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Remote Sens. 2017, 9(5), 402; doi:10.3390/rs9050402

Evaluation of Multiple Downscaled Microwave Soil Moisture Products over the Central Tibetan Plateau

1
School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China
2
School of Resource and Civil Engineering, Wuhan Institute of Technology, Wuhan 430205, China
3
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
*
Author to whom correspondence should be addressed.
Academic Editors: Nicolas Baghdadi, Xiaofeng Li and Prasad S. Thenkabail
Received: 22 February 2017 / Revised: 3 April 2017 / Accepted: 21 April 2017 / Published: 25 April 2017
View Full-Text   |   Download PDF [6163 KB, uploaded 25 April 2017]   |  

Abstract

Downscaled microwave soil moisture (SM) products with a fine resolution are of great importance for both local and regional studies. However, few studies have explored the merits of multiple downscaled microwave SM products. An evaluation of the different products could help to advance knowledge of the downscaled microwave SM products and help researchers to choose the appropriate downscaled SM products for use in further studies. In this research, five microwave SM products derived from Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR-E), AMSR2, and Soil Moisture and Ocean Salinity (SMOS) data were downscaled via the back-propagation neural network (BPNN). The BPNN was chosen because it can effectively simulate the nonlinear relationship between SM and the land surface temperature (LST)/vegetation index (VI). The different downscaled SM products were evaluated with in-situ SM data from the central Tibetan Plateau Soil Moisture/Temperature Monitoring Network (SMTMN) during the period from 1 August 2010 to 31 December 2012. Compared with the regression technique, the downscaled correlation coefficient (r) is significantly improved by the BPNN. The downscaled root-mean-square error (RMSE) and bias are comparable for the two techniques. As expected, LST and enhanced VI (EVI) are physically related to SM, and this is the most suitable combination for SM downscaling. Except for the ascending node of SMOS and AMSR2, the downscaled r is closely related to the original RMSE, and a lower original RMSE for the SM product results in a higher downscaled r. The BPNN-downscaled SMOS product in descending node is the closest to the in-situ SM among the different downscaled microwave SM products. The temporal variations and ranges of the microwave SM products are well maintained by the BPNN downscaling. Furthermore, the evaluations against in-situ SM reveal that the overall accuracies of the BPNN-downscaled SM products are very close to the original microwave SM products. View Full-Text
Keywords: evaluation; downscaling; back-propagation neural network (BPNN); passive microwave soil moisture products evaluation; downscaling; back-propagation neural network (BPNN); passive microwave soil moisture products
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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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MDPI and ACS Style

Jiang, H.; Shen, H.; Li, H.; Lei, F.; Gan, W.; Zhang, L. Evaluation of Multiple Downscaled Microwave Soil Moisture Products over the Central Tibetan Plateau. Remote Sens. 2017, 9, 402.

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