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Modeling and Mapping Soil Moisture of Plateau Pasture Using RADARSAT-2 Imagery

Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, 100101 Beijing, China
Author to whom correspondence should be addressed.
Academic Editors: Nicolas Baghdadi and Prasad S. Thenkabail
Remote Sens. 2015, 7(2), 1279-1299;
Received: 16 September 2014 / Accepted: 20 January 2015 / Published: 23 January 2015
PDF [68465 KB, uploaded 23 January 2015]


Accurate soil moisture retrieval of a large area in high resolution is significant for plateau pasture. The object of this paper is to investigate the estimation of volumetric soil moisture in vegetated areas of plateau pasture using fully polarimetric C-band RADARSAT-2 SAR (Synthetic Aperture Radar) images. Based on the water cloud model, Chen model, and Dubois model, we proposed two developed algorithms for soil moisture retrieval and validated their performance using experimental data. We eliminated the effect of vegetation cover by using the water cloud model and minimized the effect of soil surface roughness by solving the Dubois equations. Two experimental campaigns were conducted in the Qinghai Lake watershed, northeastern Tibetan Plateau in September 2012 and May 2013, respectively, with simultaneous satellite overpass. Compared with the developed Chen model, the predicted soil moisture given by the developed Dubois model agreed better with field measurements in terms of accuracy and stability. The RMSE, R2, and RPD value of the developed Dubois model were (5.4, 0.8, 1.6) and (3.05, 0.78, 1.74) for the two experiments, respectively. Validation results indicated that the developed Dubois model, needing a minimum of prior information, satisfied the requirement for soil moisture inversion in the study region. View Full-Text
Keywords: soil moisture; SAR; RADARSAT-2; NDWI; water-cloud; plateau pasture soil moisture; SAR; RADARSAT-2; NDWI; water-cloud; plateau pasture

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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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Chai, X.; Zhang, T.; Shao, Y.; Gong, H.; Liu, L.; Xie, K. Modeling and Mapping Soil Moisture of Plateau Pasture Using RADARSAT-2 Imagery. Remote Sens. 2015, 7, 1279-1299.

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