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Satellite-derived land surface temperature: Current status and perspectives

Open access
Li, Zhao-Liang, Tang, Bo-Hui, Wu, Hua, Ren, Huazhong, Yan, Guangjian, Wan, Zhengming, Trigo, Isabel F., Sobrino, José A.·2013·Remote Sensing of Environment

Abstract

Land surface temperature (LST) is one of the key parameters in the physics of land surface processes from local through global scales. The importance of LST is being increasingly recognized and there is a strong interest in developing methodologies to measure LST from space. However, retrieving LST is still a challenging task since the LST retrieval problem is ill-posed. This paper reviews the current status of selected remote sensing algorithms for estimating LST from thermal infrared (TIR) data. A brief theoretical background of the subject is presented along with a survey of the algorithms employed for obtaining LST from space-based TIR measurements. The discussion focuses on TIR data acquired from polar-orbiting satellites because of their widespread use, global applicability and higher spatial resolution compared to geostationary satellites. The theoretical framework and methodologies used to derive the LST from the data are reviewed followed by the methodologies for validating satellite-derived LST. Directions for future research to improve the accuracy of satellite-derived LST are then suggested.

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Metadata

Authors
Li, Z.-L., Tang, B.-H., Wu, H., Ren, H., Yan, G., Wan, Z., Trigo, I. F., & Sobrino, J. A.
Venue
Remote Sensing of Environment
Publisher
Elsevier BV
Published
2013-04
Volume
131
Pages
14-37
ISSN
0034-4257 (ISSN-L)
OpenAlex
W2026337749
Cited by
2,274
References
1
FWCI
82.04
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Satellite-derived land surface temperature: Current status and perspectives. https://app.cochat.ai/papers/10.1016/j.rse.2012.12.008
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Li, Z.-L., Tang, B.-H., Wu, H., Ren, H., Yan, G., Wan, Z., Trigo, I. F., & Sobrino, J. A. (2013). Satellite-derived land surface temperature: Current status and perspectives. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2012.12.008

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