Proceedings Paper
Inversion land surface temperature by using TM data| Format | Member Price | Non-Member Price |
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Paper Abstract
The land surface temperature (LST) plays an important role in the process of interaction between surface and atmosphere.
It is widely need in meteorology, geology, hydrology, ecological and many other fields. This article uses the ETM+ data
of February 16th, 2002 and August 27th, 2002, using the single window algorithm to retrieve the LST in the southern area
of Gansu province. First step is removing cloud for image. Secondly, classifies the type of surface by dividing into three
types of water surface, snow surfaces (winter) and natural surface. Then, estimate the emissivity according to the
classification in order to calculate surface temperature. Through the analysis of spatial distribution of land surface
temperature in the study area, the result shows QinZhiHao's single window algorithm is consistent with the reality.
Paper Details
Date Published: 24 October 2012
PDF: 9 pages
Proc. SPIE 8513, Remote Sensing and Modeling of Ecosystems for Sustainability IX, 85130D (24 October 2012); doi: 10.1117/12.930428
Published in SPIE Proceedings Vol. 8513:
Remote Sensing and Modeling of Ecosystems for Sustainability IX
Wei Gao; Thomas J. Jackson, Editor(s)
PDF: 9 pages
Proc. SPIE 8513, Remote Sensing and Modeling of Ecosystems for Sustainability IX, 85130D (24 October 2012); doi: 10.1117/12.930428
Show Author Affiliations
Jianmao Guo, Lanzhou Arid Meteorological Institute of China Meteorological Adiministration (China)
Nanjing Univ. of Information Science & Technology (China)
Junyi Shi, Nanjing Univ. of Information Science & Technology (China)
Xiangyun Han, Nanjing Univ. of Information Science & Technology (China)
Nanjing Univ. of Information Science & Technology (China)
Junyi Shi, Nanjing Univ. of Information Science & Technology (China)
Xiangyun Han, Nanjing Univ. of Information Science & Technology (China)
Tengfei Zheng, Nanjing Univ. of Information Science & Technology (China)
Qi Wang, Nanjing Univ. of Information Science & Technology (China)
Qi Wang, Nanjing Univ. of Information Science & Technology (China)
Published in SPIE Proceedings Vol. 8513:
Remote Sensing and Modeling of Ecosystems for Sustainability IX
Wei Gao; Thomas J. Jackson, Editor(s)
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