Ouaadi N., Jarlan Lionel, Ezzahar J., Zribi M., Khabba S., Bouras E., Frison Pierre-Louis. (2020). Surface soil moisture retrieval over irrigated wheat crops in semi-arid areas using sentinel-1 data. In :
2020 Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS). Pïscataway : IEEE, 212-215. M2GARSS.Mediterranean and Middle-East Geoscience and Remote Sensing Symposium, TUNIS (TUN), 2020/03/09-11. ISBN 978-1-7281-2191-8.
Titre du document
Surface soil moisture retrieval over irrigated wheat crops in semi-arid areas using sentinel-1 data
Ouaadi N., Jarlan Lionel, Ezzahar J., Zribi M., Khabba S., Bouras E., Frison Pierre-Louis
In
2020 Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS)
Source
Pïscataway : IEEE, 2020,
212-215 ISBN 978-1-7281-2191-8
Colloque
M2GARSS.Mediterranean and Middle-East Geoscience and Remote Sensing Symposium, TUNIS (TUN), 2020/03/09-11
The sensitivity of the backscattering coefficient and the interferometric coherence to surface soil moisture changes and wheat crops growth was analyzed using the time series derived from C-band Sentinel-1. Results show that the interferometric coherence is sensitive to wheat biomass while the backscatter intensity is more influenced by the surface soil moisture (SSM) changes. A new method to retrieve SSM combining the interferometric coherence and C-band backscattering coefficient acquired by Sentinel-1 is tested over two irrigated wheat plots during two growth seasons around Marrakech city (center of Morocco). It is shown that SSM can be estimated with a reasonable accuracy from sowing to harvest (R=0.65; RMSE =0.07m3/m3; bias =0.01m3/m3). These results enhance the potentialities of Sentinel1 data for SSM retrieval even in the presence of a dense canopy
Plan de classement
Pédologie [068]
;
Sciences du monde végétal [076]
;
Télédétection [126]
