Automatic Case-Based Reasoning Approach for Landslide Detection: Integration of Object-Oriented Image Analysis and a Genetic Algorithm

This paper proposes an automatic method for detecting landslides by using an integrated approach comprising object-oriented image analysis (OOIA), a genetic algorithm (GA), and a case-based reasoning (CBR) technique. It consists of three main phases: (1) image processing and multi-image segmentation...

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Vydáno v:	Remote sensing (Basel, Switzerland) Ročník 7; číslo 4; s. 4318 - 4342
Hlavní autoři:	Dou, Jie, Chang, Kuan-Tsung, Chen, Shuisen, Yunus, Ali, Liu, Jin-King, Xia, Huan, Zhu, Zhongfan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Basel MDPI AG 01.04.2015
Témata:	Algorithms Automation genetic algorithm (GA) Genetic algorithms Image analysis image classification image segmentation landslide detection Landslides Object oriented object-oriented image analysis (OOIA) Object-oriented programming Reasoning Remote sensing Segmentation Urban areas
ISSN:	2072-4292, 2072-4292
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Abstract	This paper proposes an automatic method for detecting landslides by using an integrated approach comprising object-oriented image analysis (OOIA), a genetic algorithm (GA), and a case-based reasoning (CBR) technique. It consists of three main phases: (1) image processing and multi-image segmentation; (2) feature optimization; and (3) detecting landslides. The proposed approach was employed in a fast-growing urban region, the Pearl River Delta in South China. The results of detection were validated with the help of field surveys. The experimental results indicated that the proposed OOIA-GA-CBR (0.87) demonstrates higher classification performance than the stand-alone OOIA (0.75) method for detecting landslides. The area under curve (AUC) value was also higher than that of the simple OOIA, indicating the high efficiency of the proposed landslide detection approach. The case library created using the integrated model can be reused for time-independent analysis, thus rendering our approach superior in comparison to other traditional methods, such as the maximum likelihood classifier. The results of this study thus facilitate fast generation of accurate landslide inventory maps, which will eventually extend our understanding of the evolution of landscapes shaped by landslide processes.
AbstractList	This paper proposes an automatic method for detecting landslides by using an integrated approach comprising object-oriented image analysis (OOIA), a genetic algorithm (GA), and a case-based reasoning (CBR) technique. It consists of three main phases: (1) image processing and multi-image segmentation; (2) feature optimization; and (3) detecting landslides. The proposed approach was employed in a fast-growing urban region, the Pearl River Delta in South China. The results of detection were validated with the help of field surveys. The experimental results indicated that the proposed OOIA-GA-CBR (0.87) demonstrates higher classification performance than the stand-alone OOIA (0.75) method for detecting landslides. The area under curve (AUC) value was also higher than that of the simple OOIA, indicating the high efficiency of the proposed landslide detection approach. The case library created using the integrated model can be reused for time-independent analysis, thus rendering our approach superior in comparison to other traditional methods, such as the maximum likelihood classifier. The results of this study thus facilitate fast generation of accurate landslide inventory maps, which will eventually extend our understanding of the evolution of landscapes shaped by landslide processes.
Author	Chang, Kuan-Tsung Chen, Shuisen Xia, Huan Yunus, Ali Liu, Jin-King Zhu, Zhongfan Dou, Jie
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Snippet	This paper proposes an automatic method for detecting landslides by using an integrated approach comprising object-oriented image analysis (OOIA), a genetic...
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SubjectTerms	Algorithms Automation genetic algorithm (GA) Genetic algorithms Image analysis image classification image segmentation landslide detection Landslides Object oriented object-oriented image analysis (OOIA) Object-oriented programming Reasoning Remote sensing Segmentation Urban areas
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Title	Automatic Case-Based Reasoning Approach for Landslide Detection: Integration of Object-Oriented Image Analysis and a Genetic Algorithm
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