Speaker
Description
For the first time, the Copernicus Programme of the European Union provides access to valuable satellite Earth Observation data and dedicated services for the interested public free of charge. The satellites Sentinel-1 and 2 offer extensive sets of microwave and optical data at least until the year 2030. This guaranteed long-term availability enables the development of value-added information products for the public administration.
The project SenThiS (Sentinels for Thuringian Information Systems) has been funded by the German Federal Ministry of Transport and Digital Infrastructure (funding codes 50EW1512 and 50EW1513). It links two state authorities of the Free State of Thuringia, Germany, the Thuringian State Agency of Environment and Geology and the Thuringian Forest Administration (institution under public law) with two SMEs, the Earth Observation Services GmbH and Feiffer consult. These project partners were investigating the information potential of Sentine-1 and 2 for the two state authorities for different use cases.
One of these use cases is soil moisture, being an important variable in the hydrologic cycle. It controls the partitioning of precipitation into infiltration and surface-runoff and are an essential component of precipitation-runoff models used for flood forecasting.
The SAR sensor of Sentinel-1 is operating at C-band in the microwave region of the electromagnetic spectrum. A multitude of publications proofed the sensitivity of SAR data for soil moisture. One approach for extracting surface soil moisture related information from SAR data is the use of change-detection models. Here it is assumed that the environmental factors controlling radar backscatter are acting on different temporal scales. Short-term changes in the range of hours to a few days are addressed to soil moisture changes. If a sufficient number of SAR data sets is available, a change detection model can be developed to describe the temporal evolution of the SAR data on a pixel-by-pixel basis. Over time, a minimum and maximum radar backscatter level can be estimated, which are related to wilting level and field capacity. Once these two levels are known, each radar backscatter measurement can be scaled between these values to yield a relative surface soil moisture value. To mask out areas for which a soil moisture retrieval is not meaningful (e.g. forests, settlements, water surfaces), a land cover map has been produced from optical Sentinel-2 data. The surface soil moisture data, generated by the Earth Observation Services GmbH, are then transferred to the Thuringian State Agency of Environment and Geology, where they have been used to feed a precipitation-runoff model. Overall, a good agreement with modelled data has been found. Nevertheless, there are environmental phenomena like dew have been found to be problematic for soil moisture retrieval.
In conclusion, it can be stated that surface soil moisture information can be extracted from Sentinel-1 SAR data and are of great value for hydrologic modelling.
