Urban landscape pattern change based on multi-temporal CBERS imagery - Taking Xuzhou City as an example

Pei Jun Du; Lin Shan Yuan; Hua Peng Zhang; Kun Tan; Zuo Xia Yin

Urban landscape pattern change based on multi-temporal CBERS imagery - Taking Xuzhou City as an example

Pei Jun Du^*
, Lin Shan Yuan
, Hua Peng Zhang
, Kun Tan
, Zuo Xia Yin

^*此作品的通讯作者

China University of Mining and Technology

科研成果: 期刊稿件 › 文章 › 同行评审

5 引用（Scopus）

摘要

CBERS CCD and IRMSS images were classified using Maximum Likelihood Classifier, Support Vector Machine and Object-Oriented Classifiers, and the classification results of SVM were used to further landscape pattern analysis of Xuzhou city. Urban landscape pattern and its dynamic change were analyzed based on multi-temporal analysis on landscape pattern indices derived from the classification results of 2001, 2005 and 2007. Furthermore, multi-scale data of CBERS sensors were used for landscape pattern analysis and statistical comparison. It proves that CBERS data is suitable for urban landscape analysis.

源语言	英语
页（从-至）	106-113
页数	8
期刊	Zhongguo Kuangye Daxue Xuebao/Journal of China University of Mining and Technology
卷	38
期	1
出版状态	已出版 - 1月 2009
已对外发布	是

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abstract = "CBERS CCD and IRMSS images were classified using Maximum Likelihood Classifier, Support Vector Machine and Object-Oriented Classifiers, and the classification results of SVM were used to further landscape pattern analysis of Xuzhou city. Urban landscape pattern and its dynamic change were analyzed based on multi-temporal analysis on landscape pattern indices derived from the classification results of 2001, 2005 and 2007. Furthermore, multi-scale data of CBERS sensors were used for landscape pattern analysis and statistical comparison. It proves that CBERS data is suitable for urban landscape analysis.",

keywords = "CBERS, Classification, Landscape pattern, Support vector machine",

author = "Du, \{Pei Jun\} and Yuan, \{Lin Shan\} and Zhang, \{Hua Peng\} and Kun Tan and Yin, \{Zuo Xia\}",

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T1 - Urban landscape pattern change based on multi-temporal CBERS imagery - Taking Xuzhou City as an example

AU - Du, Pei Jun

AU - Yuan, Lin Shan

AU - Zhang, Hua Peng

AU - Tan, Kun

AU - Yin, Zuo Xia

PY - 2009/1

Y1 - 2009/1

N2 - CBERS CCD and IRMSS images were classified using Maximum Likelihood Classifier, Support Vector Machine and Object-Oriented Classifiers, and the classification results of SVM were used to further landscape pattern analysis of Xuzhou city. Urban landscape pattern and its dynamic change were analyzed based on multi-temporal analysis on landscape pattern indices derived from the classification results of 2001, 2005 and 2007. Furthermore, multi-scale data of CBERS sensors were used for landscape pattern analysis and statistical comparison. It proves that CBERS data is suitable for urban landscape analysis.

AB - CBERS CCD and IRMSS images were classified using Maximum Likelihood Classifier, Support Vector Machine and Object-Oriented Classifiers, and the classification results of SVM were used to further landscape pattern analysis of Xuzhou city. Urban landscape pattern and its dynamic change were analyzed based on multi-temporal analysis on landscape pattern indices derived from the classification results of 2001, 2005 and 2007. Furthermore, multi-scale data of CBERS sensors were used for landscape pattern analysis and statistical comparison. It proves that CBERS data is suitable for urban landscape analysis.

KW - CBERS

KW - Classification

KW - Landscape pattern

KW - Support vector machine

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SN - 1000-1964

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JO - Zhongguo Kuangye Daxue Xuebao/Journal of China University of Mining and Technology

JF - Zhongguo Kuangye Daxue Xuebao/Journal of China University of Mining and Technology

IS - 1

ER -

Urban landscape pattern change based on multi-temporal CBERS imagery - Taking Xuzhou City as an example

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