{"type": "FeatureCollection", "features": [{"id": "10.1109/lgrs.2021.3073484", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:19:15Z", "type": "Journal Article", "created": "2021-06-10", "title": "Sentinel-1 Backscatter Assimilation Using Support Vector Regression or the Water Cloud Model at European Soil Moisture Sites", "description": "Sentinel-1 backscatter observations were assimilated into the Global Land Evaporation Amsterdam Model (GLEAM) using an ensemble Kalman filter. As a forward operator, which is required to simulate backscatter from soil moisture and leaf area index (LAI), we evaluated both the traditional water cloud model (WCM) and the support vector regression (SVR). With SVR, a closer fit between backscatter observations and simulations was achieved. The impact on the correlation between modeled and in situ soil moisture measurements was similar when assimilating the Sentinel data using WCM (\u0394 R = +0.037) or SVR (\u0394 R = +0.025).", "keywords": ["Vegetation mapping", "support vector regression (SVR)", "Technology and Engineering", "Data models", "0211 other engineering and technologies", "Computational modeling", "02 engineering and technology", "15. 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Trento-Bolzano (Italy), 3-5 Nov. 2021. A good understanding of soil moisture spatial patterns is useful for assessing the hydrological connectivity and runoff generation processes in a catchment. Thus, we have applied numerical modelling approaches to investigate the spatial patterns of soil moisture at the Nu\u010dice experimental catchment (0.531 km 2 ) in the Czech Republic. The catchment was established in 2011 to observe the rainfall-runoff processes, soil erosion and water balance in an agricultural landscape. The catchment consists of three fields covering over 95 % of the area. Eight field surveys were conducted to capture the soil moisture patterns at different scales. Even though the soil management and soil properties in the fields of Nu\u010dice seem to be nearly homogeneous, we have observed spatial variability in topsoil moisture. In numerical simulations, a 3D spatially-distributed model MIKE-SHE was used to simulate the water movement within the catchments. The MIKE-SHE simulation has been mainly calibrated with rainfall-runoff observations and point-scale soil moisture data. In the simulation, we have obtained the spatial patterns of soil moisture at each time step. The soil moisture spatial patterns from the simulation have been compared with the density of the vegetation cover (NDVI), and topsoil moisture patterns from field surveys. We found that the density of vegetation cover has a good correlation with the soil moisture spatial distribution. However, this correlation was not captured in the MIKE-SHE simulation. Future research will include Cosmic-ray neutron sensing and stable isotope analysis to improve the current understanding of the catchment. Peer reviewed", "keywords": ["Vegetation mapping", "13. Climate action", "Solid modeling", "0207 environmental engineering", "Three-dimensional displays", "Soil moisture", "Soil properties", "02 engineering and technology", "15. Life on land", "Moisture", "6. 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