DocumentCode
2321337
Title
Numerical study of urban expansion and its influence on urban environment using Landsat TM/ETM+ images
Author
Ma, Ya ; Kuang, Yao-qiu ; Huan, Ning-sheng
Author_Institution
Key Lab. of Marginal Sea Geol., Chinese Acad. of Sci., Guangzhou
fYear
2009
fDate
20-22 May 2009
Firstpage
1
Lastpage
7
Abstract
Multi-temporal Landsat TM/ETM+ imagery of 1990, 2000, and 2005 were used in this study. And the vegetation abundances, percent impervious surface, normalized difference impervious surface index(NDISI) and brightness temperature were retrieved from each TM/ETM+ dataset. Then the urban expansion, urban heat island and the relationships between LST and other variables which relate to urban environment were investigated. Results indicated that the percentage of urban area in Guangzhou increased significantly, which grew from 18.35% in 1990, to 24.16% in 2000, and further to 33.29% in 2005. But the intensity of urban heat island was not always enlarged during 1990-2005. And the regression analyses showed that, at the pixel-scale, the relationships between LST and other two variables (vegetation abundances and percent impervious surface) were relatively more complicated and could not be described by using the linear regression model. However, LST had a strong positive and negative correlation with percent impervious area and vegetation abundance in the region-scale, respectively. These results may be very useful for moderate- or large-scale ecological modeling and climate modeling.
Keywords
atmospheric boundary layer; atmospheric temperature; land surface temperature; regression analysis; remote sensing; vegetation; AD 1990; AD 2000; AD 2005; Guangzhou; brightness temperature; climate modeling; land surface temperature; large-scale ecological modeling; linear regression model; multitemporal Landsat TM/ETM+ imagery; normalized difference impervious surface index; percent impervious surface; urban environment; urban expansion; urban heat island; vegetation abundances; Biological system modeling; Brightness temperature; Information retrieval; Linear regression; Regression analysis; Remote sensing; Satellites; Thermal pollution; Urban areas; Vegetation mapping;
fLanguage
English
Publisher
ieee
Conference_Titel
Urban Remote Sensing Event, 2009 Joint
Conference_Location
Shanghai
Print_ISBN
978-1-4244-3460-2
Electronic_ISBN
978-1-4244-3461-9
Type
conf
DOI
10.1109/URS.2009.5137637
Filename
5137637
Link To Document