Using TM thermal image to retrieve land surface temperature

Jianmao Guo; Xujie Li; Bin Zhu; Yexian Zhou

doi:10.1117/12.860082

12 August 2010 Using TM thermal image to retrieve land surface temperature

Jianmao Guo, Xujie Li, Bin Zhu, Yexian Zhou

Proceedings Volume 7811, Atmospheric and Environmental Remote Sensing Data Processing and Utilization VI: Readiness for GEOSS IV; 78110G (2010) https://doi.org/10.1117/12.860082
Event: SPIE Optical Engineering + Applications, 2010, San Diego, California, United States

Abstract

The land surface temperature is an important parameter to hydrology and meteorology, it affects the exchange of sensible and latent heats between atmosphere, sea and land, and it can not be lack in many research fields. To retrieve land surface temperature exactly and quantificationally will promote the development of research areas such as drought forecasting crop yield estimating numerical weather forecast, global climate change and carbon balance. Therefore, retrieval of land surface temperature using thermal infrared remote sensing becomes one of the most important tasks in quantificational remote sensing study. The TM images are used in this article, which were recorded in June 11, 2001 over Nakchu area in Tibetan Plateau, to calculate the land surface temperature. The natural surface is classified based on information of remote sensing (snow, water and other land surface) and relevant information of geography, then the emissivity can be dealt with by each surface type in different way. Last, the land surface temperature is inversed by mono-window algorithm. The result show that the derived regional distributions of the the land surface temperature for the whole mesoscale area is agreed with the land surface status very well.

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Jianmao Guo, Xujie Li, Bin Zhu, and Yexian Zhou "Using TM thermal image to retrieve land surface temperature", Proc. SPIE 7811, Atmospheric and Environmental Remote Sensing Data Processing and Utilization VI: Readiness for GEOSS IV, 78110G (12 August 2010); https://doi.org/10.1117/12.860082

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KEYWORDS

Earth observing sensors

Sensors

Landsat

Natural surfaces

Vegetation

Atmospheric sensing

Remote sensing

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