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Remote Sens. 2015, 7(6), 8128-8153; doi:10.3390/rs70608128

Retrieval and Multi-scale Validation of Soil Moisture from Multi-temporal SAR Data in a Semi-Arid Tropical Region

1
Centre d'Etudes Spatiales de la Biosphere (CESBIO), 31400 Toulouse, France
2
Department of Civil Engineering, Indian Institute of Science, Bangalore 560012, India
3
Indian Space Research Organization, Bangalore 560097, India
4
LETG Rennes Costel, UMR 6554 CNRS, 350043 Rennes, France
*
Author to whom correspondence should be addressed.
Academic Editors: Nicolas Baghdadi and Prasad S. Thenkabail
Received: 25 February 2015 / Revised: 4 June 2015 / Accepted: 11 June 2015 / Published: 18 June 2015
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Abstract

The current study presents an algorithm to retrieve surface Soil Moisture (SM) from multi-temporal Synthetic Aperture Radar (SAR) data. The developed algorithm is based on the Cumulative Density Function (CDF) transformation of multi-temporal RADARSAT-2 backscatter coefficient (BC) to obtain relative SM values, and then converts relative SM values into absolute SM values using soil information. The algorithm is tested in a semi-arid tropical region in South India using 30 satellite images of RADARSAT-2, SMOS L2 SM products, and 1262 SM field measurements in 50 plots spanning over 4 years. The validation with the field data showed the ability of the developed algorithm to retrieve SM with RMSE ranging from 0.02 to 0.06 m3/m3 for the majority of plots. Comparison with the SMOS SM showed a good temporal behaviour with RMSE of approximately 0.05 m3/m3 and a correlation coefficient of approximately 0.9. The developed model is compared and found to be better than the change detection and delta index model. The approach does not require calibration of any parameter to obtain relative SM and hence can easily be extended to any region having time series of SAR data available. View Full-Text
Keywords: soil moisture; SAR; multi-temporal; CDF; RADARSAT-2; SMOS soil moisture; SAR; multi-temporal; CDF; RADARSAT-2; SMOS
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Tomer, S.K.; Al Bitar, A.; Sekhar, M.; Zribi, M.; Bandyopadhyay, S.; Sreelash, K.; Sharma, A.; Corgne, S.; Kerr, Y. Retrieval and Multi-scale Validation of Soil Moisture from Multi-temporal SAR Data in a Semi-Arid Tropical Region. Remote Sens. 2015, 7, 8128-8153.

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