Clay Content Mapping Using Soil Moisture Products Derived From a Synergetic Use of Sentinel-1 and Sentinel-2 Data
2020
Bousbih, Safa | Zribi, Mehrez | Chabaane, Zohra Lili | Baghdadi, Nicolas | Gorrab, Azza | Ben Aissa, Nadhira | Centre d'études spatiales de la biosphère (CESBIO) ; Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3) ; Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Université de Carthage (Tunisie) = University of Carthage (UCAR) | Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | TOSCA/CNES TAPAS - ERANET-MED 03-62 CHAAMS
International audience
Show more [+] Less [-]English. This study aimed to explore the potential of Sentinel satellites to predict topsoil texture, and more precisely to produce clay content map at fine spatial resolution. With its components and its porosity, soil texture is directly linked to soil moisture. In this context and with the arrival of Sentinel constellation, data are acquired with high spatial and temporal resolution. And soil moisture is retrieved from a synergetic use of Sentinel-1 (S-1) and Sentinel-2 (S-2) data between July and early December 2017, over a semi-arid area in central Tunisia. Relationship between soil moisture and clay content is studied and used to produce texture map.Classification algorithm based on random forest (RF) is used for the mapping of clay content classes. The results showed the potential of S-1 and S-2 products to predict soil texture.
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