A: Soil moisture (volumetric) map from SAR data. B: NDVI Image (biomass) from optical data

Knowledge of soil moisture enhances our understanding of the hydrologic cycle and plant-water-soil relations. Applying this information on agricultural production sites can increase the effectiveness of water use in fields. SBI aims to achieve significant progress by applying different methods to SAR (Synthetic Aperture Radar) data processing. This includes interferometry (InSAR) in particular and amplitude analysis, as well as refining the results through using the information obtained from optical satellite images and agricultural parameters.

The soil moisture of the agricultural fields is detected by using X- and C-band SAR data provided by high spatial resolution images from TerraSAR–X, RADARSAT-2 and Sentinel-1. From optical satellite images, like those from RapidEye, vegetation indices are derived and applied for correcting influences coming from biomass which covers the soil and effects the soil moisture estimations.

Our methods for interpreting the satellite images for soil moisture are proven by data from in-situ surveys of soil and plant characteristics. The feasibility of customized products is tested by integrating the soil moisture data acquired into models, e.g., for the purpose of analyzing water availability and drought risks for crops. A part of the project incorporates customer requirements and involves the preparation of the production processes.

The project is conducted by Spatial Business Integration GmbH and TRE Canada Inc., bringing together the expertise on space born agricultural surveys using optical and radar data and the experiences of interferometry in space born radar applications. The project is funded by the German (DLR) and Canadian Space Agencies (CSA).