Remote Sensing Applications and Decision Support

Retrieving soil surface temperature under snowpack using special sensor microwave/imager brightness temperature in forested areas of Heilongjiang, China: an improved method

[+] Author Affiliations
Xingming Zheng, Xiaofeng Li, Tao Jiang, Shiyi Zhang, Kai Zhao

Chinese Academy of Sciences, Northeast Institute of Geography and Agroecology, Changchun 130102, China

Chinese Academy of Sciences, Changchun Jingyuetan Remote Sensing Experiment Station, Changchun 130102, China

Yanling Ding

Northeast Normal University, Changchun 130024, China

Lili Wu

Chinese Academy of Sciences, Northeast Institute of Geography and Agroecology, Changchun 130102, China

University of Chinese Academy of Sciences, Beijing 100049, China

J. Appl. Remote Sens. 10(2), 026016 (May 05, 2016). doi:10.1117/1.JRS.10.026016
History: Received November 24, 2015; Accepted April 11, 2016
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Abstract.  Soil surface temperature (Ts) is an important indicator of global temperature change and a key input parameter for retrieving land surface variables using remote sensing techniques. Due to the masking in the thermal infrared band and the scattering in the microwave band of snow, the temperature of soil surfaces covered by snow is difficult to infer from remote sensing data. We attempted to estimate Ts under snow cover using brightness temperature data from the special sensor microwave/imager. Ts under snow cover was underestimated due to the strong scattering effect of snow on upward soil microwave emissions at 37 GHz. The underestimated portion of Ts is related to snow properties, such as depth, grain size, and moisture. Based on the microwave emission model of layered snowpacks, the simulated results revealed a linear relationship between the underestimated Ts and the brightness temperature difference (TBD) at 19 and 37 GHz. When TBDs at 19 and 37 GHz were introduced to the Ts estimation method, accuracy improved, i.e., the root mean square error and bias of the estimated Ts decreased greatly, especially for dry snow. This improvement allows Ts estimation of snow-covered surfaces from 37 GHz microwave brightness temperature.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Xingming Zheng ; Xiaofeng Li ; Tao Jiang ; Yanling Ding ; Lili Wu, et al.
"Retrieving soil surface temperature under snowpack using special sensor microwave/imager brightness temperature in forested areas of Heilongjiang, China: an improved method", J. Appl. Remote Sens. 10(2), 026016 (May 05, 2016). ; http://dx.doi.org/10.1117/1.JRS.10.026016


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