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Remote Sens. 2015, 7(1), 647-665; doi:10.3390/rs70100647

A Practical Split-Window Algorithm for Estimating Land Surface Temperature from Landsat 8 Data

1
Institute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, China
2
Satellite Environmental Application Center, Ministry of Environmental Protection, Beijing 100094, China
*
Author to whom correspondence should be addressed.
Academic Editors: Zhao-Liang Li, Jose A. Sobrino, Xiaoning Song and Prasad S. Thenkabail
Received: 17 October 2014 / Accepted: 4 January 2015 / Published: 8 January 2015
(This article belongs to the Special Issue Recent Advances in Thermal Infrared Remote Sensing)
View Full-Text   |   Download PDF [40796 KB, uploaded 8 January 2015]   |  

Abstract

This paper developed a practical split-window (SW) algorithm to estimate land surface temperature (LST) from Thermal Infrared Sensor (TIRS) aboard Landsat 8. The coefficients of the SW algorithm were determined based on atmospheric water vapor sub-ranges, which were obtained through a modified split-window covariance–variance ratio method. The channel emissivities were acquired from newly released global land cover products at 30 m and from a fraction of the vegetation cover calculated from visible and near-infrared images aboard Landsat 8. Simulation results showed that the new algorithm can obtain LST with an accuracy of better than 1.0 K. The model consistency to the noise of the brightness temperature, emissivity and water vapor was conducted, which indicated the robustness of the new algorithm in LST retrieval. Furthermore, based on comparisons, the new algorithm performed better than the existing algorithms in retrieving LST from TIRS data. Finally, the SW algorithm was proven to be reliable through application in different regions. To further confirm the credibility of the SW algorithm, the LST will be validated in the future. View Full-Text
Keywords: Land Surface Temperature (LST); Landsat 8; split-window algorithm; Thermal Infrared (TIR) Land Surface Temperature (LST); Landsat 8; split-window algorithm; Thermal Infrared (TIR)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Du, C.; Ren, H.; Qin, Q.; Meng, J.; Zhao, S. A Practical Split-Window Algorithm for Estimating Land Surface Temperature from Landsat 8 Data. Remote Sens. 2015, 7, 647-665.

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