ORCID Profile
0000-0001-8600-5168
Current Organisations
Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences
,
Leibniz Universität Hannover
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Publisher: Hindawi Limited
Date: 2013
DOI: 10.1155/2013/616578
Publisher: Elsevier BV
Date: 06-2015
Publisher: MDPI AG
Date: 11-10-2019
DOI: 10.3390/RS11202356
Abstract: In the face of rapid global change it is imperative to preserve geo ersity for the overall conservation of bio ersity. Geo ersity is important for understanding complex biogeochemical and physical processes and is directly and indirectly linked to bio ersity on all scales of ecosystem organization. Despite the great importance of geo ersity, there is a lack of suitable monitoring methods. Compared to conventional in-situ techniques, remote sensing (RS) techniques provide a pathway towards cost-effective, increasingly more available, comprehensive, and repeatable, as well as standardized monitoring of continuous geo ersity on the local to global scale. This paper gives an overview of the state-of-the-art approaches for monitoring soil characteristics and soil moisture with unmanned aerial vehicles (UAV) and air- and spaceborne remote sensing techniques. Initially, the definitions for geo ersity along with its five essential characteristics are provided, with an explanation for the latter. Then, the approaches of spectral traits (ST) and spectral trait variations (STV) to record geo ersity using RS are defined. LiDAR (light detection and ranging), thermal and microwave sensors, multispectral, and hyperspectral RS technologies to monitor soil characteristics and soil moisture are also presented. Furthermore, the paper discusses current and future satellite-borne sensors and missions as well as existing data products. Due to the prospects and limitations of the characteristics of different RS sensors, only specific geotraits and geo ersity characteristics can be recorded. The paper provides an overview of those geotraits.
Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-8988
Abstract: & & In the frame of the science preparation activities for the upcoming German hyperspectral satellite mission EnMAP, an airborne survey took place in September 2019 with hyperspectral VNIR-SWIR-LWIR data using the HySpex sensor and the newly acquired Hyper-Cam LWIR camera from the GeoResearch Center Potsdam (GFZ) mounted on the airborne platform Cessna-T207A from the Free University Berlin (FUB). Although logistically complex conditions with several teams distributed in different locations, all the sites in central and northern Greece could be successfully acquired under clear sky conditions, and all data could be demilitarized providing 45 flight stripes covering a total area of 300 km& sup& & /sup& .& & & & This abstract is focusing on the Amyntaio soil site in northern Greece, an agricultural area of variable soil composition from carbonate rich to clay/silt content to organic carbon rich fields around the lignite mine south of the area, over which 11 flight stripes could be acquired. The science goals of the Amyntaio soil c aign were: (a) Simulation of hyperspectral satellite imagery and demonstration of the potential of upcoming spaceborne hyperspectral sensors (EnMAP, CHIME) for global soil mapping and monitoring (b) Large test and validation for existing soil algorithms such as the HYSOMA / ENSOMAP software tools for the prediction of top-soil quantitative surface properties (c) Data validation and comparison of soil products with recent relevant satellite sensors (e.g. S2, PRISMA, ECOSTRESS) (d) Enlargement of global soil spectral libraries with harmonised standards and testbed for their use as calibration-validation data for soil spectral models.& & & & Simultaneous to the airborne survey, an intensive ground-based c aign took place in the area focusing on the acquisition of soil data, VNIR-SWIR and LWIR in-situ data with field spectroradiometers (PSR+, ASD FieldSpec3, MEMS, Handheld FTIR), fractional vegetation cover with RGB and UAV RGB data, soil moisture, infiltrometer and spectral data in undisturbed soil crust with the SoilPRO device, and Cal-Val data acquisition at the same time than the overflight (Temperature-loggers, ASD VNIR-SWIR, handheld FTIR) over bare soils and black/white thermal targets.& & & & We present the project objectives, selected field, airborne, satellite data, with preliminary analyses that show the high data quality and the potential of multi hyperspectral airborne c aigns as a support for basic science developments and satellite mission preparations. The results represent how more sensor flexibility can bridge the gap from in-situ to satellite scale. Further airborne flights and carefully designed in situ c aigns will allow testing and iterative improvement of new observational modalities for soil monitoring based on the integrated information from satellite platforms with the one provided by in-situ systems on the ground and air.& &
Publisher: Elsevier BV
Date: 08-2021
Publisher: Unpublished
Date: 2014
Publisher: MDPI AG
Date: 24-10-2012
DOI: 10.3390/RS4113265
Publisher: MDPI AG
Date: 18-12-0012
DOI: 10.3390/RS14061459
Abstract: There was an error in the original publication [...]
Publisher: Hindawi Limited
Date: 20-01-2023
DOI: 10.1155/2023/4155390
Abstract: Soil spectral libraries (SSLs) are important big-data archives (spectra associated with soil properties) that are analyzed via machine-learning algorithms to estimate soil attributes. Since different spectral measurement protocols are applied when constructing SSLs, it is necessary to examine harmonization techniques to merge the data. In recent years, several techniques for harmonization have been proposed, among which the internal soil standard (ISS) protocol is the most largely applied and has demonstrated its capacity to rectify systematic effects during spectral measurements. Here, we postulate that a spectral transfer function (TF) can be extracted between existing (old) SSLs if a subset of s les from two (or more) different SSLs are remeasured using the ISS protocol. A machine-learning TF strategy was developed, assembling random forest (RF) spectral-based models to predict the ISS spectral condition using soil s les from two existing SSLs. These SSLs had already been measured using different protocols without any ISS treatment the Brazilian (BSSL, generated in 2019) and the European (LUCAS, generated in 2009–2012) SSLs. To verify the TF’s ability to improve the spectral assessment of soil attributes after harmonizing the different SSLs’ protocols, RF spectral-based models for estimating organic carbon (OC) in soil were developed. The results showed high spectral similarities between the ISS and the ISS–TF spectral observations, indicating that post-ISS rectification is possible. Furthermore, after merging the SSLs with the TFs, the spectral-based assessment of OC was considerably improved, from R2 = 0.61, RMSE (g/kg) = 12.46 to R2 = 0.69, RMSE (g/kg) = 11.13. Given our results, this paper enhances the importance of soil spectroscopy by contributing to analyses in remote sensing, soil surveys, and digital soil mapping.
Location: Germany
No related grants have been discovered for Sabine Chabrillat.