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International Geoscience and Remote Sensing Symposium

In 2021 a joint initiative of Belgium and The Netherlands

TU1.O-20.5

Soil Organic Carbon modelling with Digital Soil Mapping and Remote sensing for permanently vegetated areas

Laura Poggio, Luis de Sousa, Giulio Genova, ISRIC World Soil Information, Netherlands; Pablo d'Angelo, Peter Schwind, Uta Heiden, German Aerospace Center (DLR), Germany
Session:
Hyperspectral Imaging for Soil Mapping and Monitoring
Track:
Invited Sessions
Presentation Time:
Tue, 13 Jul, 09:30-09:45 (UTC)
Tue, 13 Jul, 11:30-11:45 Central Europe Summer Time (UTC +2)
Tue, 13 Jul, 17:30-17:45 China Standard Time (UTC +8)
Tue, 13 Jul, 05:30-05:45 Eastern Daylight Time (UTC -4)
Session Co-Chairs:
Bas Van Wesemael, Université catholique de Louvain and Sabine Chabrillat, Helmholtz-Zentrum Potsdam—Deutsches GeoForschungsZentrum GFZ
Session Manager:
chengzhe Li
Presentation
Discussion
Resources
Session TU1.O-20
TU1.O-20.1: Estimation of field scale topsoil properties of agronomic interest from PRISMA imaging spectrometer data
Raffaele Casa, Massimo Tolomio, Nada Mzid, University of Tuscia, Italy; Stefano Pignatti, Simone Pascucci, National Research Council (CNR), Italy
TU1.O-20.3: CROPLAND TOPSOIL PROPERTIES MAPPING BY APPLYING A MACHINE LEARNING ALGORITHM TO OPEN ACCESS COPERNICUS DATA
Nikolaos Tziolas, Nikolaos Tsakiridis, George Zalidis, Aristotle University Of Thessaloniki, Greece
TU1.O-20.4: ANALYSIS OF SENSITIVE SPECTRAL CHARACTERISTICS OF FARMLAND SOIL ORGANIC MATTER CONTENT BASED ON AHSI/ZY1-02D DATA
Yayu Yang, Kun Shang, Land Satellite Remote Sensing Application Center, Ministry of Natural Resources of China, China; Yuanjin Xu, China University of Geosciences, China
TU1.O-20.5: Soil Organic Carbon modelling with Digital Soil Mapping and Remote sensing for permanently vegetated areas
Laura Poggio, Luis de Sousa, Giulio Genova, ISRIC World Soil Information, Netherlands; Pablo d'Angelo, Peter Schwind, Uta Heiden, German Aerospace Center (DLR), Germany
TU1.O-20.6: Evaluating Soil Reflectance Composites generated by SCMaP using different Sentinel-2 reflectance data inputs
Uta Heiden, Pablo d'Angelo, Peter Schwind, Raquel de los Reyes Lopez, Rupert Mueller, DLR Oberpfaffenhofen, Remote Sensing Technology Institute, Germany

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