Cereal crops soil parameters retrieval using L-Band ALOS-2 and C-Band Sentinel-1 sensors

International audienceThis paper discusses the potential of L-band Advanced Land Observing Satellite-2 (ALOS-2) and C-band Sentinel-1 radar data for retrieving soil parameters over cereal fields. For this purpose,multi-incidence, multi-polarization and dual-frequency satellite data were acquired simultaneouslywith in situ measurements collected over a semiarid area, the Merguellil Plain (central Tunisia). TheL- and C-band signal sensitivity to soil roughness, moisture and vegetation was investigated. Highcorrelation coefficients were observed between the radar signals and soil roughness values for allprocessed multi-configurations of ALOS-2 and Sentinel-1 data. The sensitivity of SAR (SyntheticAperture Radar) data to soil moisture was investigated for three classes of the normalized differencevegetation index (NDVI) (low vegetation cover, medium cover and dense cover), illustrating adecreasing sensitivity with increasing NDVI values. The highest sensitivity to soil moisture underthe dense cover class is observed in L-band data. For various vegetation properties (leaf area index(LAI), height of vegetation cover (H) and vegetation water content (VWC)), a strong correlation isobserved with the ALOS-2 radar signals (in HH(Horizontal-Horizontal) and HV(Horizontal-Vertical)polarizations). Different empirical models that link radar signals (in the L- and C-bands) to soilmoisture and roughness parameters, as well as the semi-empirical Dubois modified model (Dubois-B)and the modified integral equation model (IEM-B), over bare soils are proposed for all polarizations.The results reveal that IEM-B performed a better accuracy comparing to Dubois-B. This analysisis also proposed for covered surfaces using different options provided by the water cloud model(WCM) (with and without the soil–vegetation interaction scattering term) coupled with the bestaccuracy bare soil backscattering models: IEM-B for co-polarization and empirical models for theentire dataset. Based on the validated backscattering models, different options of coupled models aretested for soil moisture inversion. The integration of a soil–vegetation interaction component in theWCM illustrates a considerable contribution to soil moisture precision in the HV polarization modein the L-band frequency and a neglected effect on C-band data inversion