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Accuracy assessment of urban growth pattern classification methods using confusion matrix and ROC analysis

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dc.citedby5
dc.contributor.authorGhani N.L.A.en_US
dc.contributor.authorAbidin S.Z.Z.en_US
dc.contributor.authorKhalid N.E.A.en_US
dc.contributor.authorid56940219600en_US
dc.contributor.authorid25824609700en_US
dc.contributor.authorid25634252000en_US
dc.date.accessioned2023-05-29T06:01:21Z
dc.date.available2023-05-29T06:01:21Z
dc.date.issued2015
dc.descriptionClassification (of information); Growth rate; Image resolution; Matrix algebra; Pattern recognition; Soft computing; Accuracy assessment; Accuracy of classifications; Classification methods; Confusion matrices; Expansion index; Receiver operating characteristic analysis; ROC analysis; Urban growth patterns; Urban growthen_US
dc.description.abstractUrban growth pattern can be categorized as either infill, expansion or outlying. Studies on urban growth classification are focusing on the description of urban growth pattern geometric features using conventional landscape metrics. These metrics are too simple and unable to give detailed information on accuracy of the classification methods. This paper aims to assess the accuracy of classification methods that can determine urban growth patterns correctly for a specific growth area. Accuracy assessments are carried out using three different classification methods - moving window, topological relation border length and landscape expansion index. Based on confusion matrices and receiver operating characteristic (ROC) analysis, results show that landscape expansion index has the best accuracy among all. � Springer Science+Business Media Singapore 2015.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1007/978-981-287-936-3_24
dc.identifier.epage264
dc.identifier.scopus2-s2.0-84946039583
dc.identifier.spage255
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84946039583&doi=10.1007%2f978-981-287-936-3_24&partnerID=40&md5=49a56e4986ab76d4452d666b63348b59
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22499
dc.identifier.volume545
dc.publisherSpringer Verlagen_US
dc.sourceScopus
dc.sourcetitleCommunications in Computer and Information Science
dc.titleAccuracy assessment of urban growth pattern classification methods using confusion matrix and ROC analysisen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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