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Journal of Applied Remote Sensing • new

Downscaling essential climate variable soil moisture using multisource data from 2003 to 2010 in China
Author(s): Hui-Lin Wang; Ru An; Jia-jun You; Ying Wang; Yuehong Chen; Xiao-ji Shen; Wei Gao; Yi-nan Wang; Yu Zhang; Zhe Wang; Jonathan Arthur Quaye-Ballard
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Paper Abstract

Soil moisture plays an important role in the water cycle within the surface ecosystem, and it is the basic condition for the growth of plants. Currently, the spatial resolutions of most soil moisture data from remote sensing range from ten to several tens of km, while those observed in-situ and simulated for watershed hydrology, ecology, agriculture, weather, and drought research are generally <1  km. Therefore, the existing coarse-resolution remotely sensed soil moisture data need to be downscaled. This paper proposes a universal and multitemporal soil moisture downscaling method suitable for large areas. The datasets comprise land surface, brightness temperature, precipitation, and soil and topographic parameters from high-resolution data and active/passive microwave remotely sensed essential climate variable soil moisture (ECV_SM) data with a spatial resolution of 25 km. Using this method, a total of 288 soil moisture maps of 1-km resolution from the first 10-day period of January 2003 to the last 10-day period of December 2010 were derived. The in-situ observations were used to validate the downscaled ECV_SM. In general, the downscaled soil moisture values for different land cover and land use types are consistent with the in-situ observations. Mean square root error is reduced from 0.070 to 0.061 using 1970 in-situ time series observation data from 28 sites distributed over different land uses and land cover types. The performance was also assessed using the GDOWN metric, a measure of the overall performance of the downscaling methods based on the same dataset. It was positive in 71.429% of cases, indicating that the suggested method in the paper generally improves the representation of soil moisture at 1-km resolution.

Paper Details

Date Published: 6 October 2017
PDF: 17 pages
J. Appl. Rem. Sens. 11(4) 045003 doi: 10.1117/1.JRS.11.045003
Published in: Journal of Applied Remote Sensing Volume 11, Issue 4
Show Author Affiliations
Hui-Lin Wang, Nanjing Univ. (China)
Ru An, Hohai Univ. (China)
Jia-jun You, Hohai Univ. (China)
Ying Wang, Univ. of Southampton (United Kingdom)
Yuehong Chen, Hohai Univ. (China)
Xiao-ji Shen, Hohai Univ. (China)
Wei Gao, Hohai Univ. (China)
Yi-nan Wang, Hohai Univ. (China)
Yu Zhang, Hohai Univ. (China)
Zhe Wang, Hohai Univ. (China)
Jonathan Arthur Quaye-Ballard, Kwame Nkrumah Univ. (Ghana)

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