Snow Depth Inversion Using the Localized HUT Model Based on FY-3B MWRI Data in the Farmland of Heilongjiang Province, China

被引：0
作者：
Lili Wu
Xiaofeng Li
Kai Zhao
Xingming Zheng
机构：
[1] Chinese Academy of Sciences,Northeast Institute of Geography and Agroecology
[2] University of Chinese Academy of Sciences,undefined
[3] Changchun Jingyuetan Remote Sensing Test Site of Chinese Academy of Sciences,undefined
来源：
Journal of the Indian Society of Remote Sensing | 2017年 / 45卷
关键词：
FY-3B; Microwave Radiation Imager (MWRI); Extinction coefficient; Snow depth; Passive Microwave (PM); Heilongjiang Province;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Snow depth parameter inversion in the farmland using passive microwave remote sensing is of great significance to the agricultural production in Northeast China. Firstly, the Helsinki University of Technology (HUT) snow emission model was validated in the farmland based on microwave radiation imager (MWRI) onboard FengYun-3B satellite (FY-3B). The results showed that there was a big difference between the brightness temperature of HUT model simulation and MWRI for 18.7 GHz horizontal polarization (18.7 H) and 36.5 GHz horizontal polarization (36.5 H). To improve HUT model, the empirical parameter in the model was localized. Then the localized HUT (LHUT) model was built, where the extinction coefficient was calculated by the new extinction coefficient formula. Next, LHUT model was validated based on MWRI data and compared with HUT model. The results showed that LHUT underestimates slightly the brightness temperature with 0.91 and 4.19 K for 18.7 and 36.5 H respectively, and LHUT is superior to HUT model. Finally, the genetic algorithm (GA) was used to invert snow depth based on LHUT. The results showed that snow depth was underestimated with 6.79 cm based on LHUT. The inverted snow depth based on LHUT model is in better agreement with the measured snow depth.
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页码：89 / 100
页数：11
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