Case studies on the retrieval and classification of agricultural parameters

To promote the efficient and fruitful use of water, land, and energy in sustainable agriculture, knowledge and sophisticated management are required. Earth observation (EO) products with high spatial and temporal resolution have been useful in observing agricultural processes and assisting effective management. They will support the shift to green agriculture when included in sophisticated environmental management frameworks. To gain widespread acceptance, it is, however, crucial to constantly check their accuracy and make use of supplementary data sources. In the presentation, a few case studies involving the use of multi-frequency SAR data to map and monitor the spatial and temporal variability of land surface parameters and agricultural operations will be used as examples. The emphasis is on assessing algorithms for the retrieval of surface soil moisture (SSM) and vegetation water content (VWC), classification, and monitoring of irrigation extent and tillage practices at high resolution. The approach of the algorithms is based on incoherent and coherent change detection. Results indicate that high spatial and temporal resolution interleaved SSM products can be produced by combining C- and L-band SAR data. They also showed great potential for tillage classification at large scales. Additionally, for the classification of irrigated areas, a useful complementarity between SAR and optical multi-spectral data has evolved. SAR data, in particular, can offer accurate early projections of the extent of irrigated areas.