An Efficient Approach for Pixel Decomposition of Land Surface Temperature from Landsat TM Data

WANG Fei; QIN Zhihao; SONG Caiying

doi:10.13203/j.whugis20140604

Volume 42 Issue 1

Jan. 2017

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Geomatics and Information Science of Wuhan University > 2017 > 42(1): 116-122. > DOI: 10.13203/j.whugis20140604

WANG Fei, QIN Zhihao, SONG Caiying. An Efficient Approach for Pixel Decomposition of Land Surface Temperature from Landsat TM Data[J]. Geomatics and Information Science of Wuhan University, 2017, 42(1): 116-122. DOI: 10.13203/j.whugis20140604

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An Efficient Approach for Pixel Decomposition of Land Surface Temperature from Landsat TM Data

1.
School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China
2.
Institute of Agro-Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China

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The National Natural Science Foundation of China 41471300

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Author Bio:
WANG Fei, PhD candidate, specializes in thermal remote sensing and agriculture remote sensing. E-mail: essiwf@163.com
Corresponding author:
QIN Zhihao, PhD, professor. E-mail: zhihaoqin@163.com
Received Date: December 27, 2014
Published Date: January 04, 2017

Graphical Abstract

Abstract

Abstract

The spatial resolution of land surface temperature (LST, 120 m) retrieved from thermal infrared (TIR) band is lower than its visible/near-infrared (VNIR) bands (30 m). LST image with high spatial resolution compatible with VNIR bands of Landsat TM is very important for application of the LST image to many studies such as environmental monitoring. The objective of this study is to decompose the coarse pixels of the LST image data into the same pixel scale of the auxiliary VNIR data. Firstly, the E-DisTrad method is used to divide LST of the parent pixels into the sub-pixels to obtain the first decomposition temperature and the theoretical radiance at-sensor of each sub-pixel. Then, a chess-segmentation is done to the temperature of the sub-pixels on the basis of the object-oriented image segmentation method to compute the weight for each sub-pixel, which is consequently used to allocate the thermal radiance for each sub-pixel to generate the decomposed LST image. At last, a method of increase the spatial resolution firstly and then used for double-step pixel decomposition is executed in the study to validate the accuracy and efficiency of the decomposition method for the Landsat TM image of Beijing. The result showed that the double-step pixel decomposition method is applicable for decomposition of LST images for high spatial resolution, reflecting the spatial differences of different land use and land cover and ensure the conservation of energy before and after pixel decomposition. Therefore we can conclude that it is ideally suited for complex covered surface area of downscaling thermal infrared band remote sensing data.
- land surface temperature,
- pixel decomposition,
- Landsat TM

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References

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An Efficient Approach for Pixel Decomposition of Land Surface Temperature from Landsat TM Data

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