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Proceedings Paper

Remote sensing-based research of urban thermodynamic landscape heterogeneity and spatial scale effect
Author(s): Jia Yi; Yongzhong Tian; Lifen Zhu; Yanghua Gao; Bin Wang
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Paper Abstract

Spatial pattern of urban thermal environment has an important impact on urban microclimate ecology and human living environment. Because of the limitation of current research methods and techniques, spatial patterns and dynamic characteristics of the urban heat island were not well understood. This paper took the core urban area of Chongqing as the research object, used Landsat TM images in 1988,2001 and 2006, coupled with the ground meteorological data, to detect the hot field thermodynamic landscape heterogeneity. Supported with RS, GIS and the basic theory of "landscape ecology", this paper quantitatively explored the change patterns of several basic landscape metrics and the indexes of grain autocorrelation at different scales, such as Landscape Shape Index (LSI), Fractal Dimension-Mean Nearest (FRAC-MN), Shannon-Weaver Landscape Diversity Index (SHDI), Moran I index, and Geary C index and so on. The result showed that the urban thermodynamic landscape heterogeneity in Chongqing urban area was very obvious; landscape metrics were sensitive to grain variance; urban thermodynamic landscape pattern was spatially dependent on the scale; different metrics responded to the different scale; the resolution of 150 meters was an intrinsic scale for the heterogeneity in Chongqing core city. This research also indicated that decreasing consumption of heat energy and enlarging the area of greenbelt and water are effective ways to weaken urban heat effect.

Paper Details

Date Published: 10 September 2008
PDF: 8 pages
Proc. SPIE 7083, Remote Sensing and Modeling of Ecosystems for Sustainability V, 70831F (10 September 2008); doi: 10.1117/12.795911
Show Author Affiliations
Jia Yi, Southwest Univ. (China)
Yongzhong Tian, Southwest Univ. (China)
Lifen Zhu, Chongqing Technology and Business Univ. (China)
Yanghua Gao, Chongqing Institute of Meteorological Science (China)
Bin Wang, Southwest Univ. (China)

Published in SPIE Proceedings Vol. 7083:
Remote Sensing and Modeling of Ecosystems for Sustainability V
Wei Gao; Hao Wang, Editor(s)

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