DocumentCode
2132165
Title
Texture analysis for urban spatial pattern study using SPOT imagery
Author
Zhang, Qiaofeng ; Wang, Jinfei ; Gong, Peng ; Shi, Peijun
Author_Institution
Dept. of Geogr., Univ. of Western Ontario, London, Ont., Canada
Volume
5
fYear
2001
fDate
2001
Firstpage
2149
Abstract
SPOT panchromatic imagery of Beijing has been studied to capture the unique spatial pattern of the city. Texture analysis, which reveals spatial variations, was adopted to interpret the urban spatial patterns. Statistical and structural texture features were extracted from the SPOT image and evaluated for their capability of detailed mapping of urban structures. Supervised image classifications were performed on combinations of different texture features. The imagery was classified into: low-rise, old multi-storey, newer multi-storey and most-recent multistorey, high-rise, roads, construction sites, open water/vegetated and agricultural areas. The study shows that the classification accuracy of original SPOT imagery is only 46%. By using six textural channels, the accuracy has increased to 72%. The best classification shows the urban spatial pattern well
Keywords
geophysical signal processing; geophysical techniques; image classification; image texture; terrain mapping; 350 to 800 nm; Beijing; China; SPOT; accuracy; buildings; city; geophysical measurement technique; image classification; image processing; image texture; land surface; optical imaging; panchromatic imagery; remote sensing; road; satellite remote sensing; spatial pattern; spatial variation; terrain mapping; texture analysis; town; urban area; Cities and towns; Environmental management; Geography; Image analysis; Image classification; Image resolution; Image texture analysis; Pattern analysis; Satellites; Spatial resolution;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International
Conference_Location
Sydney, NSW
Print_ISBN
0-7803-7031-7
Type
conf
DOI
10.1109/IGARSS.2001.977932
Filename
977932
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