Determining Urban Land Uses Through Building-associated Element Attributes Derived from LIDAR and Aerial Photographs

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dc.contributor.advisorCurrit, Nathan
dc.contributor.authorMeng, Xuelianen_US
dc.contributor.committeeMemberFonstad, Mark A.
dc.contributor.committeeMemberZhan, F. Benjamin
dc.contributor.committeeMemberWang, Le
dc.contributor.committeeMemberYang, Xiaojun
dc.date.accessioned2012-02-24T10:12:16Z
dc.date.available2012-02-24T10:12:16Z
dc.date.issued2010-05en_US
dc.description.abstractUrban land-use research is a key component in analyzing the interactions between human activities and environmental change. Researchers have conducted many experiments to classify urban or built-up land, forest, water, agriculture, and other land-use and land-cover types. Separating residential land uses from other land uses within urban areas, however, has proven to be surprisingly troublesome. Although highresolution images have recently become more available for land-use classification, an increase in spatial resolution does not guarantee improved classification accuracy by traditional classifiers due to the increase of class complexity. This research presents an approach to detect and separate residential land uses on a building scale directly from remotely sensed imagery to enhance urban land-use analysis. Specifically, the proposed methodology applies a multi-directional ground filter to generate a bare ground surface from lidar data, then utilizes a morphology-based building detection algorithm to identify buildings from lidar and aerial photographs, and finally separates residential buildings using a supervised C4.5 decision tree analysis based on the seven selected building land-use indicators. Successful execution of this study produces three independent methods, each corresponding to the steps of the methodology: lidar ground filtering, building detection, and building-based object-oriented land-use classification. Furthermore, this research provides a prototype as one of the few early explorations of building-based land-use analysis and successful separation of more than 85% of residential buildings based on an experiment on an 8.25-km2 study site located in Austin, Texas.en_US
dc.description.departmentGeography and Environmental Studies
dc.formatText
dc.format.extent155 pages
dc.format.medium1 file (.pdf)
dc.identifier.citationMeng, X. (2010). <i>Determining urban land uses through building-associated element attributes derived from LIDAR and aerial photographs</i> (Unpublished dissertation). Texas State University-San Marcos, San Marcos, Texas.
dc.identifier.urihttps://hdl.handle.net/10877/4297
dc.language.isoen
dc.subjectLIDARen_US
dc.subjectObject-orienteden_US
dc.subjectBuildingen_US
dc.subjectDecision treeen_US
dc.subjectLand useen_US
dc.subjectUrbanen_US
dc.subjectGround filteringen_US
dc.subjectAerial photographsen_US
dc.subject.classificationGeographyen_US
dc.titleDetermining Urban Land Uses Through Building-associated Element Attributes Derived from LIDAR and Aerial Photographsen_US
dc.typeDissertation
thesis.degree.departmentGeography
thesis.degree.disciplineGeography
thesis.degree.grantorTexas State University-San Marcos
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy

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