<> "The repository administrator has not yet configured an RDF license."^^ . <> . . . "Accuracies of Soil Moisture Estimations Using a Semi-Empirical Model over Bare Soil Agricultural Croplands from Sentinel-1 SAR Data"^^ . "This study describes a semi-empirical model developed to estimate volumetric soil\r\nmoisture ( v\r\nϑ) in bare soils during the dry season (March–May) using C-band (5.42 GHz) synthetic\r\naperture radar (SAR) imagery acquired from the Sentinel-1 European satellite platform at a 20 m\r\nspatial resolution. The semi-empirical model was developed using backscatter coefficient (σ° dB)\r\nand in situ soil moisture collected from Siruguppa taluk (sub-district) in the Karnataka state of\r\nIndia. The backscatter coefficients 0\r\nVV σ and 0\r\nVH σ were extracted from SAR images at 62\r\ngeo-referenced locations where ground sampling and volumetric soil moisture were measured at a\r\n10 cm (0–10 cm) depth using a soil core sampler and a standard gravimetric method during the dry\r\nmonths (March–May) of 2017 and 2018. A linear equation was proposed by combining 0\r\nVV σ and\r\n0\r\nVH σ to estimate soil moisture. Both localized and generalized linear models were derived.\r\nThirty-nine localized linear models were obtained using the 13 Sentinel-1 images used in this\r\nstudy, considering each polarimetric channel Co-Polarization (VV) and Cross-Polarization(VH)\r\nseparately, and also their linear combination of VV + VH. Furthermore, nine generalized linear\r\nmodels were derived using all the Sentinel-1 images acquired in 2017 and 2018; three generalized\r\nmodels were derived by combining the two years (2017 and 2018) for each polarimetric channel;\r\nand three more models were derived for the linear combination of 0\r\nVV σ and 0\r\nVH σ . The above set of\r\nequations were validated and the Root Mean Square Error (RMSE) was 0.030 and 0.030 for 2017 and\r\n2018, respectively, and 0.02 for the combined years of 2017 and 2018. Both localized and\r\ngeneralized models were compared with in situ data. Both kind of models revealed that the linear\r\ncombination of 0\r\nVV σ + 0\r\nVH σ showed a significantly higher R2 than the individual polarimetric\r\nchannels."^^ . "2020-05" . . . "12" . "10" . . "MDPI"^^ . . . "Remote Sensing (TSI)"^^ . . . "20724292" . . . . . . . . . . . . . . . . "M"^^ . "Irshad Ahmed"^^ . "M Irshad Ahmed"^^ . . "G"^^ . "Nico"^^ . "G Nico"^^ . . "A M"^^ . "Whitbread"^^ . "A M Whitbread"^^ . . "H"^^ . "Anil Kumar"^^ . "H Anil Kumar"^^ . . . . . . "Accuracies of Soil Moisture Estimations Using a Semi-Empirical Model over Bare Soil Agricultural Croplands from Sentinel-1 SAR Data (PDF)"^^ . . . . . "remotesensing-12-01664 (1).pdf"^^ . . . "Accuracies of Soil Moisture Estimations Using a Semi-Empirical Model over Bare Soil Agricultural Croplands from Sentinel-1 SAR Data (Other)"^^ . . . . . . "indexcodes.txt"^^ . . "HTML Summary of #11513 \n\nAccuracies of Soil Moisture Estimations Using a Semi-Empirical Model over Bare Soil Agricultural Croplands from Sentinel-1 SAR Data\n\n" . "text/html" . . . "Remote Sensing"@en . . . "GIS Techniques/Remote Sensing"@en . . . "Soil Science"@en . .