Combining crop model and remote sensing data at high resolution for the assessment of rice agricultural practices in the South-Eastern France (take 5 experiment SPOT4-SPOT5)

Crop systems are constantly changing due to modifications in the agricultural practices to respond to market changes, the constraints of the environment, the climate hazards... Rice cultivation practiced in the Camargue region (SE France) have decreased these last years, however rice plays a crucial role for the hydrological balance of the region and for crop systems desalinizing soils. The aim of this study is to analyze the potentialities of remote sensing data acquired at high spatial and temporal resolution (HRST) to identify the main agricultural practices and estimate their impact on rice production. A large dataset acquired over the Camargue from the Take5 experiment (SPOT4 in 2013 and SPOT5 in 2015), completed by Landsat data has been used. Two assimilation methods of HRST data were evaluated within a crop model. Results showed the impact of the spatial variability of practices on the yields. The sowing dates were retrieved from inverse procedures and gave satisfactory results compared to ground surveys.