Exploiting big geodata in the context of soil moisture retrieval on large areas: the case of the SMOSAR system and SM-Tools

Gridded soil moisture (SM) observations play a crucial role in understanding the hydrologic cycle and in agricultural monitoring. High-resolution (0.1 - 1.0 km) SM products can be derived from Copernicus Sentinel-1 (S-1) Synthetic Aperture Radar (SAR) data that are systematically acquired at a global scale. This paper describes the SM-Tools software framework developed and used over the last ten years to support the scaling up the application of the "Soil moisture retrieval from multi-temporal SAR data" (SMOSAR) code developed at CNR for the SM retrieval. The SM-Tools also support the calibration and validation of the SAR SM products. Besides, the paper introduces the challenges and opportunities that the development of downstream prototype services poses.