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Comprehensive evaluation of soil moisture retrieval models under different crop cover types using C-band synthetic aperture radar data
Authors:P Kumar  A Choudhary  D K Gupta  V N Mishra  A K Vishwakarma
Institution:1. Department of Physics, Institute of Science, Banaras Hindu University, Varanasi, India;2. Environmental Science Division, Central Road Research Institute, New Delhi, India;3. Department of Physics, Indian Institute of Technology (BHU), Varanasi, India
Abstract:In the present study, random forest regression (RFR), support vector regression (SVR) and artificial neural network regression (ANNR) models were evaluated for the retrieval of soil moisture covered by winter wheat, barley and corn crops. SVR with radial basis function kernel was provided the highest adj. R2 (0.95) value for soil moisture retrieval covered by the wheat crop at VV polarization. However, RFR provided the adj. R2 (0.94) value for soil moisture retrieval covered by barley crop at VV polarization using Sentinel-1A satellite data. The adj. R2 (0.94) values were found for the soil moisture covered by corn crop at VV polarization using RFR, SVR linear and radial basis function kernels. The least performance was reported using ANNR model for almost all the crops under investigation. The soil moisture retrieval outcomes were found better at VV polarization in comparison to VH polarization using three different models.
Keywords:Sentinel-1A  RFR  SVR  ANNR  soil moisture
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