Share Email Print

Proceedings Paper

Research on retrieving land surface temperature from MODIS thermal infrared data
Author(s): Lei Zheng; Lingli Tang; Zhaoliang Li
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

In Earth Observing System (EOS) plan, MODerate-resolution Imaging Spectroradiometer (MODIS) is loaded on both the two polar-orbit satellites: Terra (EOS-AM1) and Aqua (EOS-PM1). MODIS data has 16 Thermal InfraRed (TIR) channels (3.5~14.5 μm) among all of its 36 channels. Land Surface Temperature (LST) is an important indicator of earth surface energy balances and climate changes, as well as a key parameter in physical processes of land surface on both global and regional scale. LST is widely applied in the research of disciplines such as meteorology, hydrology, ecology, biochemistry, etc1. Therefore, retrieving LST from appropriate MODIS TIR bands is one of the important applications. First of all, this paper introduces theoretical foundations of retrieving LST from remote sensing data, such as the method of selecting appropriate TIR bands by conditional analysis of atmospheric window. Then, this paper provides an overview of LST retrieving algorithms up to now, including Single Window Algorithm, Split Window Algorithm, Improved Split Window Algorithm, Generalized Split Window Algorithm and Day/Night Algorithm. And at last, towards to the limitations of LST retrieving algorithm, the authors indicates their specific perspectives on the directions of further correlative research in two aspects: improving LST retrieving algorithm and increasing LST retrieving accuracy.

Paper Details

Date Published: 19 May 2006
PDF: 8 pages
Proc. SPIE 6199, Remote Sensing and Space Technology for Multidisciplinary Research and Applications, 619908 (19 May 2006); doi: 10.1117/12.673657
Show Author Affiliations
Lei Zheng, China Remote Sensing Satellite Ground Station, CAS (China)
Graduate Univ. of Chinese Academy of Sciences (China)
Lingli Tang, China Remote Sensing Satellite Ground Station, CAS (China)
Zhaoliang Li, Institute of Geographic Sciences and Natural Resources Research, CAS (China)
LSIIT, CNRS (France)

Published in SPIE Proceedings Vol. 6199:
Remote Sensing and Space Technology for Multidisciplinary Research and Applications
Qingxi Tong; Xiuwan Chen; Allen Huang; Wei Gao, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?