Separating vegetation and soil temperature using airborne multiangular remote sensing image data

引用方式:
Liu Q, Yan CY, Xiao Q, Yan GJ, Fang L. Separating vegetation and soil temperature using airborne multiangular remote sensing image data. International Journal of Applied Earth Observation and Geoinformation, 2012, 17: 66-75, doi:10.1016/j.jag.2011.10.003.

文献信息
标题	Separating vegetation and soil temperature using airborne multiangular remote sensing image data
年份	2012
出版社	International Journal of Applied Earth Observation and Geoinformation
摘要	Land surface temperature (LST) is a key parameter in land process research. Many research efforts have been devoted to increase the accuracy of LST retrieval from remote sensing. However, because natural land surface is non-isothermal, component temperature is also required in applications such as evapo-transpiration (ET) modeling. This paper proposes a new algorithm to separately retrieve vegetation temperature and soil background temperature from multiangular thermal infrared (TIR) remote sensing data. The algorithm is based on the localized correlation between the visible/near-infrared (VNIR) bands and the TIR band. This method was tested on the airborne image data acquired during the Watershed Allied Telemetry Experimental Research (WATER) campaign. Preliminary validation indicates that the remote sensing-retrieved results can reflect the spatial and temporal trend of component temperatures. The accuracy is within three degrees while the difference between vegetation and soil temperature can be as large as twenty degrees.
PDF	此文献未收录 PDF(如何提交?)

时空三极环境大数据平台

Separating vegetation and soil temperature using airborne multiangular remote sensing image data

相关数据：