Titlebook: Geospatial Technologies for Resources Planningand Management; Chandra Shekhar Jha,Ashish Pandey,Vijay Singh Book 2022 The Editor(s) (if ap

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Water Quality Assessment from Medium Resolution Satellite Data Using Machine Learning Methods,s especially using band ratio methods, they need accurate spectral and specific absorption characteristics which are challenging to obtain for many inland water bodies. Machine learning algorithms, on the other hand can statistically derive the spatio-temporal distribution of chlorophyll-a and suspe

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Soil Penetration Depth of RISAT-1 C-Band and PALSAR-2 L-Band Sensors in Arid Zone of Rajasthan, Ind (~16 cm) than the moist soil inside the PC. It has been observed that soil penetration depth with C- and L-bands gradually decreases from surface to a depth of 120 cm in both the pits, which are commensurate with the measured soil moisture and derived dielectric coefficient (.) or backscattering co

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Yield Estimation of Rice Crop Using Semi-Physical Approach and Remotely Sensed Data,olution) microwave data through Sentinel-1 Toolbox “SNAP”, the accuracy of crop map was assessed with geotagged ground truth. Pixel level estimates were developed and accumulated at the district level using an area-weighted approach. The estimated yield was compared with the actual estimate obtained

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Satellite-Based Terrestrial Evapotranspiration Product for India,pplications. This chapter discusses the different methods of deriving the ET and the justification for adopting the Priestley Taylor algorithm. It also describes the methodology of deriving the terrestrial ET in a near real-time basis and discusses the intra-seasonal dynamics and comparison with the