Comparison of Three Single-window Algorithms for Retrieving Land-Surface Temperature with Landsat 8 TIRS Data

HU Deyong; QIAO Kun; WANG Xingling; ZHAO Limin; JI Guohua

doi:10.13203/j.whugis20150164

Volume 42 Issue 7

Jul. 2017

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Geomatics and Information Science of Wuhan University > 2017 > 42(7): 869-876. > DOI: 10.13203/j.whugis20150164

HU Deyong, QIAO Kun, WANG Xingling, ZHAO Limin, JI Guohua. Comparison of Three Single-window Algorithms for Retrieving Land-Surface Temperature with Landsat 8 TIRS Data[J]. Geomatics and Information Science of Wuhan University, 2017, 42(7): 869-876. DOI: 10.13203/j.whugis20150164

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Comparison of Three Single-window Algorithms for Retrieving Land-Surface Temperature with Landsat 8 TIRS Data

1.
College of Resource Environment & Tourism, Capital Normal University, Beijing 100048, China
2.
Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
3.
Information Center, Ministry of Civil Affairs, Beijing 100721, China
4.
Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

Funds:

The National Natural Science Foundation of China 41671339

the "Twelfth Five Year Plan" Advanced Project on Civil Space of National Defense Science and Industry Bureau D030101

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Author Bio:
HU Deyong, PhD, professor, specializes in resources and environment remote sensing, etc. E-mail: deyonghu@163.com
Corresponding author:
QIAO Kun, master. E-mail: qiaoyingying2009@126.com
Received Date: December 08, 2015
Published Date: July 04, 2017

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Abstract

Abstract

Land surface temperature (LST) is one of the important biophysical variables affecting the exchange of water and energy between land-surface and atmosphere, and it is significant to retrieve LST accurately. The mono-window algorithm is more applied in Landsat TM 6 data, including Jiménez-Muñoz mono-window algorithm (JM_SC) and Qin Zhihao mono-window algorithm (Q_SC). There are a lot of changes for Landsat8 thermal infrared sensor (TIRS) compared with Landsat TM6. Thus a mono-window algorithm for Landsat 8 data (TIRS10_SC) was proposed first, and then some comparison and analysis of three mono-window algorithms were conducted in this paper. The results show that:(1) The TIRS10_SC algorithm is closely integrated with the characteristics of Landsat8 TIRS sensor and it performs well to retrieve LST of different land-cover types based on the retrieval of atmospheric transmittance and land-surface emissivity. (2) Through the comparative analysis, it is found that the retrieval accuracy with Q_SC and TIRS10_SC is higher than JM_SC algorithm. (3) The retrieval results of homogeneous underlying surfaces such as bare soil land and cement surfaces are more accurate than vegetated surfaces. For bare soil land and cement surfaces, the average error of TIRS10_SC and Q_SC algorithm is 0.60℃, and that of JM_SC is 1.01℃; for vegetated surfaces, the average error of TIRS10_SC and Q_SC algorithm is 1.48℃, and that of JM_SC is 1.26℃.In order to improve the LST retrieval accuracy of vegetated surfaces in urban areas, the land-surface emissivity characteristics of vegetated surfaces need to be quantified more accurately.
- thermal remote sensing,
- land surface temperature,
- mono-window algorithm,
- Landsat 8 TIRS

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Comparison of Three Single-window Algorithms for Retrieving Land-Surface Temperature with Landsat 8 TIRS Data

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