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Title: | Semi-empirical model for retrieval of soil moisture using RISAT-1 C-Band SAR data over a sub-tropical semi-arid area of Rewari district, Haryana (India) |
Other Titles: | Not Available |
Authors: | Kishan Singh Rawat Vinay Kumar Sehgal Sanatan Pradhan Shibendu S. Ray |
ICAR Data Use Licennce: | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf |
Author's Affiliated institute: | ICAR::Indian Agricultural Research Institute Sathyabama University Mahalanobis National Crop Forecast Centre |
Published/ Complete Date: | 2018-03-02 |
Project Code: | Not Available |
Keywords: | Remote Sensing Microwave Soil water RISAT |
Publisher: | Springer |
Citation: | Rawat, K.S., Sehgal, V.K., Pradhan, S. et al. Semi-empirical model for retrieval of soil moisture using RISAT-1 C-Band SAR data over a sub-tropical semi-arid area of Rewari district, Haryana (India). J Earth Syst Sci 127, 18 (2018). https://doi.org/10.1007/s12040-018-0919-2 |
Series/Report no.: | Not Available; |
Abstract/Description: | We have estimated soil moisture (SM) by using circular horizontal polarization backscattering coefficient (σoRH), differences of circular vertical and horizontal σo(σoRV−σoRH) from FRS-1 data of Radar Imaging Satellite (RISAT-1) and surface roughness in terms of RMS height (RMSheight). We examined the performance of FRS-1 in retrieving SM under wheat crop at tillering stage. Results revealed that it is possible to develop a good semi-empirical model (SEM) to estimate SM of the upper soil layer using RISAT-1 SAR data rather than using existing empirical model based on only single parameter, i.e., σo. Near surface SM measurements were related to σoRH, σoRV−σoRH derived using 5.35 GHz (C-band) image of RISAT-1 and RMSheight. The roughness component derived in terms of RMSheight showed a good positive correlation with σoRV−σoRH(R2=0.65). By considering all the major influencing factors (σoRH, σoRV−σoRH, and RMSheight), an SEM was developed where SM (volumetric) predicted values depend on σoRH, σoRV−σoRH, and RMSheight. This SEM showed R2 of 0.87 and adjusted R2 of 0.85, multiple R=0.94 and with standard error of 0.05 at 95% confidence level. Validation of the SM derived from semi-empirical model with observed measurement (SMObserved) showed root mean square error (RMSE) = 0.06, relative-RMSE (R-RMSE) = 0.18, mean absolute error (MAE) = 0.04, normalized RMSE (NRMSE) = 0.17, Nash–Sutcliffe efficiency (NSE) = 0.91 (≈1), index of agreement (d) = 1, coefficient of determination (R2)=0.87, mean bias error (MBE) = 0.04, standard error of estimate (SEE) = 0.10, volume error (VE) = 0.15, variance of the distribution of differences (S2d)=0.004. The developed SEM showed better performance in estimating SM than Topp empirical model which is based only on σo. By using the developed SEM, top soil SM can be estimated with low mean absolute percent error (MAPE) = 1.39 and can be used for operational applications. |
Description: | Not Available |
ISSN: | Not Available |
Type(s) of content: | Research Paper |
Sponsors: | Not Available |
Language: | English |
Name of Journal: | Journal of Earth System Science (Proceedings of the Indian Academy of Sciences - Earth and Planetary Science) |
NAAS Rating: | 7.42 |
Volume No.: | 127(2) |
Page Number: | 1-11 |
Name of the Division/Regional Station: | Division of Agricultural Physics |
Source, DOI or any other URL: | https://doi.org/10.1007/s12040-018-0919-2 |
URI: | http://krishi.icar.gov.in/jspui/handle/123456789/34469 |
Appears in Collections: | CS-IARI-Publication |
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