TY  - JOUR
AU  - Che, Tao
AU  - Dai, Liyun
AU  - Zheng, Xingming
AU  - Li, Xiaofeng
AU  - Zhao, Kai
PY  - 2016
DA  - 2016//
TI  - Estimation of snow depth from passive microwave brightness temperature data in forest regions of northeast China
JO  - Remote Sensing of Environment
VL  - 183
KW  - Snow cover;Snow depth;Forest;Remote sensing;Passive microwave;Brightness temperature
AB  - Abstract(#br)Snow depth is an important factor in water resources management in Northeast China. Forest covers 40% of Northeast China, and the presence of forests influences the accuracy of snow depth retrievals from passive microwave remote sensing data. An optimal iteration method was used to retrieve the forest transmissivities at 18 and 36<ce:hsp sp="0.25"/>GHz based on the snow and forest microwave radiative transfer models and the snow properties measured in field experiments. The transmissivities at 18 and 36<ce:hsp sp="0.25"/>GHz are 0.895 and 0.656 in the horizontal polarization, and 0.821 and 0.615 in the vertical polarization, respectively. Furthermore, the forest transmissivity and snow properties were input into the Microwave Emission Model of Layered Snowpacks (MEMLS) to establish a dynamic look-up table (LUT). Snow depths were retrieved from satellite passive microwave remote sensing data based on the LUT method, and these retrievals were verified by snow depth observations at 103 meteorological stations. The results showed that the bias between the retrieved and measured snow depths is very small
ID  - Che2016
ER  -