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Retrieval of precipitation for grassland based on the multi-temporal Sentinel-1 SAR data |
ZHANG Zhaoying1, LU Yicen2, WU Guozhou3, WANG Yongli3 |
1. Xilingol Meteorological Bureau, Xilinhot 026000, China; 2. Zhejiang Meteorological Bureau, Hangzhou 310002, China; 3. Ecological and Agricultural Meteorology Center of Inner Mongolia, Hohhot 010051, China |
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Abstract Water resource is indispensable to the growth of meadows in prairie, and the precise acquisition of the amount of precipitation is of great significance to the continental ecosystem and hydrological circle. This study proposed a novel technique to retrieve the precipitation on the basis of multi-temporal SAR imagery based on the fact that variations of the dielectric constant give rise to modifications of the soil moisture before and after the process of precipitation, allowing for the immediate changes in soil backscattering coefficients. Sentinel-1A SAR and actual measurements of rainfall in the meteorological stations of Erlianhot and Xilinhot were used to verify the retrieval results, which indicated the superb exponential regressive model between the difference values of backscattering coefficient before and after the process of precipitation and the real precipitation measurements. Thus, the spatial distribution of the retrieved precipitation on September 21, 2015 was obtained in the use of this method with Erlianhot as an example, meanwhile, the result shows the favorable spatial distribution consistency of the derived one in comparison with the product of MODIS atmospheric precipitable water considering the atmospheric motion and the acquisition time of imagery. Therefore, this pragmatic method is contrived to yield the actual rainfall spatial distribution in low vegetation coverage regions.
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Keywords
moment matching
GF-2
streaking noise
destriping model
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Issue Date: 04 December 2017
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