-Induced Chlorophyll Fluorescence
Publisher: MDPI AG
Date: 25-03-2022
DOI: 10.3390/RS14071581
Abstract: Satellite-estimated solar-induced chlorophyll fluorescence (SIF) is proven to be an effective indicator for dynamic drought monitoring, while the capability of SIF to assess the variability of dryland vegetation under water and heat stress remains challenging. This study presents an analysis of the responses of dryland vegetation to the worst extreme drought over the past two decades in Australia, using multi-source spaceborne SIF derived from the Global Ozone Monitoring Experiment-2 (GOME-2) and TROPOspheric Monitoring Instrument (TROPOMI). Vegetation functioning was substantially constrained by this extreme event, especially in the interior of Australia, in which there was hardly seasonal growth detected by neither satellite-based observations nor tower-based flux measurements. At a 16-day interval, both SIF and enhanced vegetation index (EVI) can timely capture the reduction at the onset of drought over dryland ecosystems. The results demonstrate that satellite-observed SIF has the potential for characterizing and monitoring the spatiotemporal dynamics of drought over water-limited ecosystems, despite coarse spatial resolution coupled with high-retrieval noise as compared with EVI. Furthermore, our study highlights that SIF retrieved from TROPOMI featuring substantially enhanced spatiotemporal resolution has the promising capability for accurately tracking the drought-induced variation of heterogeneous dryland vegetation.
Resposta espectral de solos em razão do ângulo de visada, da umidade e da rugosidade superficial
Publisher: FapUNIFESP (SciELO)
Date: 12-2000
DOI: 10.1590/S0100-204X2000001200018
Abstract: Este trabalho teve por objetivo avaliar as variações do fator de refletância bidirecional (FRB) de três séries de solo (McAllister, Stronghold e Epitaph) da microbacia experimental de Walnut Gulch (Arizona, EUA) em razão do ângulo de visada, da rugosidade superficial e do teor de umidade. Foram consideradas as faixas espectrais do visível e do infravermelho próximo e médio presentes no sensor TM, e os resultados foram expressos em termos de FRB em relação à resposta no Nadir (FRB relativo). O anisotropismo variou de solo para solo e foi maior nas menores faixas espectrais, nos ângulos de visada maiores localizados na direção do retroespalhamento, nos ângulos solar-zenitais maiores, e na condição de solo seco. No solo Epitaph (único solo submetido ao estudo de rugosidade) o anisotropismo foi também maior na superfície mais rugosa. Entretanto, uma melhor diferenciação entre as superfícies lisa e rugosa do solo Epitaph foi obtida na direção do espalhamento da energia refletida. Diferenças na escala e nos métodos de obtenção dos dados são apontadas como causas do realce do comportamento anisotrópico dos dados obtidos em condições de laboratório, em comparação com os dados de c o.
Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network
Publisher: Wiley
Date: 22-03-2022
DOI: 10.1111/GCB.16141
Abstract: In 2020, the Australian and New Zealand flux research and monitoring network, OzFlux, celebrated its 20 th anniversary by reflecting on the lessons learned through two decades of ecosystem studies on global change biology. OzFlux is a network not only for ecosystem researchers, but also for those ‘next users’ of the knowledge, information and data that such networks provide. Here, we focus on eight lessons across topics of climate change and variability, disturbance and resilience, drought and heat stress and synergies with remote sensing and modelling. In distilling the key lessons learned, we also identify where further research is needed to fill knowledge gaps and improve the utility and relevance of the outputs from OzFlux. Extreme climate variability across Australia and New Zealand (droughts and flooding rains) provides a natural laboratory for a global understanding of ecosystems in this time of accelerating climate change. As evidence of worsening global fire risk emerges, the natural ability of these ecosystems to recover from disturbances, such as fire and cyclones, provides lessons on adaptation and resilience to disturbance. Drought and heatwaves are common occurrences across large parts of the region and can tip an ecosystem's carbon budget from a net CO 2 sink to a net CO 2 source. Despite such responses to stress, ecosystems at OzFlux sites show their resilience to climate variability by rapidly pivoting back to a strong carbon sink upon the return of favourable conditions. Located in under‐represented areas, OzFlux data have the potential for reducing uncertainties in global remote sensing products, and these data provide several opportunities to develop new theories and improve our ecosystem models. The accumulated impacts of these lessons over the last 20 years highlights the value of long‐term flux observations for natural and managed systems. A future vision for OzFlux includes ongoing and newly developed synergies with ecophysiologists, ecologists, geologists, remote sensors and modellers.
Behavior of multitemporal and multisensor passive microwave indices in Southern Hemisphere ecosystems
Publisher: American Geophysical Union (AGU)
Date: 12-2014
DOI: 10.1002/2014JG002626
Detection and estimation of mixed paddy rice cropping patterns with MODIS data
Publisher: Elsevier BV
Date: 02-2011
Trans-disciplinary research in synthesis of grass pollen aerobiology and its importance for respiratory health in Australasia
Publisher: Elsevier BV
Date: 11-2015
Evapotranspiration seasonality across the Amazon Basin
Publisher: Copernicus GmbH
Date: 30-06-2017
Abstract: Abstract. Evapotranspiration (ET) of Amazon forests is a main driver of regional climate patterns and an important indicator of ecosystem functioning. Despite its importance, the seasonal variability of ET over Amazon forests, and its relationship with environmental drivers, is still poorly understood. In this study, we carry out a water balance approach to analyse seasonal patterns in ET and their relationships with water and energy drivers over five sub-basins across the Amazon Basin. We used in situ measurements of river discharge, and remotely sensed estimates of terrestrial water storage, rainfall, and solar radiation. We show that the characteristics of ET seasonality in all sub-basins differ in timing and magnitude. The highest mean annual ET was found in the northern Rio Negro basin (∼ 1497 mm year−1) and the lowest values in the Solimões River basin (∼ 986 mm year−1). For the first time in a basin-scale study, using observational data, we show that factors limiting ET vary across climatic gradients in the Amazon, confirming local-scale eddy covariance studies. Both annual mean and seasonality in ET are driven by a combination of energy and water availability, as neither rainfall nor radiation alone could explain patterns in ET. In southern basins, despite seasonal rainfall deficits, deep root water uptake allows increasing rates of ET during the dry season, when radiation is usually higher than in the wet season. We demonstrate contrasting ET seasonality with satellite greenness across Amazon forests, with strong asynchronous relationships in ever-wet watersheds, and positive correlations observed in seasonally dry watersheds. Finally, we compared our results with estimates obtained by two ET models, and we conclude that neither of the two tested models could provide a consistent representation of ET seasonal patterns across the Amazon.
Annual Seasonality Extraction Using the Cubic Spline Function and Decadal Trend in Temporal Daytime MODIS LST Data
Publisher: MDPI AG
Date: 02-12-2017
DOI: 10.3390/RS9121254
A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform
Publisher: Elsevier BV
Date: 10-2018
Optical vegetation indices for monitoring terrestrial ecosystems globally
Publisher: Springer Science and Business Media LLC
Date: 31-05-2022
MONITORING SPATIAL PATTERNS OF VEGETATION PHENOLOGY IN AN AUSTRALIAN TROPICAL TRANSECT USING MODIS EVI
Publisher: Copernicus GmbH
Date: 28-07-2012
DOI: 10.5194/ISPRSARCHIVES-XXXIX-B8-271-2012
Abstract: Abstract. Phenology is receiving increasing interest in the area of climate change and vegetation adaptation to climate. The phenology of a landscape can be used as a key parameter in land surface models and dynamic global vegetation models to more accurately simulate carbon, water and energy exchanges between land cover and atmosphere. However, the characterisation of phenology is lacking in tropical savannas which cover more than 30% of global land area, and are highly vulnerable to climate change. The objective of this study is to investigate the spatial pattern of vegetation phenology along the Northern Australia Tropical Transect (NATT) where the major biomes are wet and dry tropical savannas. For this analysis we used more than 11 years Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) product from 2000 to 2011. Eight phenological metrics were derived: Start of Season (SOS), End of Season (EOS), Length of Season (LOS), Maximum EVI (MaxG), Minimum EVI (MinG), annual litude (AMP), large integral (LIG), and small integral (SIG) were generated for each year and each pixel. Our results showed there are significant spatial patterns and considerable interannual variations of vegetation phenology along the NATT study area. Generally speaking, vegetation growing season started and ended earlier in the north, and started and ended later in the south, resulting in a southward decrease of growing season length (LOS). Vegetation productivity, which was represented by annual integral EVI (LIG), showed a significant descending trend from the northern part of NATT to the southern part. Segmented regression analysis showed that there exists a distinguishable breakpoint along the latitudinal gradient, at least in terms of annual minimum EVI (EVI), which is located between 18.84°S to 20.04°S.
Diverse sensitivity of winter crops over the growing season to climate and land surface temperature across the rainfed cropland-belt of eastern Australia
Publisher: Elsevier BV
Date: 02-2018
Actual evapotranspiration estimation by ground and remote sensing methods: the Australian experience
Publisher: Wiley
Date: 16-12-2011
DOI: 10.1002/HYP.8391
Developing Two Spectral Disease Indices for Detection of Wheat Leaf Rust (Pucciniatriticina)
Publisher: MDPI AG
Date: 26-05-2014
DOI: 10.3390/RS6064723
An Iterative BRDF/NDVI Inversion Algorithm Based on <italic>A Posteriori</italic> Variance Estimation of Observation Errors
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2016
Hyperspectral Remote Sensing of Vegetation and Agricultural Crops
Publisher: CRC Press
Date: 25-10-2011
DOI: 10.1201/B11222-41
Short-time-series grassland mapping using Sentinel-2 imagery and deep learning-based architecture
Publisher: Elsevier BV
Date: 12-2022
Large seasonal swings in leaf area of Amazon rainforests
Publisher: Proceedings of the National Academy of Sciences
Date: 20-03-2007
Abstract: Despite early speculation to the contrary, all tropical forests studied to date display seasonal variations in the presence of new leaves, flowers, and fruits. Past studies were focused on the timing of phenological events and their cues but not on the accompanying changes in leaf area that regulate vegetation–atmosphere exchanges of energy, momentum, and mass. Here we report, from analysis of 5 years of recent satellite data, seasonal swings in green leaf area of ≈25% in a majority of the Amazon rainforests. This seasonal cycle is timed to the seasonality of solar radiation in a manner that is suggestive of anticipatory and opportunistic patterns of net leaf flushing during the early to mid part of the light-rich dry season and net leaf abscission during the cloudy wet season. These seasonal swings in leaf area may be critical to initiation of the transition from dry to wet season, seasonal carbon balance between photosynthetic gains and respiratory losses, and litterfall nutrient cycling in moist tropical forests.
Climate and leaf phenology controls on tropical forest photosynthesis
Publisher: IEEE
Date: 07-2016
Ecosystem resilience despite large-scale altered hydroclimatic conditions
Publisher: Springer Science and Business Media LLC
Date: 20-01-2013
DOI: 10.1038/NATURE11836
Abstract: Climate change is predicted to increase both drought frequency and duration, and when coupled with substantial warming, will establish a new hydroclimatological model for many regions. Large-scale, warm droughts have recently occurred in North America, Africa, Europe, Amazonia and Australia, resulting in major effects on terrestrial ecosystems, carbon balance and food security. Here we compare the functional response of above-ground net primary production to contrasting hydroclimatic periods in the late twentieth century (1975-1998), and drier, warmer conditions in the early twenty-first century (2000-2009) in the Northern and Southern Hemispheres. We find a common ecosystem water-use efficiency (WUE(e): above-ground net primary production/evapotranspiration) across biomes ranging from grassland to forest that indicates an intrinsic system sensitivity to water availability across rainfall regimes, regardless of hydroclimatic conditions. We found higher WUE(e) in drier years that increased significantly with drought to a maximum WUE(e) across all biomes and a minimum native state in wetter years that was common across hydroclimatic periods. This indicates biome-scale resilience to the interannual variability associated with the early twenty-first century drought--that is, the capacity to tolerate low, annual precipitation and to respond to subsequent periods of favourable water balance. These findings provide a conceptual model of ecosystem properties at the decadal scale applicable to the widespread altered hydroclimatic conditions that are predicted for later this century. Understanding the hydroclimatic threshold that will break down ecosystem resilience and alter maximum WUE(e) may allow us to predict land-surface consequences as large regions become more arid, starting with water-limited, low-productivity grasslands.
Regional and seasonal variation in airborne grass pollen levels between cities of Australia and New Zealand
Publisher: Springer Science and Business Media LLC
Date: 29-07-2016
A Review on Assessing and Mapping Soil Erosion Hazard Using Geo-Informatics Technology for Farming System Management
Publisher: MDPI AG
Date: 11-12-2020
DOI: 10.3390/RS12244063
Abstract: Soil erosion is a severe threat to food production systems globally. Food production in farming systems decreases with increasing soil erosion hazards. This review article focuses on geo-informatics applications for identifying, assessing and predicting erosion hazards for sustainable farming system development. Several researchers have used a variety of quantitative and qualitative methods with erosion models, integrating geo-informatics techniques for spatial interpretations to address soil erosion and land degradation issues. The review identified different geo-informatics methods of erosion hazard assessment and highlighted some research gaps that can provide a basis to develop appropriate novel methodologies for future studies. It was found that rainfall variation and land-use changes significantly contribute to soil erosion hazards. There is a need for more research on the spatial and temporal pattern of water erosion with rainfall variation, innovative techniques and strategies for landscape evaluation to improve the environmental conditions in a sustainable manner. Examining water erosion and predicting erosion hazards for future climate scenarios could also be approached with emerging algorithms in geo-informatics and spatiotemporal analysis at higher spatial resolutions. Further, geo-informatics can be applied with real-time data for continuous monitoring and evaluation of erosion hazards to risk reduction and prevent the damages in farming systems.
Assessment of biophysical properties of Royal Belum tropical forest, Malaysia
Publisher: Wiley
Date: 25-10-2017
DOI: 10.1111/SJTG.12215
Vegetation Indices, Remote Sensing and Forest Monitoring
Publisher: Wiley
Date: 09-2012
Hyperspectral versus multispectral crop-productivity modeling and type discrimination for the HyspIRI mission
Publisher: Elsevier BV
Date: 12-2013
Fragmentation disrupts the seasonality of Amazonian evergreen forests
Publisher: Research Square Platform LLC
Date: 29-07-2021
DOI: 10.21203/RS.3.RS-722038/V1
Abstract: Predictions of the magnitude and timing of leaf phenology in Amazonian forests remain highly controversial, which limits our understanding of future ecosystem function with a changing environment. Here, we use biweekly terrestrial LiDAR surveys spanning wet and dry seasons in Central Amazonia to show that plant phenology of old-growth forests varies strongly across strata but that this seasonality is sensitive to disturbances arising from forest fragmentation. In combination with continuous microclimate measurements, we found that when maximum daily temperatures reached 35 °C in the latter part of the dry season, the upper canopy of large trees in undisturbed forests shed their leaves and branches. By contrast, the understory greens-up with increased light availability driven by the upper canopy loss alongside more sunlight radiation, even during periods of drier soil and atmospheric conditions. However, persistently high temperatures on forest edges exacerbated the upper canopy losses of large trees throughout the dry season, and the understory seasonality in these light-rich environments was disrupted as a result of the altered canopy structure. These findings demonstrate the plant-climate interactions controlling the seasonality of wet Amazonian forests and show that forest fragmentation will aggravate forest loss under a hotter and drier future scenario.
SAR-Based Bathymetry
Publisher: Springer New York
Date: 2014
An introduction to the Australian and New Zealand flux tower network – OzFlux
Publisher: Copernicus GmbH
Date: 31-10-2016
Abstract: Abstract. OzFlux is the regional Australian and New Zealand flux tower network that aims to provide a continental-scale national research facility to monitor and assess trends, and improve predictions, of Australia's terrestrial biosphere and climate. This paper describes the evolution, design, and current status of OzFlux as well as provides an overview of data processing. We analyse measurements from all sites within the Australian portion of the OzFlux network and two sites from New Zealand. The response of the Australian biomes to climate was largely consistent with global studies except that Australian systems had a lower ecosystem water-use efficiency. Australian semi-arid/arid ecosystems are important because of their huge extent (70 %) and they have evolved with common moisture limitations. We also found that Australian ecosystems had a similar radiation-use efficiency per unit leaf area compared to global values that indicates a convergence toward a similar biochemical efficiency. The two New Zealand sites represented extremes in productivity for a moist temperate climate zone, with the grazed dairy farm site having the highest GPP of any OzFlux site (2620 gC m−2 yr−1) and the natural raised peat bog site having a very low GPP (820 gC m−2 yr−1). The paper discusses the utility of the flux data and the synergies between flux, remote sensing, and modelling. Lastly, the paper looks ahead at the future direction of the network and concludes that there has been a substantial contribution by OzFlux, and considerable opportunities remain to further advance our understanding of ecosystem response to disturbances, including drought, fire, land-use and land-cover change, land management, and climate change, which are relevant both nationally and internationally. It is suggested that a synergistic approach is required to address all of the spatial, ecological, human, and cultural challenges of managing the delicately balanced ecosystems in Australasia.
Spaceborne Hyperspectral EO-1 Hyperion Data Pre-Processing
Publisher: CRC Press
Date: 07-12-2018
Partitioning controls on Amazon forest photosynthesis between environmental and biotic factors at hourly to interannual timescales
Publisher: Wiley
Date: 11-10-2016
DOI: 10.1111/GCB.13509
Abstract: Gross ecosystem productivity (GEP) in tropical forests varies both with the environment and with biotic changes in photosynthetic infrastructure, but our understanding of the relative effects of these factors across timescales is limited. Here, we used a statistical model to partition the variability of seven years of eddy covariance-derived GEP in a central Amazon evergreen forest into two main causes: variation in environmental drivers (solar radiation, diffuse light fraction, and vapor pressure deficit) that interact with model parameters that govern photosynthesis and biotic variation in canopy photosynthetic light-use efficiency associated with changes in the parameters themselves. Our fitted model was able to explain most of the variability in GEP at hourly (R
Supplementary material to "MODIS vegetation products as proxies of photosynthetic potential: a look across meteorological and biologic driven ecosystem productivity"
Publisher: Copernicus GmbH
Date: 04-12-2015
Large diurnal compensatory effects mitigate the response of Amazonian forests to atmospheric warming and drying
Publisher: American Association for the Advancement of Science (AAAS)
Date: 26-05-2023
Abstract: Photosynthesis and evapotranspiration in Amazonian forests are major contributors to the global carbon and water cycles. However, their diurnal patterns and responses to atmospheric warming and drying at regional scale remain unclear, hindering the understanding of global carbon and water cycles. Here, we used proxies of photosynthesis and evapotranspiration from the International Space Station to reveal a strong depression of dry season afternoon photosynthesis (by 6.7 ± 2.4%) and evapotranspiration (by 6.1 ± 3.1%). Photosynthesis positively responds to vapor pressure deficit (VPD) in the morning, but negatively in the afternoon. Furthermore, we projected that the regionally depressed afternoon photosynthesis will be compensated by their increases in the morning in future dry seasons. These results shed new light on the complex interplay of climate with carbon and water fluxes in Amazonian forests and provide evidence on the emerging environmental constraints of primary productivity that may improve the robustness of future projections.
Spatial patterns and temporal dynamics in savanna vegetation phenology across the north australian tropical transect
Publisher: Elsevier BV
Date: 12-2013
Advances in Hyperspectral Remote Sensing of Vegetation and Agricultural Crops
Publisher: CRC Press
Date: 07-12-2018
Assessment of biophysical soil properties through spectral decomposition techniques
Publisher: Elsevier BV
Date: 02-1991
Evaluation of the MODIS vegetation index compositing algorithm using SeaWiFS data
Publisher: IEEE
Date: 1998
Fifty Years of Advances in Hyperspectral Remote Sensing of Agriculture and Vegetation—Summary, Insights, and Highlights of Volume IV
Publisher: CRC Press
Date: 07-12-2018
An Optimal Sampling Design for Observing and Validating Long-Term Leaf Area Index with Temporal Variations in Spatial Heterogeneities
Publisher: MDPI AG
Date: 26-01-2015
DOI: 10.3390/RS70201300
Seasonal Comparisons of Himawari-8 AHI and MODIS Vegetation Indices over Latitudinal Australian Grassland Sites
Publisher: MDPI AG
Date: 03-08-2020
DOI: 10.3390/RS12152494
Abstract: The Advanced Himawari Imager (AHI) on board the Himawari-8 geostationary (GEO) satellite offers comparable spectral and spatial resolutions as low earth orbiting (LEO) sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) sensors, but with hypertemporal image acquisition capability. This raises the possibility of improved monitoring of highly dynamic ecosystems, such as grasslands, including fine-scale phenology retrievals from vegetation index (VI) time series. However, identifying and understanding how GEO VI temporal profiles would be different from traditional LEO VIs need to be evaluated, especially with the new generation of geostationary satellites, with unfamiliar observation geometries not experienced with MODIS, VIIRS, or Advanced Very High Resolution Radiometer (AVHRR) VI time series data. The objectives of this study were to investigate the variations in AHI reflectances and normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and two-band EVI (EVI2) in relation to diurnal phase angle variations, and to compare AHI VI seasonal datasets with MODIS VIs (standard and sun and view angle-adjusted VIs) over a functional range of dry grassland sites in eastern Australia. Strong NDVI diurnal variations and negative NDVI hotspot effects were found due to differential red and NIR band sensitivities to diurnal phase angle changes. In contrast, EVI and EVI2 were nearly insensitive to diurnal phase angle variations and displayed nearly flat diurnal profiles without noticeable hotspot influences. At seasonal time scales, AHI NDVI values were consistently lower than MODIS NDVI values, while AHI EVI and EVI2 values were significantly higher than MODIS EVI and EVI2 values, respectively. We attributed the cross-sensor differences in VI patterns to the year-round smaller phase angles and backscatter observations from AHI, in which the sunlit canopies induced a positive EVI/ EVI2 response and negative NDVI response. BRDF adjustments of MODIS VIs to solar noon and to the oblique view zenith angle of AHI resulted in strong cross-sensor convergence of VI values (R2 0.94, mean absolute difference .02). These results highlight the importance of accounting for cross-sensor observation geometries for generating compatible AHI and MODIS annual VI time series. The strong agreement found in this study shows promise in cross-sensor applications and suggests that a denser time series can be formed through combined GEO and LEO measurement synergies.
Mapping Rubber Tree Stand Age using Pléiades Satellite Imagery: A Case Study in Talang District, Phuket, Thailand
Publisher: Faculty of Engineering, Chulalongkorn University
Date: 31-07-2015
Satellite-observed shifts in C3/C4 abundance in Australian grasslands are associated with rainfall patterns
Publisher: Elsevier BV
Date: 05-2022
2-band enhanced vegetation index without a blue band and its application to AVHRR data
Publisher: SPIE
Date: 13-09-2007
DOI: 10.1117/12.734933
Mapping paddy rice with multi-date moderate-resolution imaging spectroradiometer (MODIS) data in China
Publisher: Zhejiang University Press
Date: 10-2009
A soil-adjusted vegetation index (SAVI)
Publisher: Elsevier BV
Date: 08-1988
Climate-driven land surface phenology advance is overestimated due to ignoring land cover changes
Publisher: IOP Publishing
Date: 04-2023
Abstract: Global warming has led to earlier spring green-up dates (GUDs) in recent decades with significant consequences for global carbon and hydrologic cycles. In addition to changes in climate, land cover change (LCC), including interchanges between vegetation and non-vegetation, and among plants with different functional traits, may also affect GUD. Here, we analyzed how satellite-derived GUD from 1992 to 2020 was impacted by changes in temperature, precipitation, standardized precipitation evapotranspiration index (SPEI), solar radiation, and LCC for the Northern Hemisphere ( ° N). While the climate variables had larger impact overall, variability in GUD was controlled by LCC for 6% of the Northern Hemisphere, with systematically earlier or later changes among transitions between different land cover types. These changes were found mainly along the southeastern coast of the United States, in Central-north Europe, and across northeastern China. We further showed that climate change attribution of earlier GUD during 1992–2020 was overestimated by three days when the impact of LCC was ignored. Our results deepen the understanding of how LCC impacts GUD variability and enables scientists to more accurately evaluate the impact of climate change on land surface phenology.
Evaluation of optical remote sensing to estimate actual evapotranspiration and canopy conductance
Publisher: Elsevier BV
Date: 02-2013
An introduction to the Australian and New Zealand flux tower network – OzFlux
Publisher: Copernicus GmbH
Date: 28-04-2016
DOI: 10.5194/BG-2016-152
Abstract: Abstract. OzFlux is the regional Australian and New Zealand flux tower network that aims to provide a continental-scale national research facility to monitor and assess trends, and improve predictions, of Australia’s terrestrial biosphere and climate. This paper describes the evolution, design and current status of OzFlux as well as an overview of data processing. We analyse measurements from the Australian portion of the OzFlux network and found that the response of Australian biomes to climate was largely consistent with global studies but that Australian systems had a lower ecosystem water-use efficiency. Australian semi-arid/arid ecosystems are important because of their huge extent (70 %) and they have evolved with common moisture limitations. We also found that Australian ecosystems had similar radiation use efficiency per unit leaf area compared to global values that indicates a convergence toward a similar biochemical efficiency. The paper discusses the utility of the flux data and the synergies between flux, remote sensing and modelling. Lastly, the paper looks ahead at the future direction of the network and concludes that there has been a substantial contribution by OzFlux and considerable opportunities remain to further advance our understanding of ecosystem response to disturbances including drought, fire, land use and land cover change, land management and climate change that are relevant both nationally and internationally. It is suggested that a synergistic approach is required to address all of the spatial, ecological, human and cultural challenges of managing the delicately balanced ecosystems in Australia.
Assessing the seasonal dynamics of the Brazilian Cerrado vegetation through the use of spectral vegetation indices
Publisher: Informa UK Limited
Date: 05-2004
Developing an Index for Detection and Identification of Disease Stages
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2016
REMOTE SENSING FOR ENVIRONMENTAL MONITORING
Publisher: Elsevier
Date: 2004
Remote Sensing Image Classification
Publisher: CRC Press
Date: 16-02-2011
DOI: 10.1201/B10599-16
Scaling effects on spring phenology detections from MODIS data at multiple spatial resolutions over the contiguous United States
Publisher: Elsevier BV
Date: 10-2017
Buffelgrass (Pennisetum ciliare) land conversion and productivity in the plains of Sonora, Mexico
Publisher: Elsevier BV
Date: 2006
Fifty Years of Advances in Hyperspectral Remote Sensing of Agriculture and Vegetation—Summary, Insights, and Highlights of Volume II
Publisher: CRC Press
Date: 07-12-2018
An Interdisciplinary Field Study of the Energy and Water Fluxes in the Atmospheric-Biosphere System over Semiarid Rangelands: Description and Some Preliminary Results
Publisher: American Meteorological Society
Date: 11-1991
An empirical investigation of cross-sensor relationships of NDVI and red/near-infrared reflectance using EO-1 Hyperion data
Publisher: Elsevier BV
Date: 30-01-2006
MODIS EVIbased Variability in Amazon Phenology across the Rainforest-Cerrado Ecotone
Publisher: IEEE
Date: 07-2006
Global trends in vegetation seasonality in the GIMMS NDVI3g and their robustness
Publisher: Elsevier BV
Date: 02-2021
Assessments of multisensor vegetation index dependencies with hyperspectral and tower flux data
Publisher: SPIE
Date: 31-08-2006
DOI: 10.1117/12.681382
Land surface phenological response to decadal climate variability across Australia using satellite remote sensing
Publisher: Copernicus GmbH
Date: 29-09-2014
Abstract: Abstract. Land surface phenological cycles of vegetation greening and browning are influenced by variability in climatic forcing. Quantitative spatial information on phenological cycles and their variability is important for agricultural applications, wildfire fuel accumulation, land management, land surface modeling, and climate change studies. Most phenology studies have focused on temperature-driven Northern Hemisphere systems, where phenology shows annually recurring patterns. However, precipitation-driven non-annual phenology of arid and semi-arid systems (i.e., drylands) received much less attention, despite the fact that they cover more than 30% of the global land surface. Here, we focused on Australia, a continent with one of the most variable rainfall climates in the world and vast areas of dryland systems, where a detailed phenological investigation and a characterization of the relationship between phenology and climate variability are missing. To fill this knowledge gap, we developed an algorithm to characterize phenological cycles, and analyzed geographic and climate-driven variability in phenology from 2000 to 2013, which included extreme drought and wet years. We linked derived phenological metrics to rainfall and the Southern Oscillation Index (SOI). We conducted a continent-wide investigation and a more detailed investigation over the Murray–Darling Basin (MDB), the primary agricultural area and largest river catchment of Australia. Results showed high inter- and intra-annual variability in phenological cycles across Australia. The peak of phenological cycles occurred not only during the austral summer, but also at any time of the year, and their timing varied by more than a month in the interior of the continent. The magnitude of the phenological cycle peak and the integrated greenness were most significantly correlated with monthly SOI within the preceding 12 months. Correlation patterns occurred primarily over northeastern Australia and within the MDB, predominantly over natural land cover and particularly in floodplain and wetland areas. Integrated greenness of the phenological cycles (surrogate of vegetation productivity) showed positive anomalies of more than 2 standard deviations over most of eastern Australia in 2009–2010, which coincided with the transition from the El Niño-induced decadal droughts to flooding caused by La Niña.
MODIS Vegetation Indices
Publisher: Springer New York
Date: 2010
Can UAV-Based Infrared Thermography Be Used to Study Plant-Parasite Interactions between Mistletoe and Eucalypt Trees?
Publisher: MDPI AG
Date: 19-12-2018
DOI: 10.3390/RS10122062
Abstract: Some of the remnants of the Cumberland Plain woodland, an endangered dry sclerophyllous forest type of New South Wales, Australia, host large populations of mistletoe. In this study, the extent of mistletoe infection was investigated based on a forest inventory. We found that the mistletoe infection rate was relatively high, with 69% of the Eucalyptus fibrosa and 75% of the E. moluccana trees being infected. Next, to study the potential consequences of the infection for the trees, canopy temperatures of mistletoe plants and of infected and uninfected trees were analyzed using thermal imagery acquired during 10 flights with an unmanned aerial vehicle (UAV) in two consecutive summer seasons. Throughout all flight c aigns, mistletoe canopy temperature was 0.3–2 K lower than the temperature of the eucalypt canopy it was growing in, suggesting higher transpiration rates. Differences in canopy temperature between infected eucalypt foliage and mistletoe were particularly large when incoming radiation peaked. In these conditions, eucalypt foliage from infected trees also had significantly higher canopy temperatures (and likely lower transpiration rates) compared to that of uninfected trees of the same species. The study demonstrates the potential of using UAV-based infrared thermography for studying plant-water relations of mistletoe and its hosts.
Ku-band SAR data for bare soil moisture retrieval over agricultural fields
Publisher: IEEE
Date: 1997
Mangrove Phenology and Environmental Drivers Derived from Remote Sensing in Southern Thailand
Publisher: MDPI AG
Date: 22-04-2019
DOI: 10.3390/RS11080955
Abstract: Vegetation phenology is the annual cycle timing of vegetation growth. Mangrove phenology is a vital component to assess mangrove viability and includes start of season (SOS), end of season (EOS), peak of season (POS), and length of season (LOS). Potential environmental drivers include air temperature (Ta), surface temperature (Ts), sea surface temperature (SST), rainfall, sea surface salinity (SSS), and radiation flux (Ra). The Enhanced vegetation index (EVI) was calculated from Moderate Resolution Imaging Spectroradiometer (MODIS, MOD13Q1) data over five study sites between 2003 and 2012. Four of the mangrove study sites were located on the Malay Peninsula on the Andaman Sea and one site located on the Gulf of Thailand. The goals of this study were to characterize phenology patterns across equatorial Thailand Indo-Malay mangrove forests, identify climatic and aquatic drivers of mangrove seasonality, and compare mangrove phenologies with surrounding upland tropical forests. Our results show the seasonality of mangrove growth was distinctly different from the surrounding land-based tropical forests. The mangrove growth season was approximately 8–9 months duration, starting in April to June, peaking in August to October and ending in January to February of the following year. The 10-year trend analysis revealed significant delaying trends in SOS, POS, and EOS for the Andaman Sea sites but only for EOS at the Gulf of Thailand site. The cumulative rainfall is likely to be the main factor driving later mangrove phenologies.
Simulation of solar-induced chlorophyll fluorescence in a heterogeneous forest using 3-D radiative transfer modelling and airborne LiDAR
Publisher: Elsevier BV
Date: 09-2022
An application of airborne hyperspectral and EO-1 Hyperion data for inter-sensor calibration of vegetation indices for regional-scale monitoring
Publisher: IEEE
Date: 2002
A technique of inter-sensor VI translations using EO-1 Hyperion data to minimize systematic differences in spectral band-pass filters
Publisher: IEEE
Date: 2002
Landsat and GRACE observations of arid wetland dynamics in a dryland river system under multi-decadal hydroclimatic extremes
Publisher: Elsevier BV
Date: 12-2016
Intercomparison and evaluation of spring phenology products using National Phenology Network and AmeriFlux observations in the contiguous United States
Publisher: Elsevier BV
Date: 08-2017
A 20-year study of NDVI variability over the Northeast Region of Brazil
Publisher: Elsevier BV
Date: 10-2006
Implementation Of The Auspollen Partnership Project And Pre‐Evaluation Survey Of User Perception Of The Value Of Local Pollen Information
Publisher: Wiley
Date: 09-2017
DOI: 10.1111/IMJ.56_13578
Evaluating the Effect of Different Wheat Rust Disease Symptoms on Vegetation Indices Using Hyperspectral Measurements
Publisher: MDPI AG
Date: 05-06-2014
DOI: 10.3390/RS6065107
Surface Energy Dynamics and Canopy Structural Properties in Intact and Disturbed Forests in the Southern Amazon
Publisher: American Geophysical Union (AGU)
Date: 31-08-2023
DOI: 10.1029/2023JG007465
Abstract: The Brazilian Amazon has been a focus of land development with large swaths of forests converted to agriculture. Forest degradation by selective logging and fires has accompanied the agricultural frontier and has resulted in significant impacts on Amazonian ecosystems. Changes in forest structure resulting from forest disturbances have large impacts on the surface energy balance, including on land surface temperature (LST) and evapotranspiration (ET). This study's objective is to assess the effects of forest disturbances on water fluxes and forest structure in a transitional forest site in the Southern Amazon. We used ET and LST products from MODIS and Landsat 8 and GEDI‐derived forest structure data to address our research questions. We found that disturbances induced seasonal water stress, more pronounced in croplands astures than in forests (differences up to 20% in the dry season), and more pronounced in second‐growth and recently burned areas than in logged and intact forests (differences up to 12% in the dry season). Moreover, ET and LST were negatively related, with more consistent relationships across disturbance classes in the dry season ( R 2 : 0.41–0.87) than in the wet season ( R 2 : 0.18–0.49). Forest and cropland or pasture classes showed contrasting relationships in the dry season. Finally, we found that forest structure exhibited stronger relationships with ET and LST in the most disturbed forests ( R 2 : 0.01–0.43) than in the least disturbed forests ( R 2 0.05). Our findings help to elucidate degraded forests functioning under a changing climate and to improve estimates of water and energy fluxes in Amazonian degraded forests.
Spatiotemporal Variations of Dryland Vegetation Phenology Revealed by Satellite-Observed Fluorescence and Greenness across the North Australian Tropical Transect
Publisher: MDPI AG
Date: 22-06-2022
DOI: 10.3390/RS14132985
Abstract: Accurate characterization of spatial patterns and temporal variations in dryland vegetation is of great importance for improving our understanding of terrestrial ecosystem functioning under changing climates. Here, we explored the spatiotemporal variability of dryland vegetation phenology using satellite-observed Solar-Induced chlorophyll Fluorescence (SIF) and the Enhanced Vegetation Index (EVI) along the North Australian Tropical Transect (NATT). Substantial impacts of extreme drought and intense wetness on the phenology and productivity of dryland vegetation are observed by both SIF and EVI, especially in the arid/semiarid interior of Australia without detectable seasonality in the dry year of 2018–2019. The greenness-based vegetation index (EVI) can more accurately capture the seasonal and interannual variation in vegetation production than SIF (EVI r2: 0.47~0.86, SIF r2: 0.47~0.78). However, during the brown-down periods, the rate of decline in EVI is evidently slower than that in SIF and in situ measurement of gross primary productivity (GPP), due partially to the advanced seasonality of absorbed photosynthetically active radiation. Over 70% of the variability of EVI (except for Hummock grasslands) and 40% of the variability of SIF (except for shrublands) can be explained by the water-related drivers (rainfall and soil moisture). By contrast, air temperature contributed to 25~40% of the variability of the effective fluorescence yield (SIFyield) across all biomes. In spite of high retrieval noises and variable accuracy in phenological metrics (MAE: 8~60 days), spaceborne SIF observations, offsetting the drawbacks of greenness-based phenology products with a potentially lagged end of the season, have the promising capability of mapping and characterizing the spatiotemporal dynamics of dryland vegetation phenology.
Enhanced canopy growth precedes senescence in 2005 and 2010 Amazonian droughts
Publisher: Elsevier BV
Date: 06-2018
MONITORING PHENOLOGICAL VARIABILITY ACROSS A TROPICAL SAVANNA ARIDITY GRADIENT WITH REMOTE SENSING ACROSS SEASONAL TO ANNUALAND EXTREME EVENTS
Publisher: Copernicus GmbH
Date: 31-08-2012
DOI: 10.5194/ISPRSARCHIVES-XXXVIII-8-W20-19-2011
Abstract: Abstract. Tropical savannas are key components of the global carbon and water cycles and understanding their functioning is critical to understanding ecosystem feedbacks to global climate. By observing broad scale vegetation responses to climatic variability, remote sensing offers powerful insights into the patterns and processes underlying savanna behaviour. However, savannas are highly complex, multi-layer and heterogenous ecosystems composed of C3 (herbaceous) and C4 (woodland) components with asynchronous phenological responses to environmental controls. There are concerns about optimizing the detection of savanna functioning as well as in understanding their environmental controls with remote-sensing data due to their coarse resolution. Furthermore, seasonalphenologic variations in satellite observations need to be sufficiently accurate to ensure confidence in interpreting vegetation responses to interannual climatic variation and to aid in constraining models of carbon and water fluxes. In this study, we analysed several years of high temporal frequency MODIS and TRMM satellite data sets of vegetation dynamics and rainfall, respectively, to seasonal and interannual responses of savanna multifunctional components to climate variability across a tropical savanna aridity gradient (1760 to 580 mm annual rainfall) in northern Australia. We compared our results with a series of eddy covariance (EC) tower flux data of gross primary production and analyzed a wide set of ecosystem processes including photosynthesis, net primary productivity, phenological metrics in timing of the growing season, and rain use efficiencies. We found MODIS satellite measurements to yield highly accurate spatial and temporal variability in ecosystem functioning and able to replicate interannual patterns and responses to rainfall observed with the EC tower data. Although these results appear promising for regional extensions of satelliteflux tower relationships at the landscape level, we also observed various issues with footprint matching and hysteresis effects that potentially may limit the utility of remote sensing in scaling fluxes of carbon and water to the regional scales.
Extraction Of Soil And Vegetation Parameters From High Resolution Bi-directional Reflectance Spectra
Publisher: IEEE
Date: 1992
Estimation of vegetation photosynthetic capacity from space‐based measurements of chlorophyll fluorescence for terrestrial biosphere models
Publisher: Wiley
Date: 08-2014
DOI: 10.1111/GCB.12664
Abstract: Photosynthesis simulations by terrestrial biosphere models are usually based on the Farquhar's model, in which the maximum rate of carboxylation (Vcmax ) is a key control parameter of photosynthetic capacity. Even though Vcmax is known to vary substantially in space and time in response to environmental controls, it is typically parameterized in models with tabulated values associated to plant functional types. Remote sensing can be used to produce a spatially continuous and temporally resolved view on photosynthetic efficiency, but traditional vegetation observations based on spectral reflectance lack a direct link to plant photochemical processes. Alternatively, recent space-borne measurements of sun-induced chlorophyll fluorescence (SIF) can offer an observational constraint on photosynthesis simulations. Here, we show that top-of-canopy SIF measurements from space are sensitive to Vcmax at the ecosystem level, and present an approach to invert Vcmax from SIF data. We use the Soil-Canopy Observation of Photosynthesis and Energy (SCOPE) balance model to derive empirical relationships between seasonal Vcmax and SIF which are used to solve the inverse problem. We evaluate our Vcmax estimation method at six agricultural flux tower sites in the midwestern US using spaced-based SIF retrievals. Our Vcmax estimates agree well with literature values for corn and soybean plants (average values of 37 and 101 μmol m(-2) s(-1) , respectively) and show plausible seasonal patterns. The effect of the updated seasonally varying Vcmax parameterization on simulated gross primary productivity (GPP) is tested by comparing to simulations with fixed Vcmax values. Validation against flux tower observations demonstrate that simulations of GPP and light use efficiency improve significantly when our time-resolved Vcmax estimates from SIF are used, with R(2) for GPP comparisons increasing from 0.85 to 0.93, and for light use efficiency from 0.44 to 0.83. Our results support the use of space-based SIF data as a proxy for photosynthetic capacity and suggest the potential for global, time-resolved estimates of Vcmax .
Performance of Three Reflectance Calibration Methods for Airborne Hyperspectral Spectrometer Data
Publisher: MDPI AG
Date: 03-02-2009
DOI: 10.3390/S90200794
Use of MODIS Satellite Images and an Atmospheric Dust Transport Model To Evaluate Juniperus Spp. Pollen Phenology and Dispersal to Support Public Health Alerts
Publisher: Elsevier BV
Date: 02-2011
Proposing an ecologically viable and economically sound farming system using a matrix-based geo-informatics approach.
Publisher: Elsevier BV
Date: 11-2021
Response of Dryland Vegetation Under Extreme Wet Events with Satellite Measures of Greenness and Fluorescence
Publisher: Elsevier BV
Date: 2022
DOI: 10.2139/SSRN.4062582
Interpreting vegetation indices
Publisher: Elsevier BV
Date: 12-1991
Creating New Near-Surface Air Temperature Datasets to Understand Elevation-Dependent Warming in the Tibetan Plateau
Publisher: MDPI AG
Date: 27-05-2020
DOI: 10.3390/RS12111722
Abstract: The Tibetan Plateau has been undergoing accelerated warming over recent decades, and is considered an indicator for broader global warming phenomena. However, our understanding of warming rates with elevation in complex mountain regions is incomplete. The most serious concern is the lack of high-quality near-surface air temperature (Tair) datasets in these areas. To address this knowledge gap, we developed an automated mapping framework for the estimation of seamless daily minimum and maximum Land Surface Temperatures (LSTs) for the Tibetan Plateau from the existing MODIS LST products for a long period of time (i.e., 2002–present). Specific machine learning methods were developed and linked with target-oriented validation and then applied to convert LST to Tair. Spatial variables in retrieving Tair, such as solar radiation and vegetation indices, were used in estimation of Tair, whereas MODIS LST products were mainly focused on temporal variation in surface air temperature. We validated our process using independent Tair products, revealing more reliable estimates on Tair the R2 and RMSE at monthly scales generally fell in the range of 0.9–0.95 and 1–2 °C. Using these continuous and consistent Tair datasets, we found temperature increases in the elevation range between 2000–3000 m and 4000–5000 m, whereas the elevation interval at 6000–7000 m exhibits a cooling trend. The developed datasets, findings and methodology contribute to global studies on accelerated warming.
Soil Cation Leaching by “Acid Rain” with Varying Nitrate‐to‐Sulfate Ratios
Publisher: Wiley
Date: 07-1984
A review of vegetation indices
Publisher: Informa UK Limited
Date: 08-1995
Drought resilience of Australian rangelands under intense hydroclimatic variability
Publisher: IEEE
Date: 07-2016
Dynamic ecological observations from satellites inform aerobiology of allergenic grass pollen
Publisher: Elsevier BV
Date: 08-2018
Assessment of vegetation and soil water regimes in partial canopies with optical remotely sensed data
Publisher: Elsevier BV
Date: 05-1990
Appointment of new editorial board members
Publisher: Elsevier BV
Date: 04-2005
Estimation of Rubber Yield Using Sentinel-2 Satellite Data
Publisher: MDPI AG
Date: 26-04-2023
DOI: 10.3390/SU15097223
Abstract: Rubber is a perennial plant grown to produce natural rubber. It is a raw material for industrial and non-industrial products important to the world economy. The sustainability of natural rubber production is, therefore, critical for smallholder livelihoods and economic development. To maintain price stability, it is important to estimate the yields in advance. Remote sensing technology can effectively provide large-scale spatial data however, productivity estimates need to be processed from high spatial resolution data generated from satellites with high accuracy and reliability, especially for smallholder livelihood areas where smaller plots contrast with large farms. This study used reflectance data from Sentinel-2 satellite imagery acquired for the 12 months between December 2020 and November 2021. The imagery included 213 plots where data on rubber production in smallholder agriculture were collected. Six vegetation indices (Vis), namely Green Soil Adjusted Vegetation Index (GSAVI), Modified Simple Ratio (MSR), Normalized Burn Ratio (NBR), Normalized Difference Vegetation Index (NDVI), Normalized Green (NR), and Ratio Vegetation Index (RVI) were used to estimate the rubber yield. The study found that the red edge spectral band (band 5) provided the best prediction with R2 = 0.79 and RMSE = 29.63 kg/ha, outperforming all other spectral bands and VIs. The MSR index provided the highest coefficient of determination, with R2 = 0.62 and RMSE = 39.25 kg/ha. When the red edge reflectance was combined with the best VI, MSR, the prediction model only slightly improved, with a coefficient determination of (R2) of 0.80 and an RMSE of 29.42 kg/ha. The results demonstrated that the Sentinel-2 data are suitable for rubber yield prediction for smallholder farmers. The findings of this study can be used as a guideline to apply in other countries or areas. Future studies will require the use of reflectance and vegetation indices derived from satellite data in combination with meteorological data, as well as the application of complex models, such as machine learning and deep learning.
Forest fragmentation impacts the seasonality of Amazonian evergreen canopies
Publisher: Springer Science and Business Media LLC
Date: 17-02-2022
DOI: 10.1038/S41467-022-28490-7
Abstract: Predictions of the magnitude and timing of leaf phenology in Amazonian forests remain highly controversial. Here, we use terrestrial LiDAR surveys every two weeks spanning wet and dry seasons in Central Amazonia to show that plant phenology varies strongly across vertical strata in old-growth forests, but is sensitive to disturbances arising from forest fragmentation. In combination with continuous microclimate measurements, we find that when maximum daily temperatures reached 35 °C in the latter part of the dry season, the upper canopy of large trees in undisturbed forests lost plant material. In contrast, the understory greened up with increased light availability driven by the upper canopy loss, alongside increases in solar radiation, even during periods of drier soil and atmospheric conditions. However, persistently high temperatures in forest edges exacerbated the upper canopy losses of large trees throughout the dry season, whereas the understory in these light-rich environments was less dependent on the altered upper canopy structure. Our findings reveal a strong influence of edge effects on phenological controls in wet forests of Central Amazonia.
Multisensor comparisons and validation of modis vegetation indices at the semiarid jornada experimental range
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2003
Evapotranspiration seasonality across the Amazon basin
Publisher: Copernicus GmbH
Date: 04-01-2017
DOI: 10.5194/ESD-2016-75
Abstract: Abstract. Evapotranspiration (ET) of Amazon forests is a main driver of regional climate patterns and an important indicator of ecosystem functioning. Despite its importance, the seasonal variability of ET over Amazon forests, and its relationship with environmental drivers, is still poorly understood. In this study, we carry out a water balance approach to analyse seasonal patterns in ET and their relationships with water and energy drivers over five sub-basins across the Amazon basin. We used in-situ measurements of river discharge, and remotely sensed estimates of terrestrial water storage, rainfall, and solar radiation. We show that the characteristics of ET seasonality in all sub-basins differ in timing and magnitude. The highest mean annual ET was found in the northern Rio Negro basin (~ 1497 mm year−1) and the lowest values in the Solimões River basin (~ 986 mm year−1). For the first time in a basin-scale study, using observational data, we show that factors limiting ET vary across climatic gradients in the Amazon, confirming local-scale eddy covariance studies. Both annual mean and seasonality in ET are driven by a combination of energy and water availability, as neither rainfall nor radiation alone could explain patterns in ET. In southern basins, despite seasonal rainfall deficits, deep root water uptake allows increasing rates of ET during the dry season, when radiation is usually higher than in the wet season. We demonstrate contrasting ET seasonality with satellite greenness across Amazon forests, with strong asynchronous relationships in ever-wet watersheds, and positive correlations observed in seasonally dry watersheds. Finally, we compared our results with estimates obtained by two ET models, and we conclude that neither of the two tested models could provide a consistent representation of ET seasonal patterns across the Amazon.
Heat wave tracker: A multi-method, multi-source heat wave measurement toolkit based on Google Earth Engine
Publisher: Elsevier BV
Date: 2022
Fraction images for monitoring intra-annual phenology of different vegetation physiognomies in Amazonia
Publisher: Informa UK Limited
Date: 02-02-2011
A multi-scale analysis of dynamic optical signals in a Southern California chaparral ecosystem: A comparison of field, AVIRIS and MODIS data
Publisher: Elsevier BV
Date: 15-08-2006
Suitability of spectral indices for evaluating vegetation characteristics on arid rangelands
Publisher: Elsevier BV
Date: 11-1987
Analysis of ERS-1 SAR data to study soil moisture content in rocky soils
Publisher: IEEE
Date: 1996
Amazon Forests Green-Up During 2005 Drought
Publisher: American Association for the Advancement of Science (AAAS)
Date: 26-10-2007
Abstract: Coupled climate-carbon cycle models suggest that Amazon forests are vulnerable to both long- and short-term droughts, but satellite observations showed a large-scale photosynthetic green-up in intact evergreen forests of the Amazon in response to a short, intense drought in 2005. These findings suggest that Amazon forests, although threatened by human-caused deforestation and fire and possibly by more severe long-term droughts, may be more resilient to climate changes than ecosystem models assume.
Land surface phenological response to decadal climate variability across Australia using satellite remote sensing
Publisher: Copernicus GmbH
Date: 28-05-2014
Abstract: Abstract. Land surface phenological cycles of vegetation greening and browning are influenced by variability in climatic forcing. Quantitative information on phenological cycles and their variability is important for agricultural applications, wildfire fuel accumulation, land management, land surface modeling, and climate change studies. Most phenology studies have focused on temperature-driven Northern Hemisphere systems, where phenology shows annually reoccurring patterns. Yet, precipitation-driven non-annual phenology of arid and semi-arid systems (i.e. drylands) received much less attention, despite the fact that they cover more than 30% of the global land surface. Here we focused on Australia, the driest inhabited continent with one of the most variable rainfall climates in the world and vast areas of dryland systems. Detailed and internally consistent studies investigating phenological cycles and their response to climate variability across the entire continent designed specifically for Australian dryland conditions are missing. To fill this knowledge gap and to advance phenological research, we used existing methods more effectively to study geographic and climate-driven variability in phenology over Australia. We linked derived phenological metrics with rainfall and the Southern Oscillation Index (SOI). We based our analysis on Enhanced Vegetation Index (EVI) data from the MODerate Resolution Imaging Spectroradiometer (MODIS) from 2000 to 2013, which included extreme drought and wet years. We conducted a continent-wide investigation of the link between phenology and climate variability and a more detailed investigation over the Murray–Darling Basin (MDB), the primary agricultural area and largest river catchment of Australia. Results showed high inter- and intra-annual variability in phenological cycles. Phenological cycle peaks occurred not only during the austral summer but at any time of the year, and their timing varied by more than a month in the interior of the continent. The phenological cycle peak magnitude and integrated greenness were most significantly correlated with monthly SOI within the preceding 12 months. Correlation patterns occurred primarily over north-eastern Australia and within the MDB predominantly over natural land cover and particularly in floodplain and wetland areas. Integrated greenness of the phenological cycles (surrogate of productivity) showed positive anomalies of more than two standard deviations over most of eastern Australia in 2009–2010, which coincided with the transition between the El Niño induced decadal droughts to flooding caused by La Niña. The quantified spatial-temporal variability in phenology across Australia in response to climate variability presented here provides important information for land management and climate change studies and applications.
Landscape context determinants to plant diversity in the permanent meadows of Southern European Alps
Publisher: Springer Science and Business Media LLC
Date: 14-03-2013
Spatio-temporal mapping and monitoring of Urban Heat Island patterns over Sydney, Australia using MODIS and Landsat-8
Publisher: IEEE
Date: 07-2016
Optimizing the Processing of UAV-Based Thermal Imagery
Publisher: MDPI AG
Date: 12-05-2017
DOI: 10.3390/RS9050476
Seasonal dynamics of native and converted cerrado physiognomies with MODIS data
Publisher: IEEE
Date: 2004
MODIS vegetation products as proxies of photosynthetic potential along a gradient of meteorologically and biologically driven ecosystem productivity
Publisher: Copernicus GmbH
Date: 07-10-2016
Abstract: Abstract. A direct relationship between gross ecosystem productivity (GEP) estimated by the eddy covariance (EC) method and Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices (VIs) has been observed in many temperate and tropical ecosystems. However, in Australian evergreen forests, and particularly sclerophyll and temperate woodlands, MODIS VIs do not capture seasonality of GEP. In this study, we re-evaluate the connection between satellite and flux tower data at four contrasting Australian ecosystems, through comparisons of GEP and four measures of photosynthetic potential, derived via parameterization of the light response curve: ecosystem light use efficiency (LUE), photosynthetic capacity (Pc), GEP at saturation (GEPsat), and quantum yield (α), with MODIS vegetation satellite products, including VIs, gross primary productivity (GPPMOD), leaf area index (LAIMOD), and fraction of photosynthetic active radiation (fPARMOD). We found that satellite-derived biophysical products constitute a measurement of ecosystem structure (e.g. leaf area index – quantity of leaves) and function (e.g. leaf level photosynthetic assimilation capacity – quality of leaves), rather than GEP. Our results show that in primarily meteorological-driven (e.g. photosynthetic active radiation, air temperature, and/or precipitation) and relatively aseasonal ecosystems (e.g. evergreen wet sclerophyll forests), there were no statistically significant relationships between GEP and satellite-derived measures of greenness. In contrast, for phenology-driven ecosystems (e.g. tropical savannas), changes in the vegetation status drove GEP, and tower-based measurements of photosynthetic activity were best represented by VIs. We observed the highest correlations between MODIS products and GEP in locations where key meteorological variables and vegetation phenology were synchronous (e.g. semi-arid Acacia woodlands) and low correlation at locations where they were asynchronous (e.g. Mediterranean ecosystems). However, we found a statistical significant relationship between the seasonal measures of photosynthetic potential (Pc and LUE) and VIs, where each ecosystem aligns along a continuum we emphasize here that knowledge of the conditions in which flux tower measurements and VIs or other remote sensing products converge greatly advances our understanding of the mechanisms driving the carbon cycle (phenology and climate drivers) and provides an ecological basis for interpretation of satellite-derived measures of greenness.
Fifty-Years of Advances in Hyperspectral Remote Sensing of Agriculture and Vegetation—Summary, Insights, and Highlights of Volume I
Publisher: CRC Press
Date: 07-12-2018
The macroecology of airborne pollen in Australian and New Zealand urban areas
Publisher: Public Library of Science (PLoS)
Date: 29-05-2014
Spatial modeling of soil erosion hazards and crop diversity change with rainfall variation in the Central Highlands of Sri Lanka.
Publisher: Elsevier BV
Date: 02-2022
DOI: 10.1016/J.SCITOTENV.2021.150405
Abstract: The spatial variation of soil erosion is essential for farming system management and resilience development, specifically in the high climate hazard vulnerable tropical countries like Sri Lanka. This study aimed to investigate climate and human-induced soil erosion through spatial modeling. Remote sensing was used for spatial modeling to detect soil erosion, crop ersity, and rainfall variation. The study employed a time-series analysis of several variables such as rainfall, land-use land-cover (LULC) and crop ersity to detect the spatial variability of soil erosion in farming systems. Rain-use efficiency (RUE) and residual trend analysis (RESTREND) combined with a regression approach were applied to partition the soil erosion due to human and climate-induced land degradation. Results showed that soil erosion has increased from 9.08 Mg/ha/yr to 11.08 Mg/ha/yr from 2000 to 2019 in the Central Highlands of Sri Lanka. The average annual rainfall has increased in the western part of the Central Highlands, and soil erosion hazards such as landslides incidence also increased during this period. However, crop ersity has been decreasing in farming systems, namely wet zone low country (WL1a) and wet zone mid-country (WM1a), in the western part of the Central Highlands. The RUE and RESTREND analyses reveal climate-induced soil erosion is responsible for land degradation in these farming systems and is a threat to sustainable food production in the farming systems of the Central Highlands.
Empirical acquisition of bidirectional reflectance of tropical forest ecosystems using unmanned aerial vehicles
Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-8300
Abstract: & & Both the sensor viewing angle and the solar angle influence the remote sensing signal of terrestrial ecosystems. This influence is characterized by the bidirectional reflectance distribution function (BRDF). Knowledge of this BRDF is needed to correctly interpret the signal, but can also provide information on vegetation characteristics and structure. Obtaining the BRDF is far from straightforward: at leaf scale, laboratory goniometers can measure reflected radiation over a range of sensor-solar angle for very homogeneous ecosystems, such as grassland or agricultural cropland, unmanned aerial vehicles (UAVs) can be programmed as giant goniometer, scanning the BRDF of an area of up to a few m& #178 . For heterogeneous ecosystems such as forests, this is not feasible. In this case, BRDF could so far only be derived from theoretical radiation transfer models or semi-empirical models yet these models do not always agree.& & & & We here propose a new method for measuring BRDF of forest ecosystems with UAVs, by measuring a star-shaped area of the ecosystem, covering in total about 3600m& #178 and capturing 6 different sensor-solar azimuth angle and three different zenith angles. This approach was applied over two sites of tropical rainforests in Queensland, Australia, with measurements with a RGB camera and a spectrometer. By repeating the flights several times during the day, we were able to test the Helmholtz reciprocity principle & #8211 that states the BRDF function of ecosystems remains the same, regardless of the solar angle & #8211 and are able to increase the range of sensor-solar angles. Our results present the first strictly empirical BRDF of tropical rainforests and confirm the importance of accurate BRDF correction of remote sensing products from forest ecosystems.& & &
Change Detection Using Vegetation Indices and Multiplatform Satellite Imagery at Multiple Temporal and Spatial Scales
Publisher: Wiley
Date: 07-02-2014
Extreme precipitation patterns and reductions of terrestrial ecosystem production across biomes
Publisher: American Geophysical Union (AGU)
Date: 13-02-2013
DOI: 10.1029/2012JG002136
Analysis of Cerrado Physiognomies and Conversion in the MODIS Seasonal–Temporal Domain
Publisher: American Meteorological Society
Date: 07-2201
Effects of Light Component and Water Stress on Photosynthesis of Amazon Rainforests During the 2015/2016 El Niño Drought
Publisher: American Geophysical Union (AGU)
Date: 06-2019
DOI: 10.1029/2018JG004988
Spatiotemporal trends of forest cover change in Southeast Asia
Publisher: Springer Berlin Heidelberg
Date: 2010
The Influences of Drought and Land-Cover Conversion on Inter-Annual Variation of NPP in the Three-North Shelterbelt Program Zone of China Based on MODIS Data
Publisher: Public Library of Science (PLoS)
Date: 27-06-2016
Fraction images derived from EO-1 Hyperion multitemporal data for dry season green up analysis in Tapajós National Forest, Brazilian Amazonia
Publisher: IEEE
Date: 2009
Decoupling of rainfall and vegetation greening in the arid Asian endorheic basins due to the irrigation intensification
Publisher: Authorea, Inc.
Date: 13-05-2023
DOI: 10.22541/ESSOAR.168394773.36976815/V1
Abstract: A large portion of Central-Western Asia is made up of contiguous closed basins, collectively termed as the Asian Endorheic Basins (AEB). As these retention basins are only being replenished by the intermittent precipitation, increasing droughts in the region and a growing demand for water have been presumed to jointly contributed to the land degradation. To understand the impact of climate change and human activities on dryland vegetation over the AEB, we conducted trend and partial correlation analysis of vegetation and hydroclimatic change from 2001 to 2021 using multi-satellite observations, including vegetation greenness, total water storage anomalies (TWSA) and meteorological data. Here we show that much of the AEB (65.53%) exhibited a greening trend over the past two decades. Partial correlation analyses indicated that climatic factors had varying effects on vegetation productivity as a function of vegetation types and aridity. In arid AEB, precipitation dominated the vegetation productivity trend. Such a rainfall dominance gave way to TWSA dominance in the hyper-arid AEB. We further showed that the decoupling of rainfall and hyper-arid vegetation greening was largely due to a significant expansion (17.3%) in irrigated cropland across the hyper-arid AEB. Given the extremely harsh environment in the hyper-arid AEB, our results therefore raised the concerns on the ecological and societal sustainability in this region, where a mild increase in precipitation might not be able to catch up the rising evaporative demand and water consumption resulted from global warming and irrigation intensification.
Evaluation of sensor calibration uncertainties on vegetation indices for MODIS
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2000
DOI: 10.1109/36.843034
Use of MODIS enhanced vegetation index to detect seasonal patterns of leaf phenology in central Amazon várzea forest
Publisher: IEEE
Date: 2009
Interaction of seasonal sun-angle and savanna phenology observed and modelled using MODIS
Publisher: MDPI AG
Date: 12-06-2019
DOI: 10.3390/RS11121398
Abstract: Remote sensing of phenology usually works at the regional and global scales, which imposes considerable variations in the solar zenith angle (SZA) across space and time. Variations in SZA alters the shape and profile of the surface reflectance and vegetation index (VI) time series, but this effect on remote-sensing-derived vegetation phenology has not been adequately evaluated. The objective of this study is to understand the behaviour of VIs response to SZA, and to further improve the interpretation of satellite observed vegetation dynamics, across space and time. In this study, the sensitivity of two widely used VIs—the normalised difference vegetation index (NDVI) and the enhanced vegetation index (EVI)—to SZA was investigated at four northern Australian savanna sites, over a latitudinal distance of 9.8° (~1100 km). Complete time series of surface reflectances, as acquired with different SZA configurations, were simulated using Bidirectional Reflectance Distribution Function (BRDF) parameters provided by MODerate Resolution Imaging Spectroradiometer (MODIS). The sun-angle dependency of the four phenological transition dates were assessed. Results showed that while NDVI was very sensitive to SZA, such sensitivity was nearly absent for EVI. A negative correlation was also observed between NDVI sensitivity to SZA and vegetation cover, with sensitivity declining to the same level as EVI when vegetation cover was high. Different sun-angle configurations resulted in considerable variations in the shape and magnitude of the phenological profiles. The sensitivity of VIs to SZA was generally greater during the dry season (with only active trees present) than in the wet season (with both active trees and grasses), thus, the sun-angle effect on VIs was phenophase-dependent. The sun-angle effect on NDVI time series resulted in considerable differences in the phenological metrics across different sun-angle configurations. Across four sites, the sun-angle effect caused 15.5 days, 21.6 days, and 20.5 days differences in the start, peak, and the end of the growing season derived from NDVI time series, with seasonally varying SZA at local solar noon, as compared to those metrics derived from NDVI time series with fixed SZA. In comparison, those differences in the start, peak, and end of the growing season for EVI were significantly smaller, with only 4.8 days, 4.9 days, and 3 days, respectively. Our results suggest the potential importance of considering the seasonal SZA effect on VI time series prior to the retrieval of phenological metrics.
Development of vegetation and soil indices for MODIS-EOS
Publisher: Elsevier BV
Date: 09-1994
Centennial Annual Rainfall Pattern Changes Show an Increasing Trend with Higher Variation over Northern Australia
Publisher: American Meteorological Society
Date: 08-2022
Abstract: Global warming and anthropogenic activities have imposed noticeable impacts on rainfall pattern changes at both spatial and temporal scales in recent decades. Systematic diagnosis of rainfall pattern changes is urgently needed at spatiotemporal scales for a deeper understanding of how climate change produces variations in rainfall patterns. The objective of this study was to identify rainfall pattern changes systematically under climate change at a subcontinental scale along a rainfall gradient ranging from 1800 to 200 mm yr −1 by analyzing centennial rainfall data covering 230 sites from 1910 to 2017 in the Northern Territory of Australia. Rainfall pattern changes were characterized by considering aspects of trends and periodicity of annual rainfall, abrupt changes, rainfall distribution, and extreme rainfall events. Our results illustrated that rainfall patterns in northern Australia have changed significantly compared with the early period of the twentieth century. Specifically, 1) a significant increasing trend in annual precipitation associated with greater variation in recent decades was observed over the entire study area, 2) temporal variations represented a mean rainfall periodicity of 27 years over wet to dry regions, 3) an abrupt change of annual rainfall amount occurred consistently in both humid and arid regions during the 1966–75 period, and 4) partitioned long-term time series of rainfall demonstrated a wetter rainfall distribution trend across coastal to inland areas that was associated with more frequent extreme rainfall events in recent decades. The findings of this study could facilitate further studies on the mechanisms of climate change that influence rainfall pattern changes. Characterizing long-term rainfall pattern changes under different rainfall conditions is important to understand the impacts of climate change. We conducted diagnosis of centennial rainfall pattern changes across wet to dry regions in northern Australia and found that rainfall patterns have noticeably changed in recent decades. The entire region has a consistent increasing trend of annual rainfall with higher variation. Meanwhile, the main shifting period of rainfall pattern was during 1966–75. Although annual rainfall seems to become wetter with an increasing trend, more frequent extreme rainfall events should also be noticed for assessing the impacts of climate changes. The findings support further study to understand long-term rainfall pattern changes under climate change.
Estimation of Soil Properties Using Hyperspectral
VIS
/
IR
Sensors
Publisher: Wiley
Date: 21-10-2005
DOI: 10.1002/0470848944.HSA064
Abstract: Knowledge of soil properties and processes are crucial to the understanding of the terrestrial hydrologic cycle and the functioning of terrestrial ecosystems. In this paper, we present the current state and potential of hyperspectral remote sensing techniques for quantitative retrieval of soil properties. Remote sensing is used to detect chemical and physical soil properties either (i) directly from the bare soil pixels, (ii) through advanced spectroscopy methods in mixed “soil‐vegetation‐litter” pixels, and (iii) by measurements of the overlying vegetated canopy to infer soil properties and moisture status. Optical‐geometric properties of soil surfaces reveal information on soil physical features, such as soil structure, crusting, and erosion. We also investigate the use of vegetation water indices to infer soil drying and wetting in the soil root zone. We conclude with a discussion on future needs and directions for remote sensing of soil properties.
Effects of Forest Canopy Vertical Stratification on the Estimation of Gross Primary Production by Remote Sensing
Publisher: MDPI AG
Date: 21-08-2018
DOI: 10.3390/RS10091329
Abstract: Gross primary production (GPP) in forests is the most important carbon flux in terrestrial ecosystems. Forest ecosystems with high leaf area index (LAI) values have erse species or complex forest structures with vertical stratifications that influence the carbon–water–energy cycles. In this study, we used three light use efficiency (LUE) GPP models and site-level experiment data to analyze the effects of the vertical stratification of dense forest vegetation on the estimates of remotely sensed GPP during the growing season of two forest sites in East Asia: Dinghushan (DHS) and Tomakomai (TMK). The results showed that different controlling environmental factors of the vertical layers, such as temperature and vapor pressure deficit (VPD), produce different responses for the same LUE value in the different sub-ecosystems (defined as the tree, shrub, and grass layers), which influences the GPP estimation. Air temperature and VPD play important roles in the effects of vertical stratification on the GPP estimates in dense forests, which led to differences in GPP uncertainties from −50% to 30% because of the distinct temperature responses in TMK. The unequal vertical LAI distributions in the different sub-ecosystems led to GPP variations of 1–2 gC/m2/day with uncertainties of approximately −30% to 20% because sub-ecosystems have unique absorbed fractions of photosynthetically active radiation (APAR) and LUE. A comparison with the flux tower-based GPP data indicated that the GPP estimations from the LUE and APAR values from separate vertical layers exhibited better model performance than those calculated using the single-layer method, with 10% less bias in DHS and more than 70% less bias in TMK. The precision of the estimated GPP in regions with thick understory vegetation could be effectively improved by considering the vertical variations in environmental parameters and the LAI values of different sub-ecosystems as separate factors when calculating the GPP of different components. Our results provide useful insight that can be used to improve the accuracy of remote sensing GPP estimations by considering vertical stratification parameters along with the LAI of sub-ecosystems in dense forests.
Estimation of latent heat flux over savannah vegetation across the North Australian Tropical Transect from multiple sensors and global meteorological data
Publisher: Elsevier BV
Date: 2017
Intrinsic climate dependency of ecosystem light and water-use-efficiencies across Australian biomes
Publisher: IOP Publishing
Date: 10-2014
Response of Spectral Reflectances and Vegetation Indices on Varying Juniper Cone Densities
Publisher: MDPI AG
Date: 22-10-2013
DOI: 10.3390/RS5105330
Multi-Scale Phenology of Temperate Grasslands: Improving Monitoring and Management With Near-Surface Phenocams
Publisher: Frontiers Media SA
Date: 05-02-2019
Climate impacts on wheat phenology and production using mutisource data in NSW, Australia
Publisher: IEEE
Date: 07-2016
Spatiotemporal partitioning of savanna plant functional type productivity along NATT
Publisher: Elsevier BV
Date: 09-2020
ESTIMATION OF THE FRACTION OF CANOPY COVER FROM MULTISPECTRAL DATA TO BE USED IN A WATER SOIL EROSION PREDICTION MODEL
Publisher: SciELO Agencia Nacional de Investigacion y Desarrollo (ANID)
Date: 2004
Topoclimatic modeling for minimum temperature prediction at a regional scale in the Central Valley of Chile*
Publisher: EDP Sciences
Date: 1997
Mangrove Phenology and Water Influences Measured with Digital Repeat Photography
Publisher: MDPI AG
Date: 17-01-2021
DOI: 10.3390/RS13020307
Abstract: The intertidal habitat of mangroves is very complex due to the dynamic roles of land and sea drivers. Knowledge of mangrove phenology can help in understanding mangrove growth cycles and their responses to climate and environmental changes. Studies of phenology based on digital repeat photography, or phenocams, have been successful in many terrestrial forests and other ecosystems, however few phenocam studies in mangrove forests showing the influence and interactions of water color and tidal water levels have been performed in sub-tropical and equatorial environments. In this study, we investigated the diurnal and seasonal patterns of an equatorial mangrove forest area at an Andaman Sea site in Phuket province, Southern Thailand, using two phenocams placed at different elevations and with different view orientations, which continuously monitored vegetation and water dynamics from July 2015 to August 2016. The aims of this study were to investigate fine-resolution, in situ mangrove forest phenology and assess the influence and interactions of water color and tidal water levels on the mangrove–water canopy signal. Diurnal and seasonal patterns of red, green, and blue chromatic coordinate (RCC, GCC, and BCC) indices were analyzed over various mangrove forest and water regions of interest (ROI). GCC signals from the water background were found to positively track diurnal water levels, while RCC signals were negatively related with tidal water levels, hence lower water levels yielded higher RCC values, reflecting brownish water colors and increased soil and mud exposure. At seasonal scales, the GCC profiles of the mangrove forest peaked in the dry season and were negatively related with the water level, however the inclusion of the water background signal d ened this relationship. We also detected a strong lunar tidal water periodicity in seasonal GCC values that was not only present in the water background, but was also detected in the mangrove–water canopy and mangrove forest phenology profiles. This suggests significant interactions between mangrove forests and their water backgrounds (color and depth), which may need to be accounted for in upscaling and coupling with satellite-based mangrove monitoring.
Comparison of the performance of latent heat flux products over southern hemisphere forest ecosystems: estimating latent heat flux error structure using in situ measurements and the triple coll
Publisher: Informa UK Limited
Date: 03-04-2018
Using Fraction Images to Study Natural Land Cover Changes in the Amazon
Publisher: IEEE
Date: 07-2006
Analysis of the global vegetation dynamic metrics using MODIS vegetation index and land cover products
Publisher: IEEE
Date: 2004
Soil and Sun angle interactions on partial canopy spectra
Publisher: Informa UK Limited
Date: 09-1987
Bidirectional properties and utilizations of high‐resolution spectra from a semiarid watershed
Publisher: American Geophysical Union (AGU)
Date: 05-1994
DOI: 10.1029/93WR03058
The use of vegetation indices in forested regions: issues of linearity and saturation
Publisher: IEEE
Date: 1997
Soil and atmosphere influences on the spectra of partial canopies
Publisher: Elsevier BV
Date: 06-1988
Effects of standing litter on the biophysical interpretation of plant canopies with spectral indices
Publisher: Elsevier BV
Date: 02-1996
Deconvolution of remotely sensed spectral mixtures for retrieval of LAI, fAPAR and soil brightness
Publisher: Elsevier BV
Date: 02-1997
The land–atmosphere water flux in the tropics
Publisher: Wiley
Date: 07-10-2009
Hyperspectral Applications to Landscape Phenology
Publisher: CRC Press
Date: 07-12-2018
Basin‐scale solar irradiance estimates in semiarid regions using GOES 7
Publisher: American Geophysical Union (AGU)
Date: 05-1994
DOI: 10.1029/93WR03059
Responses of LAI to rainfall explain contrasting sensitivities to carbon uptake between forest and non-forest ecosystems in Australia
Publisher: Springer Science and Business Media LLC
Date: 15-09-2017
DOI: 10.1038/S41598-017-11063-W
Abstract: Non-forest ecosystems (predominant in semi-arid and arid regions) contribute significantly to the increasing trend and interannual variation of land carbon uptake over the last three decades, yet the mechanisms are poorly understood. By analysing the flux measurements from 23 ecosystems in Australia, we found the the correlation between gross primary production (GPP) and ecosystem respiration (R e ) was significant for non-forest ecosystems, but was not for forests. In non-forest ecosystems, both GPP and R e increased with rainfall, and, consequently net ecosystem production (NEP) increased with rainfall. In forest ecosystems, GPP and R e were insensitive to rainfall. Furthermore sensitivity of GPP to rainfall was dominated by the rainfall-driven variation of LAI rather GPP per unit LAI in non-forest ecosystems, which was not correctly reproduced by current land models, indicating that the mechanisms underlying the response of LAI to rainfall should be targeted for future model development.
Optical and seasonal variations along the U.S.-Mexico border: an analysis with Landsat TM imagery
Publisher: IEEE
Date: 1994
Investigation of land surface phenology detections in shrublands using multiple scale satellite data
Publisher: Elsevier BV
Date: 2021
Toward the development of a multidirectional vegetation index
Publisher: American Geophysical Union (AGU)
Date: 05-1994
DOI: 10.1029/93WR03063
Assessing the ability of MODIS EVI to estimate terrestrial ecosystem gross primary production of multiple land cover types
Publisher: Elsevier BV
Date: 2017
Directional vegetation index interactions in ASAS imagery
Publisher: IEEE
Date: 1994
Evaluating Global Land Surface Models in CMIP5: Analysis of Ecosystem Water- and Light-Use Efficiencies and Rainfall Partitioning
Publisher: American Meteorological Society
Date: 20-03-2018
Abstract: Water and carbon fluxes simulated by 12 Earth system models (ESMs) that participated in phase 5 of the Coupled Model Intercomparison Project (CMIP5) over several recent decades were evaluated using three functional constraints that are derived from both model simulations, or four global datasets, and 736 site-year measurements. Three functional constraints are ecosystem water-use efficiency (WUE), light-use efficiency (LUE), and the partitioning of precipitation P into evapotranspiration (ET) and runoff based on the Budyko framework. Although values of these three constraints varied significantly with time scale and should be quite conservative if being averaged over multiple decades, the results showed that both WUE and LUE simulated by the ensemble mean of 12 ESMs were generally lower than the site measurements. Simulations by the ESMs were generally consistent with the broad pattern of energy-controlled ET under wet conditions and soil water-controlled ET under dry conditions, as described by the Budyko framework. However, the value of the parameter in the Budyko framework ω, obtained from fitting the Budyko curve to the ensemble model simulation (1.74), was larger than the best-fit value of ω to the observed data (1.28). Globally, the ensemble mean of multiple models, although performing better than any in idual model simulations, still underestimated the observed WUE and LUE, and overestimated the ratio of ET to P, as a result of overestimation in ET and underestimation in gross primary production (GPP). The results suggest that future model development should focus on improving the algorithms of the partitioning of precipitation into ecosystem ET and runoff, and the coupling of water and carbon cycles for different land-use types.
Analysis of NDVI and scaled difference vegetation index retrievals of vegetation fraction
Publisher: Elsevier BV
Date: 04-2006
Country-level net primary production distribution and response to drought and land cover change
Publisher: Elsevier BV
Date: 2017
DOI: 10.1016/J.SCITOTENV.2016.09.033
Abstract: Carbon sequestration by terrestrial ecosystems can offset emissions and thereby offers an alternative way of achieving the target of reducing the concentration of CO
Estimating biophysical parameters of rice with remote sensing data using support vector machines
Publisher: Springer Science and Business Media LLC
Date: 03-2011
DOI: 10.1007/S11427-011-4135-4
Abstract: Hyperspectral reflectance (350-2500 nm) measurements were made over two experimental rice fields containing two cultivars treated with three levels of nitrogen application. Four different transformations of the reflectance data were analyzed for their capability to predict rice biophysical parameters, comprising leaf area index (LAI m(2) green leaf area m(-2) soil) and green leaf chlorophyll density (GLCD mg chlorophyll m(-2) soil), using stepwise multiple regression (SMR) models and support vector machines (SVMs). Four transformations of the rice canopy data were made, comprising reflectances (R), first-order derivative reflectances (D1), second-order derivative reflectances (D2), and logarithm transformation of reflectances (LOG). The polynomial kernel (POLY) of the SVM using R was the best model to predict rice LAI, with a root mean square error (RMSE) of 1.0496 LAI units. The analysis of variance kernel of SVM using LOG was the best model to predict rice GLCD, with an RMSE of 523.0741 mg m(-2). The SVM approach was not only superior to SMR models for predicting the rice biophysical parameters, but also provided a useful exploratory and predictive tool for analyzing different transformations of reflectance data.
An improved SPEI drought forecasting approach using the long short-term memory neural network
Publisher: Elsevier BV
Date: 04-2021
Functional response of U.S. grasslands to the early 21st‐century drought
Publisher: Wiley
Date: 08-2014
DOI: 10.1890/13-1687.1
Abstract: Grasslands across the United States play a key role in regional livelihood and national food security. Yet, it is still unclear how this important resource will respond to the prolonged warm droughts and more intense rainfall events predicted with climate change. The early 21st-century drought in the southwestern United States resulted in hydroclimatic conditions that are similar to those expected with future climate change. We investigated the impact of the early 21st-century drought on aboveground net primary production (ANPP) of six desert and plains grasslands dominated by C4 (warm season) grasses in terms of significant deviations between observed and expected ANPP. In desert grasslands, drought-induced grass mortality led to shifts in the functional response to annual total precipitation (P(T)), and in some cases, new species assemblages occurred that included invasive species. In contrast, the ANPP in plains grasslands exhibited a strong linear function of the current-year P(T) and the previous-year ANPP, despite prolonged warm drought. We used these results to disentangle the impacts of interannual total precipitation, intra-annual precipitation patterns, and grassland abundance on ANPP, and thus generalize the functional response of C4 grasslands to predicted climate change. This will allow managers to plan for predictable shifts in resources associated with climate change related to fire risk, loss of forage, and ecosystem services.
Vegetation detection through smoke‐filled AVIRIS images: An assessment using MODIS band passes
Publisher: American Geophysical Union (AGU)
Date: 12-1998
DOI: 10.1029/98JD00051
Global variability of terrestrial surface properties derived from MODIS visible to thermal-infrared measurements
Publisher: IEEE
Date: 2005
Amazon rainforests green‐up with sunlight in dry season
Publisher: American Geophysical Union (AGU)
Date: 03-2006
DOI: 10.1029/2005GL025583
Spatial pattern and seasonal dynamics of the photosynthesis activity across Australian rainfed croplands
Publisher: Elsevier BV
Date: 2020
Prediction of airborne pollen and sub-pollen particles for thunderstorm asthma outbreaks assessment
Publisher: Elsevier BV
Date: 03-2023
Dependence of NDVI and SAVI on sun/sensor geometry and its effect on fAPAR relationships in Alfalfa
Publisher: Elsevier BV
Date: 03-1995
Estimating the Aboveground Biomass for Planted Forests Based on Stand Age and Environmental Variables
Publisher: MDPI AG
Date: 28-09-2019
DOI: 10.3390/RS11192270
Abstract: Measuring forest aboveground biomass (AGB) at local to regional scales is critical to understanding their role in regional and global carbon cycles. The Three-North Shelterbelt Forest Program (TNSFP) is the largest ecological restoration project in the world, and has been ongoing for over 40 years. In this study, we developed models to estimate the planted forest aboveground biomass (PF_AGB) for Yulin, a typical area in the project. Surface reflectances in the study area from 1978 to 2013 were obtained from Landsat series images, and integrated forest z-scores were constructed to measure afforestation and the stand age of planted forest. Normalized difference vegetation index (NDVI) was combined with stand age to develop an initial model to estimate PF_AGB. We then developed additional models that added environment variables to our initial model, including climatic factors (average temperature, total precipitation, and total sunshine duration) and a topography factor (slope). The model which combined the total precipitation and slope greatly improved the accuracy of PF_AGB estimation compared to the initial model, indicating that the environmental variables related to water distribution indirectly affected the growth of the planted forest and the resulting AGB. Afforestation in the study area occurred mainly in the early 1980s and early 21st century, and the PF_AGB in 2003 was 2.3 times than that of 1998, since the fourth term TNSFP started in 2000. The PF_AGB in 2013 was about 3.33 times of that in 2003 because many young trees matured. The leave-one-out cross-validation (LOOCV) approach showed that our estimated PF_AGB had a significant correlation with field-measured data (correlation coefficient (r) = 0.89, p 0.001, root mean square error (RMSE) = 6.79 t/ha). Our studies provided a method to estimate long time series PF_AGB using satellite repetitive measures, particularly for arid or semi-arid areas.
Abrupt shifts in phenology and vegetation productivity under climate extremes
Publisher: American Geophysical Union (AGU)
Date: 10-2015
DOI: 10.1002/2015JG003144
Influence of Sun-view geometries on the relationships among vegetation indices, LAI, and absorbed PAR
Publisher: IEEE
Date: 1994
MODIS vegetation products as proxies of photosynthetic potential: a look across meteorological and biologic driven ecosystem productivity
Publisher: Copernicus GmbH
Date: 04-12-2015
DOI: 10.5194/BGD-12-19213-2015
Abstract: Abstract. A direct relationship between gross ecosystem productivity (GEP) measured by the eddy covariance (EC) method and Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices (VIs) has been observed in many temperate and tropical ecosystems. However, in Australian evergreen forests, and particularly sclerophyll woodlands, MODIS VIs do not capture seasonality of GEP. In this study, we re-evaluate the connection between satellite and flux tower data at four contrasting Australian ecosystems, through comparisons of ecosystem photosynthetic activity (GEP) and potential (e.g. ecosystem light use efficiency and quantum yield) with MODIS vegetation satellite products, including VIs, gross primary productivity (GPPMOD), leaf area index (LAIMOD), and fraction of photosynthetic active radiation (fPARMOD). We found that satellite derived greenness products constitute a measurement of ecosystem structure (e.g. leaf area index – quantity of leaves) and function (e.g. leaf level photosynthetic assimilation capacity – quality of leaves), rather than productivity. Our results show that in primarily meteorological-driven (e.g. photosynthetic active radiation, air temperature and/or precipitation) and relatively aseasonal vegetation photosynthetic potential ecosystems (e.g. evergreen wet sclerophyll forests), there were no statistically significant relationships between GEP and satellite derived measures of greenness. In contrast, for phenology-driven ecosystems (e.g. tropical savannas), changes in the vegetation status drove GEP, and tower-based measurements of photosynthetic activity were best represented by VIs. We observed the highest correlations between MODIS products and GEP in locations where key meteorological variables and vegetation phenology were synchronous (e.g. semi-arid Acacia woodlands) and low correlation at locations where they were asynchronous (e.g. Mediterranean ecosystems). Eddy covariance data offer much more than validation and/or calibration of satellite data and models. Knowledge of the conditions in which flux tower measurements and VIs or other remote sensing products converge greatly advances our understanding of the mechanisms driving the carbon cycle (phenology and climate drivers) and provides an ecological basis for interpretation of satellite derived measures of greenness.
Australian vegetation phenology: new insights from satellite remote sensing and digital repeat photography
Publisher: Copernicus GmbH
Date: 10-05-2016
DOI: 10.5194/BG-2016-175
Abstract: Abstract. Phenology is the study of periodic biological occurrences and can provide important insights into the influence of climatic variability and change on ecosystems. Understanding Australia’s vegetation phenology is a challenge due to its erse range of ecosystems, from savannas and tropical rainforests to temperate eucalypt woodlands, semi-arid scrublands and alpine grasslands. These ecosystems exhibit marked differences in seasonal patterns of canopy development and plant life-cycle events, much of which deviates from the predictable seasonal phenological pulse of temperate deciduous and boreal biomes. Many Australian ecosystems are subject to irregular events (i.e., drought, flooding, cyclones and fire) that can alter ecosystem composition, structure and functioning just as much as seasonal change. We show how satellite remote sensing and ground-based digital repeat photography (i.e. phenocams) can be used to improve understanding of phenology in Australian ecosystems. First, we examine temporal variation in phenology at the continental scale using the Enhanced Vegetation Index (EVI), calculated from MODerate resolution Imaging Spectroradiomter (MODIS) data. Spatial gradients are revealed, ranging from regions with pronounced seasonality in canopy development (i.e., tropical savannas) to regions where seasonal variation is minimal (i.e., tropical rainforests) or high but irregular (i.e., arid ecosystems). Next, we use time series colour information extracted from phenocam imagery to illustrate a range of phenological signals in four contrasting Australian ecosystems. These include greening and senescing events in tropical savannas and temperate eucalypt understory, as well as strong seasonal dynamics of in idual trees in a seemingly static evergreen rainforest. We also demonstrate how phenology links with ecosystem gross primary productivity (from eddy covariance) and discuss why these processes are linked in some ecosystems but not others. We conclude that phenocams have the potential to greatly improve current understanding of Australian ecosystems. To facilitate sharing of this information, we have formed the Australian Phenocam Network (phenocam.org.au/).
Mangrove lagoons of the Great Barrier Reef support coral populations persisting under extreme environmental conditions
Publisher: Inter-Research Science Center
Date: 29-08-2019
DOI: 10.3354/MEPS13073
Biophysical interpretation of a spectral mixture model based on a radiative transfer model and observational data
Publisher: IEEE
Date: 1994
Radiative transfer in shrub savanna sites in Niger: preliminary results from HAPEX-Sahel. 3. Optical dynamics and vegetation index sensitivity to biomass and plant cover
Publisher: Elsevier BV
Date: 07-1994
An error and sensitivity analysis of the atmospheric- and soil-correcting variants of the NDVI for the MODIS-EOS
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-1994
DOI: 10.1109/36.298018
Derivation of vegetation isoline equations in red-NIR reflectance space
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2000
DOI: 10.1109/36.842012
Biological processes dominate seasonality of remotely sensed canopy greenness in an Amazon evergreen forest
Publisher: Wiley
Date: 23-12-2017
DOI: 10.1111/NPH.14939
Abstract: Satellite observations of Amazon forests show seasonal and interannual variations, but the underlying biological processes remain debated. Here we combined radiative transfer models (RTMs) with field observations of Amazon forest leaf and canopy characteristics to test three hypotheses for satellite-observed canopy reflectance seasonality: seasonal changes in leaf area index, in canopy-surface leafless crown fraction and/or in leaf demography. Canopy RTMs (PROSAIL and FLiES), driven by these three factors combined, simulated satellite-observed seasonal patterns well, explaining c. 70% of the variability in a key reflectance-based vegetation index (MAIAC EVI, which removes artifacts that would otherwise arise from clouds/aerosols and sun-sensor geometry). Leaf area index, leafless crown fraction and leaf demography independently accounted for 1, 33 and 66% of FLiES-simulated EVI seasonality, respectively. These factors also strongly influenced modeled near-infrared (NIR) reflectance, explaining why both modeled and observed EVI, which is especially sensitive to NIR, captures canopy seasonal dynamics well. Our improved analysis of canopy-scale biophysics rules out satellite artifacts as significant causes of satellite-observed seasonal patterns at this site, implying that aggregated phenology explains the larger scale remotely observed patterns. This work significantly reconciles current controversies about satellite-detected Amazon phenology, and improves our use of satellite observations to study climate-phenology relationships in the tropics.
Interpretation of the modified soil-adjusted vegetation index isolines in red-NIR reflectance space
Publisher: SPIE-Intl Soc Optical Eng
Date: 2007
DOI: 10.1117/1.2709702
Spatial and seasonal characterization of net primary productivity and climate variables in southeastern China using MODIS data
Publisher: Zhejiang University Press
Date: 04-2010
Soil‐Dependent Spectral Response in a Developing Plant Canopy1
Publisher: Wiley
Date: 1987
Water Loss Due to Increasing Planted Vegetation over the Badain Jaran Desert, China
Publisher: MDPI AG
Date: 18-01-2018
DOI: 10.3390/RS10010134
Groundwater-dependent ecosystems: recent insights from satellite and field-based studies
Publisher: Copernicus GmbH
Date: 21-10-2015
DOI: 10.5194/HESS-19-4229-2015
Abstract: Abstract. Groundwater-dependent ecosystems (GDEs) are at risk globally due to unsustainable levels of groundwater extraction, especially in arid and semi-arid regions. In this review, we examine recent developments in the ecohydrology of GDEs with a focus on three knowledge gaps: (1) how do we locate GDEs, (2) how much water is transpired from shallow aquifers by GDEs and (3) what are the responses of GDEs to excessive groundwater extraction? The answers to these questions will determine water allocations that are required to sustain functioning of GDEs and to guide regulations on groundwater extraction to avoid negative impacts on GDEs. We discuss three methods for identifying GDEs: (1) techniques relying on remotely sensed information (2) fluctuations in depth-to-groundwater that are associated with diurnal variations in transpiration and (3) stable isotope analysis of water sources in the transpiration stream. We then discuss several methods for estimating rates of GW use, including direct measurement using sapflux or eddy covariance technologies, estimation of a climate wetness index within a Budyko framework, spatial distribution of evapotranspiration (ET) using remote sensing, groundwater modelling and stable isotopes. Remote sensing methods often rely on direct measurements to calibrate the relationship between vegetation indices and ET. ET from GDEs is also determined using hydrologic models of varying complexity, from the White method to fully coupled, variable saturation models. Combinations of methods are typically employed to obtain clearer insight into the components of groundwater discharge in GDEs, such as the proportional importance of transpiration versus evaporation (e.g. using stable isotopes) or from groundwater versus rainwater sources. Groundwater extraction can have severe consequences for the structure and function of GDEs. In the most extreme cases, phreatophytes experience crown dieback and death following groundwater drawdown. We provide a brief review of two case studies of the impacts of GW extraction and then provide an ecosystem-scale, multiple trait, integrated metric of the impact of differences in groundwater depth on the structure and function of eucalypt forests growing along a natural gradient in depth-to-groundwater. We conclude with a discussion of a depth-to-groundwater threshold in this mesic GDE. Beyond this threshold, significant changes occur in ecosystem structure and function.
Leaf area index and normalized difference vegetation index as predictors of canopy characteristics and light interception by riparian species on the Lower Colorado River
Publisher: Elsevier BV
Date: 09-2004
Indices of Vegetation Activity
Publisher: Springer Berlin Heidelberg
Date: 27-12-2013
Relationship Between Remotely-sensed Vegetation Indices, Canopy Attributes and Plant Physiological Processes: What Vegetation Indices Can and Cannot Tell Us About the Landscape
Publisher: MDPI AG
Date: 28-03-2008
DOI: 10.3390/S8042136
Evaluation of the performance of short-term curated daily airborne grass pollen forecasts in diverse biogeographical regions during the AusPollen Partnership project 2016–2020
Publisher: Elsevier BV
Date: 10-2022
Assessing the response of the MODIS vegetation indices to landscape disturbance in the forested areas of the legal Brazilian Amazon
Publisher: Informa UK Limited
Date: 17-02-2010
A new phenology-based method for mapping wheat and barley using time-series of Sentinel-2 images
Publisher: Elsevier BV
Date: 10-2022
Soil Line Influences on Two-Band Vegetation Indices and Vegetation Isolines: A Numerical Study
Publisher: MDPI AG
Date: 12-02-2010
DOI: 10.3390/RS2020545
Spectral compatibility of vegetation indices across sensors: band decomposition analysis with Hyperion data
Publisher: SPIE-Intl Soc Optical Eng
Date: 03-2010
DOI: 10.1117/1.3400635
Análise compararativa dos produtos MODIS Ecologia para o monitoramento biofísico ambiental do bioma cerrado
Publisher: FapUNIFESP (SciELO)
Date: 06-2006
Monitoring Rainforest Dynamics in the Amazon with MODIS Land Products
Publisher: IEEE
Date: 07-2006
MODIS Vegetation Index Compositing Approach
Publisher: Elsevier BV
Date: 09-1999
Spatial based drought assessment: Where are we heading? A review on the current status and future
Publisher: Elsevier BV
Date: 10-2022
Differences in grass pollen allergen exposure across Australia
Publisher: Elsevier BV
Date: 02-2015
C- and Multiangle Ku-Band Synthetic Aperture Radar Data for Bare Soil Moisture Estimation in Agricultural Areas
Publisher: Elsevier BV
Date: 04-1998
<title>Validation of the MODIS vegetation indices over a global set of test sites: preliminary results</title>
Publisher: SPIE
Date: 23-01-2001
DOI: 10.1117/12.413945
Vegetation Index Methods for Estimating Evapotranspiration by Remote Sensing
Publisher: Springer Science and Business Media LLC
Date: 17-10-2010
Remote sensing of the terrestrial carbon cycle: A review of advances over 50 years
Publisher: Elsevier BV
Date: 11-2019
Soil spectral effects on 4-space vegetation discrimination
Publisher: Elsevier BV
Date: 03-1984
MODIS seasonal and inter-annual responses of semiarid ecosystems to drought in the southwest U.S.A.
Publisher: IEEE
Date: 2004
Spectral Compatibility of the NDVI Across VIIRS, MODIS, and AVHRR: An Analysis of Atmospheric Effects Using EO-1 Hyperion
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2013
Hyperspectral assesments of condition and species composition of Australian grasslands
Publisher: IEEE
Date: 07-2013
Forecasting Pollen Aerobiology with Modis EVI, Land Cover, and Phenology Using Machine Learning Tools
Publisher: IEEE
Date: 07-2019
Spatio-Temporal Variation of the Urban Heat Island in Santiago, Chile during Summers 2005–2017
Publisher: MDPI AG
Date: 13-10-2020
DOI: 10.3390/RS12203345
Abstract: Urban heat islands (UHIs) can present significant risks to human health. Santiago, Chile has around 7 million residents, concentrated in an average density of 480 people/km2. During the last few summer seasons, the highest extreme maximum temperatures in over 100 years have been recorded. Given the projections in temperature increase for this metropolitan region over the next 50 years, the Santiago UHI could have an important impact on the health and stress of the general population. We studied the presence and spatial variability of UHIs in Santiago during the summer seasons from 2005 to 2017 using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery and data from nine meteorological stations. Simple regression models, geographic weighted regression (GWR) models and geostatistical interpolations were used to find nocturnal thermal differences in UHIs of up to 9 °C, as well as increases in the magnitude and extension of the daytime heat island from summer 2014 to 2017. Understanding the behavior of the UHI of Santiago, Chile, is important for urban planners and local decision makers. Additionally, understanding the spatial pattern of the UHI could improve knowledge about how urban areas experience and could mitigate climate change.
Eastern‐Pacific and Central‐Pacific Types of ENSO Elicit Diverse Responses of Vegetation in the West Pacific Region
Publisher: American Geophysical Union (AGU)
Date: 27-01-2022
DOI: 10.1029/2021GL096666
Abstract: The El Niño‐Southern Oscillation (ENSO) is one of the main factors causing extreme climate events and, thus, has a significant influence on global climate systems. However, the long‐term effects of ENSO on vegetation are not well understood due to the complexity of the ENSO phenomenon under global warming. Here, we examined the variations in the response of Leaf Area Index (LAI) to different types of ENSO from 1982 to 2017 in the west Pacific region and explored their relationship with climatic factors. Results show that about 34.5% of the vegetated area in the west Pacific region displayed LAI anomalies correlated with ENSO index from 1982 to 2017, which distributed differently across climatic types. Moreover, LAI anomalies elicited by the Central‐Pacific type and by the Eastern‐Pacific type of ENSO events were significantly different, which were contributed to the controls of the different types of ENSO on precipitation and temperature.
Land Resources Monitoring, Modeling, and Mapping with Remote Sensing
Publisher: CRC Press
Date: 02-10-2015
DOI: 10.1201/B19322
Satellite sun‐induced chlorophyll fluorescence detects early response of winter wheat to heat stress in the Indian Indo‐Gangetic Plains
Publisher: Wiley
Date: 22-06-2018
DOI: 10.1111/GCB.14302
Abstract: Extremely high temperatures represent one of the most severe abiotic stresses limiting crop productivity. However, understanding crop responses to heat stress is still limited considering the increases in both the frequency and severity of heat wave events under climate change. This limited understanding is partly due to the lack of studies or tools for the timely and accurate monitoring of crop responses to extreme heat over broad spatial scales. In this work, we use novel spaceborne data of sun-induced chlorophyll fluorescence (SIF), which is a new proxy for photosynthetic activity, along with traditional vegetation indices (Normalized Difference Vegetation Index NDVI and Enhanced Vegetation Index EVI) to investigate the impacts of heat stress on winter wheat in northwestern India, one of the world's major wheat production areas. In 2010, an abrupt rise in temperature that began in March adversely affected the productivity of wheat and caused yield losses of 6% compared to previous year. The yield predicted by satellite observations of SIF decreased by approximately 13.9%, compared to the 1.2% and 0.4% changes in NDVI and EVI, respectively. During early stage of this heat wave event in early March 2010, the SIF observations showed a significant reduction and earlier response, while NDVI and EVI showed no changes and could not capture the heat stress until late March. The spatial patterns of SIF anomalies closely tracked the temporal evolution of the heat stress over the study area. Furthermore, our results show that SIF can provide large-scale, physiology-related wheat stress response as indicated by the larger reduction in fluorescence yield (SIF
Spectral Cross-Calibration of VIIRS Enhanced Vegetation Index with MODIS: A Case Study Using Year-Long Global Data
Publisher: MDPI AG
Date: 05-01-2016
DOI: 10.3390/RS8010034
Land Remote Sensing and Global Environmental Change
Publisher: Springer New York
Date: 2011
Estimates of surface soil water content using linear combinations of spectral wavebands
Publisher: Springer Science and Business Media LLC
Date: 1990
DOI: 10.1007/BF00865985
The Melbourne epidemic thunderstorm asthma event 2016: an investigation of environmental triggers, effect on health services, and patient risk factors
Publisher: Elsevier BV
Date: 06-2018
Soil Properties
Publisher: Springer New York
Date: 2014
An operational deforestation mapping system using MODIS data and spatial context analysis
Publisher: Informa UK Limited
Date: 10-01-2007
Advances in Hyperspectral Remote Sensing of Vegetation and Agricultural Croplands
Publisher: CRC Press
Date: 25-10-2011
DOI: 10.1201/B11222-3
Scaling dependencies and uncertainties in vegetation index - biophysical retrievals in heterogeneous environments
Publisher: IEEE
Date: 2005
Multi-scale phenology from digital time-lapse camera to Sentinel-2 and MODIS over Australian pastures
Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-7261
Abstract: & & As a natural ecosystem dominated by grasses, phenological studies of pastures have attracted increased attention for their important roles in global carbon cycling, ecosystem bio ersity, and public health. To better understand pasture phenology from in-situ to regional scales, accurate monitoring of pasture greenness variations across different scales is critical. As an alternative approach to labor-intensive field surveys, digital time-lapse cameras (termed phenocams) can provide diurnal and long-term vegetation greenness observation at in-situ scale with less impact from atmospheric effects. Even so, monitoring of phenology at regional to global scales only can be obtained by satellite remote sensing. The data from satellite sensors whether medium-resolution (i.e. Moderate Resolution Imaging Spectrodiometer, MODIS, 250 m) or fine spatial resolution (i.e. Sentinel-2 mission, 10 m) is widely used for vegetation phenology monitoring. However, achieving accurate pasture greenness dynamics using satellite data remains challenging due to limitations resulting from heterogeneity in Australian pastures.& & & & & & Combining phenocam, Sentinel-2 data and MODIS land surface products, this study aimed to (1) compare differences in temporal profiles of pasture greenness derived from ground-based phenocam and satellite sensors with fine- and medium-spatial resolutions, respectively (2) assess the capacity of Sentinel-2 pixels for representing the phenocam footprint for monitoring greenness dynamics and (3) evaluate the potential of improving greenness upscaling from phenocam to MODIS by masking non-grass areas via Sentinel-2 data.& & & & A set of RGB phenocams was deployed over sites located over eastern Australian pastures. Green chromatic coordinate (GCC) was calculated from phenocam images. Six spatial footprints centered at phenocam sites were defined (i.e. 10 m, 30 m, 90 m, 250 m, 750 m and 1250 m), in which the Enhanced Vegetation Index (EVI) was calculated from Sentinel-2 and MODIS. The correlations between phenocam GCC and Sentinel-2 EVI were analyzed at single and multiple sites within the phenocam footprint (& 100 m) across all phenophases. Similarly, the correlations between GCC and EVI derived from Sentinel-2 and MODIS were analyzed for larger scales (& 100 m). Finally, we analyzed the relationships between GCC and MODIS EVI derived after applying a Sentinel-2 grass mask.& & & & First, generally consistent temporal patterns of GCC and EVI were found at all spatial scales and phenophases, though there were differences at larger scales. Second, relationships between GCC and Sentinel-2 EVI within the phenocam footprint (& 100 m) kept nearly consistent regression trends and significant correlations whether from single or multiple sites, but decreasing at scales beyond 100 m. Third, correlations between GCC and MODIS EVI were similar to Sentinel-2 EVI at the same scales (& 100 m). However, at & 250 m scale, EVI derived from Sentinel-2 non-grass filtered data improved the correlation with GCC compared with EVI from all Sentinel-2 pixels and MODIS pixels. Our results indicate that Sentinel-2 can enable retrieval of grass pasture phenology in heterogeneous landscapes with higher accuracy compared with MODIS, and demonstrated the potential of Sentinel-2 data as a land cover filter to improve phenocam upscaling to MODIS. & & &
Vegetation's responses to climate variability
Publisher: Springer Science and Business Media LLC
Date: 17-02-2016
DOI: 10.1038/NATURE17301
Evaluating Spatial Representativeness of Station Observations for Remotely Sensed Leaf Area Index Products
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2016
Spectral response of the seagrass Zostera noltii with different sediment backgrounds
Publisher: Elsevier BV
Date: 04-2012
Spatial partitioning and temporal evolution of Australia's total water storage under extreme hydroclimatic impacts
Publisher: Elsevier BV
Date: 09-2016
Biophysical Applications of Satellite Remote Sensing
Publisher: Springer Berlin Heidelberg
Date: 2014
Dry-season greening of Amazon forests
Publisher: Springer Science and Business Media LLC
Date: 16-03-2016
DOI: 10.1038/NATURE16457
Regeneration of Native Trees in the Presence of Invasive Saltcedar in the Colorado River Delta, Mexico
Publisher: Wiley
Date: 12-2005
Multiple site tower flux and remote sensing comparisons of tropical forest dynamics in Monsoon Asia
Publisher: Elsevier BV
Date: 05-2008
The importance of interacting climate modes on Australia's contribution to global carbon cycle extremes
Publisher: Springer Science and Business Media LLC
Date: 15-03-2016
DOI: 10.1038/SREP23113
Abstract: The global carbon cycle is highly sensitive to climate-driven fluctuations of precipitation, especially in the Southern Hemisphere. This was clearly manifested by a 20% increase of the global terrestrial C sink in 2011 during the strongest sustained La Niña since 1917. However, inconsistencies exist between El Niño/La Niña (ENSO) cycles and precipitation in the historical record for ex le, significant ENSO–precipitation correlations were present in only 31% of the last 100 years, and often absent in wet years. To resolve these inconsistencies, we used an advanced temporal scaling method for identifying interactions amongst three key climate modes (El Niño, the Indian Ocean dipole, and the southern annular mode). When these climate modes synchronised (1999–2012), drought and extreme precipitation were observed across Australia. The interaction amongst these climate modes, more than the effect of any single mode, was associated with large fluctuations in precipitation and productivity. The long-term exposure of vegetation to this arid environment has favoured a resilient flora capable of large fluctuations in photosynthetic productivity and explains why Australia was a major contributor not only to the 2011 global C sink anomaly but also to global reductions in photosynthetic C uptake during the previous decade of drought.
Evapotranspiration on western U.S. rivers estimated using the Enhanced Vegetation Index from MODIS and data from eddy covariance and Bowen ratio flux towers
Publisher: Elsevier BV
Date: 15-08-2005
An error and sensitivity analysis of atmospheric resistant vegetation indices derived from dark target-based atmospheric correction
Publisher: Elsevier BV
Date: 12-2001
APPROACHES TO ESTABLISHING A METADATA STANDARD FOR FIELD SPECTROSCOPY DATASETS
Publisher: IEEE
Date: 07-2013
Assessment Of Soil-vegetation-senesced Materials With Spectral Mixture Modeling: Preliminary Analysis
Publisher: IEEE
Date: 1990
Multi-climate mode interactions drive hydrological and vegetation responses to hydroclimatic extremes in Australia
Publisher: Elsevier BV
Date: 09-2019
A GIS based change detection system for the Amazon forest: Advantages and implications for the environmental monitoring and regional sustainable development
Publisher: IEEE
Date: 2005
Regeneration of native trees in response to flood releases from the United States into the delta of the Colorado River, Mexico
Publisher: Elsevier BV
Date: 09-2001
Determining crop acreage estimates for specific winter crops using shape attributes from sequential MODIS imagery
Publisher: Elsevier BV
Date: 08-2013
Linearization of NDVI Based on its Relationship with Vegetation Fraction
Publisher: American Society for Photogrammetry and Remote Sensing
Date: 08-2010
Ecohydrological decoupling of water storage and vegetation attributed to China’s large-scale ecological restoration programs
Publisher: Elsevier BV
Date: 12-2022
Vegetation Indices
Publisher: Springer New York
Date: 2014
Synthetic Aperture Radar (L band) and Optical Vegetation Indices for Discriminating the Brazilian Savanna Physiognomies: A Comparative Analysis
Publisher: American Meteorological Society
Date: 09-2005
DOI: 10.1175/EI117.1
Abstract: The all-weather capability, signal independence to the solar illumination angle, and response to 3D vegetation structures are the highlights of active radar systems for natural vegetation mapping and monitoring. However, they may present significant soil background effects. This study addresses a comparative analysis of the performance of L-band synthetic aperture radar (SAR) data and optical vegetation indices (VIs) for discriminating the Brazilian cerrado physiognomies. The study area was the Brasilia National Park, Brazil, one of the test sites of the Large-Scale Biosphere–Atmosphere (LBA) experiment in Amazonia. Seasonal Japanese Earth Resources Satellite-1 (JERS-1) SAR backscatter coefficients (σ°) were compared with two vegetation indices [normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI)] over the five most dominant cerrados’ physiognomies plus gallery forest. In contrast to the VIs, σ° from dry and wet seasons did not change significantly, indicating primary response to vegetation structures. Discriminant analysis and analysis of variance (ANOVA) showed an overall higher performance of radar data. However, when both SAR and VIs are combined, the discrimination capability increased significantly, indicating that the fusion of the optical and radar backscatter observations provides overall improved classifications of the cerrado types. In addition, VIs showed good performance for monitoring the cerrado dynamics.
Land surface phenology retrievals for arid and semi-arid ecosystems
Publisher: Elsevier BV
Date: 03-2022
Estimating Peanut Leaf Chlorophyll Content with Dorsiventral Leaf Adjusted Indices: Minimizing the Impact of Spectral Differences between Adaxial and Abaxial Leaf Surfaces
Publisher: MDPI AG
Date: 15-09-2019
DOI: 10.3390/RS11182148
Abstract: Relatively little research has assessed the impact of spectral differences among dorsiventral leaves caused by leaf structure on leaf chlorophyll content (LCC) retrieval. Based on reflectance measured from peanut adaxial and abaxial leaves and LCC measurements, this study proposed a dorsiventral leaf adjusted ratio index (DLARI) to adjust dorsiventral leaf structure and improve LCC retrieval accuracy. Moreover, the modified Datt (MDATT) index, which was insensitive to leaves structure, was optimized for peanut plants. All possible wavelength combinations for the DLARI and MDATT formulae were evaluated. When reflectance from both sides were considered, the optimal combination for the MDATT formula was ( R 723 − R 738 ) / ( R 723 − R 722 ) with a cross-validation R2cv of 0.91 and RMSEcv of 3.53 μg/cm2. The DLARI formula provided the best performing indices, which were ( R 735 − R 753 ) / ( R 715 − R 819 ) for estimating LCC from the adaxial surface (R2cv = 0.96, RMSEcv = 2.37 μg/cm2) and ( R 732 − R 754 ) / ( R 724 − R 773 ) for estimating LCC from reflectance of both sides (R2cv = 0.94, RMSEcv = 2.81 μg/cm2). A comparison with published vegetation indices demonstrated that the published indices yielded reliable estimates of LCC from the adaxial surface but performed worse than DLARIs when both leaf sides were considered. This paper concludes that the DLARI is the most promising approach to estimate peanut LCC.
Scaling up spring phenology derived from remote sensing images
Publisher: Elsevier BV
Date: 06-2018
Normalization of multidirectional red and NIR reflectances with the SAVI
Publisher: Elsevier BV
Date: 08-1992
Relation between ERS‐1 synthetic aperture radar data and measurements of surface roughness and moisture content of rocky soils in a semiarid rangeland
Publisher: American Geophysical Union (AGU)
Date: 06-1998
DOI: 10.1029/98WR00032
Interrelationship among among MODIS vegetation products across an Amazon Eco-climatic gradient
Publisher: IEEE
Date: 2005
Vegetation Mapping for Change Detection on an Arid-Zone River
Publisher: Springer Science and Business Media LLC
Date: 10-2005
DOI: 10.1007/S10661-005-6285-Y
Abstract: A vegetation mapping system for change detection was tested at the Havasu National Wildlife Refuge (HNWR) on the Lower Colorado River. A low-cost, aerial photomosaic of the 4200 ha, study area was constructed utilizing an automated digital camera system, supplemented with oblique photographs to aid in determining species composition and plant heights. Ground-truth plots showed high accuracy in distinguishing native cottonwood (Populus fremontii) and willow (Salix gooddingii) trees from other vegetation on aerial photos. Marsh vegetation (mainly cattails, Typha domengensis) was also easily identified. However, shrubby terrestrial vegetation, consisting of saltcedar (Tamarix ramosissima), arrowweed (Pluchea sericea), and mesquite trees (Prosopis spp.), could not be accurately distinguished from each other and were combined into a single shrub layer on the final vegetation map. The final map took the form of a base, shrub and marsh layer, which was displayed as a Normalized Difference Vegetation Index map from a Landsat Enhanced Thematic Mapper (ETM+) image to show vegetation intensity. Native willow and cottonwood trees were digitized manually on the photomosaic and overlain on the shrub layer in a GIS. By contrast to present, qualitative mapping systems used on the Lower Colorado River, this mapping system provides quantitative information that can be used for accurate change detection. However, better methods to distinguish between saltcedar, mesquite, and arrowweed are needed to map the shrub layer.
Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence
Publisher: Proceedings of the National Academy of Sciences
Date: 25-03-2014
Abstract: Global food and biofuel production and their vulnerability in a changing climate are of paramount societal importance. However, current global model predictions of crop photosynthesis are highly uncertain. Here we demonstrate that new space-based observations of chlorophyll fluorescence, an emission intrinsically linked to plant biochemistry, enable an accurate, global, and time-resolved measurement of crop photosynthesis, which is not possible from any other remote vegetation measurement. Our results show that chlorophyll fluorescence data can be used as a unique benchmark to improve our global models, thus providing more reliable projections of agricultural productivity and climate impact on crop yields. The enormous increase of the observational capabilities for fluorescence in the very near future strengthens the relevance of this study.
A pilot forecasting system for epidemic thunderstorm asthma in south-eastern Australia
Publisher: American Meteorological Society
Date: 02-2020
Abstract: In November 2016, an unprecedented epidemic thunderstorm asthma event in Victoria, Australia, resulted in many thousands of people developing breathing difficulties in a very short period of time, including 10 deaths, and created extreme demand across the Victorian health services. To better prepare for future events, a pilot forecasting system for epidemic thunderstorm asthma (ETSA) risk has been developed for Victoria. The system uses a categorical risk-based approach, combining operational forecasting of gusty winds in severe thunderstorms with statistical forecasts of high ambient grass pollen concentrations, which together generate the risk of epidemic thunderstorm asthma. This pilot system provides the first routine daily epidemic thunderstorm asthma risk forecasting service in the world that covers a wide area, and integrates into the health, ambulance, and emergency management sector. Epidemic thunderstorm asthma events have historically occurred infrequently, and no event of similar magnitude has impacted the Victorian health system since. However, during the first three years of the pilot, 2017–19, two high asthma presentation events and four moderate asthma presentation events were identified from public hospital emergency department records. The ETSA risk forecasts showed skill in discriminating between days with and without health impacts. However, even with hindsight of the actual weather and airborne grass pollen conditions, some high asthma presentation events occurred in districts that were assessed as low risk for ETSA, reflecting the challenge of predicting this unusual phenomenon.
Seasonal landscape and spectral vegetation index dynamics in the Brazilian Cerrado: An analysis within the Large-Scale Biosphere–Atmosphere Experiment in Amazônia (LBA)
Publisher: Elsevier BV
Date: 11-2019
Monitoring vegetation phenology using MODIS
Publisher: Elsevier BV
Date: 03-2003
A Radiative Transfer Model for Heterogeneous Agro-Forestry Scenarios
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2016
Peer review report 1 On “Parameterizing ecosystem light use efficiency and water use efficiency to estimate maize gross primary production and evapotranspiration using MODIS EVI”
Publisher: Elsevier BV
Date: 2016
Peer review report 1 On “Parameterizing ecosystem light use efficiency and water use efficiency to estimate maize gross primary production and evapotranspiration using MODIS EVI”
Publisher: Elsevier BV
Date: 2016
Sunlight mediated seasonality in canopy structure and photosynthetic activity of Amazonian rainforests
Publisher: IOP Publishing
Date: 06-2015
A new wet reference target method for continuous infrared thermography of vegetations
Publisher: Elsevier BV
Date: 10-2016
Soil moisture controls on phenology and productivity in a semi-arid critical zone
Publisher: Elsevier BV
Date: 10-2016
DOI: 10.1016/J.SCITOTENV.2016.05.142
Abstract: The Earth's Critical Zone, where physical, chemical and biological systems interact, extends from the top of the canopy to the underlying bedrock. In this study, we investigated soil moisture controls on phenology and productivity of an Acacia woodland in semi-arid central Australia. Situated on an extensive sand plain with negligible runoff and drainage, the carry-over of soil moisture content (θ) in the rhizosphere enabled the delay of phenology and productivity across seasons, until conditions were favourable for transpiration of that water to prevent overheating in the canopy. Storage of soil moisture near the surface (in the top few metres) was promoted by a siliceous hardpan. Pulsed recharge of θ above the hardpan was rapid and depended upon precipitation amount: 150mm storm(-1) resulted in saturation of θ above the hardpan (i.e., formation of a temporary, discontinuous perched aquifer above the hardpan in unconsolidated soil) and immediate carbon uptake by the vegetation. During dry and inter-storm periods, we inferred the presence of hydraulic lift from soil storage above the hardpan to the surface due to (i) regular daily drawdown of θ in the reservoir that accumulates above the hardpan in the absence of drainage and evapotranspiration (ii) the dimorphic root distribution wherein most roots were found in dry soil near the surface, but with significant root just above the hardpan and (iii) synchronisation of phenology amongst trees and grasses in the dry season. We propose that hydraulic redistribution provides a small amount of moisture that maintains functioning of the shallow roots during long periods when the surface soil layer was dry, thereby enabling Mulga to maintain physiological activity without diminishing phenological and physiological responses to precipitation when conditions were favourable to promote canopy cooling.
Derivation of Soil Line Influence on Two-Band Vegetation Indices and Vegetation Isolines
Publisher: MDPI AG
Date: 03-11-2009
DOI: 10.3390/RS1040842
Mulga, a major tropical dry open forest of Australia: Recent insights to carbon and water fluxes
Publisher: IOP Publishing
Date: 12-2016
Predicting riparian evapotranspiration from MODIS vegetation indices and meteorological data
Publisher: Elsevier BV
Date: 2005
Leaf development and demography explain photosynthetic seasonality in Amazon evergreen forests
Publisher: American Association for the Advancement of Science (AAAS)
Date: 26-02-2016
Abstract: Models assume that lower precipitation in tropical forests means less plant-available water and less photosynthesis. Direct measurements in the Amazon, however, show that production remains constant or increases in the dry season. To investigate this mismatch, Wu et al. use tower-based cameras to detect the phenology (i.e., the seasonal patterns) of leaf dynamics in tropical tree crowns in Amazonia, Brazil, and relate this to patterns of CO 2 flux. Accounting for age-dependent variation among in idual leaves and crowns is necessary for understanding the seasonal dynamics of photosynthesis in the entire ecosystem. Leaf phenology regulates seasonality of the carbon flux in tropical forests across a gradient of climate zones. Science , this issue p. 972
Development of a two-band enhanced vegetation index without a blue band
Publisher: Elsevier BV
Date: 15-10-2008
A performance evaluation of the MODIS vegetation index compositing algorithm
Publisher: IEEE
Date: 2001
The impact of drought on urban green space
Publisher: Copernicus GmbH
Date: 28-03-2022
DOI: 10.5194/EGUSPHERE-EGU22-13187
Abstract: & & The role of water in shaping and developing cities has been known and referred to in numerous studies in the last two decades. Urban water management encounters compelling features, including rapid urban expansion and consequent demographic change, climate change, and environmental limitations. Urban green spaces bridge the relationship between humans and nature. As the major feature of green infrastructure, urban green space (UGS) has a crucial role in cities' human health and quality of life. UGS makes cities more habitable and promotes psychological and physical health by filtering air, enhancing water quality, reducing traffic noise, and adjusting wind speed, among other benefits. One of the most important features of urban greenery is its contribution to reducing urban heat islands and cooling the city. In order to attain a water-resilient city, we need to overcome challenges associated with water scarcity, such as drought events. While the impact of drought on forestry, agriculture, and riparian corridors has already been studied, this study is one of the first to assess the effect of drought on the UGS. The main objective of this study is to find a sustainable approach toward a green, livable city under climate change by optimizing the water footprint of UGS. As the third most liveable city in the world in 2021, Adelaide city was selected as the case study. The changes in greenness and water requirement of UGS in Greater Adelaide were studied to detect the impact of drought from 2000 to 2020. The optical remote sensing techniques were employed using Landsat, MODIS, and Sentinel images. The study area's greenness and ETa time series were simulated on the Google Earth Engine platform. Preliminary results show that the water footprint of Adelaide's urban green space is the highest in December with the highest rate of heat-wave and the lowest in June.& &
The agricultural potential of selected C4 plants in arid environments
Publisher: Elsevier BV
Date: 09-1984
Editorial: Building and delivering real-world, integrated sustainability solutions: Insights, methods and case-study applications
Publisher: Frontiers Media SA
Date: 26-02-2019
Fifty Years of Advances in Hyperspectral Remote Sensing of Agriculture and Vegetation—Summary, Insights, and Highlights of Volume III
Publisher: CRC Press
Date: 07-12-2018
Surface energy dynamics and canopy structural properties in intact and disturbed forests in the Southern Amazon
Publisher: Authorea, Inc.
Date: 09-03-2023
DOI: 10.22541/ESSOAR.167839947.73218884/V1
Abstract: The Brazilian Amazon has been a focus of land development with large swaths of forests converted to agriculture. Forest degradation by selective logging and fires has accompanied the advance of the frontier and has resulted in significant impacts on Amazonian ecosystems. Changes in forest structure resulting from forest disturbances have large impacts on the surface energy balance, including on land surface temperature (LST) and evapotranspiration (ET). The objective of this study is to assess the effects of forest disturbances on water fluxes and canopy structural properties in a transitional forest site located in Mato Grosso State, Southern Amazon. We used ET and LST products from MODIS and Landsat 8 as well as GEDI-derived forest structure data to address our research questions. We found that disturbances induced seasonal water stress, more pronounced and earlier in croplands and pastures than in forests, and more pronounced in second-growth and recently burned areas than in logged and intact forests. Moreover, we found that ET and LST were negatively related, with a more consistent relationship across disturbance classes in the dry season than the wet season, and that forest and cropland and pasture classes showed contrasting relationships in the dry season. Finally, we found that canopy structural properties exhibited moderate relationships with ET and LST in the most disturbed forests, but negligible correlations in the least disturbed forests. Our findings help to elucidate degraded forests functioning under a changing climate and to improve estimates of water and energy fluxes in the Amazon degraded forests.
Towards a remote sensing data based evapotranspiration estimation in Northern Australia using a simple random forest approach
Publisher: Elsevier BV
Date: 08-2021
Estimation of latent heat flux using satellite land surface temperature and a variational data assimilation scheme over a eucalypt forest savanna in Northern Australia
Publisher: Elsevier BV
Date: 04-2019
Functional differences between summer and winter season rain assessed with MODIS-derived phenology in a semi-arid region
Publisher: Wiley
Date: 02-2010
Retrieval Of Surface Physical Parameters With AVHRR And SMMR Over Africa
Publisher: IEEE
Date: 1993
Assessment of spectral vegetation indices for riparian vegetation in the Colorado River delta, Mexico
Publisher: Elsevier BV
Date: 09-2001
Enabling self-management of pollen allergies: a pre-season questionnaire evaluating the perceived benefit of providing local pollen information
Publisher: Springer Science and Business Media LLC
Date: 18-07-2019
Quality assurance of global vegetation index compositing algorithms using AVHRR data
Publisher: IEEE
Date: 1997
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University Of California, Berkeley
Location: United States of America
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End Date: 12-2014
Amount: $210,000.00
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View Funded ActivityDiscovery Projects - Grant ID: DP140102698
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End Date: 12-2017
Amount: $460,000.00
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View Funded ActivityDiscovery Projects - Grant ID: DP210100347
Start Date: 05-2021
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