Adaptation of Oh Model for Soil Parameters Retrieval Using Multi-Angular RADARSAT-2 Datasets

Hongquan Wang (1) , Stéphane Méric (1) , Sophie Allain (1) , Eric Pottier (1)

1 IETR - Institut d'Électronique et des Technologies du numéRique

The global context of this study is to improve the robustness of surface geophysical parameter retrieval models. Consequently, the adaptation of the existing retrieval models to radar measurement datasets is very important regarding the improvement of soil parameter retrieval procedures. In this context, the objective of this paper is to empirically adapt the Oh model based on the polarimetric RADARSAT-2 datasets acquired at different incidence angles, along with the simultaneous ground truth. The coefficients in the Oh model are adapted in order to decrease the deviation between Oh model predictions and SAR measurements. Improved agreements are found between the adapted Oh model and backscattering coefficients derived from multi-angular (ranged from 24° to 43°) SAR data. This indicates that the model adaptation could provide a way to improve the model behaviours and enhance the geophysical parameter retrieval.

Mots clés: -Multi-angular Measurements; RADARSAT-2 Datasets; Oh Model; Surface Roughness; Soil Moisture

Domaines: Electronique

Hongquan Wang, Stéphane Méric, Sophie Allain, Eric Pottier. Adaptation of Oh Model for Soil Parameters Retrieval Using Multi-Angular RADARSAT-2 Datasets. Journal of Surveying and Mapping Engineering, 2014, 2 (4), pp.65-74. ⟨hal-01127973⟩