Paper
24 November 2008 Analysis on seasonal characteristics of UHI in Beijing city using Landsat 5 TM data
Zhaoming Zhang, Guojin He
Author Affiliations +
Proceedings Volume 7123, Remote Sensing of the Environment: 16th National Symposium on Remote Sensing of China; 71230G (2008) https://doi.org/10.1117/12.816175
Event: Remote Sensing of the Environment: 16th National Symposium on Remote Sensing of China, 2007, Beijing, China
Abstract
Urban heat island (UHI) is an important feature of urban thermal environment. In order to detect the seasonal characteristics of urban heat island in Beijing city, Landsat 5 TM images acquired on July 25th 2005, November 14th 2005, and April 7th 2006 respectively were used to retrieve land surface temperature (LST) of Beijing city based on the generalized single channel algorithm which is a new algorithm applicable to retrieve land surface temperature from only one thermal infrared channel. Then seasonal urban thermal environmental characteristics were analyzed. The result shows that in summer the urban heat island phenomenon is evident, and in both winter and spring, land surface temperature within the second ring road is obviously higher than that between the second and the fourth ring roads showing the ring-shaped UHI features, which is in accordance with the ring-road system of Beijing city. But areas outside the fourth ring road show lighter tone (meaning higher temperature) in the land surface temperature distribution map of winter and spring and reasons for this abnormity were given.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhaoming Zhang and Guojin He "Analysis on seasonal characteristics of UHI in Beijing city using Landsat 5 TM data", Proc. SPIE 7123, Remote Sensing of the Environment: 16th National Symposium on Remote Sensing of China, 71230G (24 November 2008); https://doi.org/10.1117/12.816175
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KEYWORDS
Roads

Earth observing sensors

Landsat

Vegetation

Sensors

Infrared radiation

Remote sensing

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