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Proceedings Paper

Abstracting of suspected illegal land use in urban areas using case-based classification of remote sensing images
Author(s): Fulong Chen; Chao Wang; Chengyun Yang; Hong Zhang; Fan Wu; Wenjuan Lin; Bo Zhang
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Paper Abstract

This paper proposed a method that uses a case-based classification of remote sensing images and applied this method to abstract the information of suspected illegal land use in urban areas. Because of the discrete cases for imagery classification, the proposed method dealt with the oscillation of spectrum or backscatter within the same land use category, and it not only overcame the deficiency of maximum likelihood classification (the prior probability of land use could not be obtained) but also inherited the advantages of the knowledge-based classification system, such as artificial intelligence and automatic characteristics. Consequently, the proposed method could do the classifying better. Then the researchers used the object-oriented technique for shadow removal in highly dense city zones. With multi-temporal SPOT 5 images whose resolution was 2.5×2.5 meters, the researchers found that the method can abstract suspected illegal land use information in urban areas using post-classification comparison technique.

Paper Details

Date Published: 24 November 2008
PDF: 6 pages
Proc. SPIE 7123, Remote Sensing of the Environment: 16th National Symposium on Remote Sensing of China, 71230R (24 November 2008); doi: 10.1117/12.816188
Show Author Affiliations
Fulong Chen, Graduate Univ. of Chinese Academy of Sciences (China)
Ctr. for Earth Observation and Digital Earth (China)
Chao Wang, Ctr. for Earth Observation and Digital Earth (China)
Chengyun Yang, Shenzhen Municipal Administration of Land, Resources, and Real Estate (China)
Hong Zhang, Ctr. for Earth Observation and Digital Earth (China)
Fan Wu, Ctr. for Earth Observation and Digital Earth (China)
Wenjuan Lin, Shenzhen Municipal Administration of Land, Resources, and Real Estate (China)
Bo Zhang, Ctr. for Earth Observation and Digital Earth (China)


Published in SPIE Proceedings Vol. 7123:
Remote Sensing of the Environment: 16th National Symposium on Remote Sensing of China
Qingxi Tong, Editor(s)

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