Spatial autocorrelation prediction model of housing market in sprawl area
Urban sprawl is one of the most widely discussed urban issues as it leads to poorly planned patterns of development that result in negative consequences. In fact, research and modelling studies of urban sprawl are considered critical towards ensuring a sustainable urban growth. Therefore, this study...
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my.uthm.eprints.110502024-05-29T02:27:02Z http://eprints.uthm.edu.my/11050/ Spatial autocorrelation prediction model of housing market in sprawl area Mohd Sairi, Nur Asyikin T Technology (General) Urban sprawl is one of the most widely discussed urban issues as it leads to poorly planned patterns of development that result in negative consequences. In fact, research and modelling studies of urban sprawl are considered critical towards ensuring a sustainable urban growth. Therefore, this study aims to develop an urban sprawl model specifically for Johor Bahru by achieving four objectives: to investigate the clustering of housing location based on spatial proximity, to generate the urban sprawl characteristics based on the clustering characteristics of housing, to predict the future urban sprawl pattern based on spatial autocorrelation index and to develop urban sprawl models based on the spatial autocorrelation index. The land use and housing transaction data was acquired from the Department of Town and Country Planning Johor as well as Valuation and Property Services Department respectively. However, the use of spatial data prompted concerns about the possibility of spatial autocorrelation. Thus, to address the urban sprawl issue and methodological issues, this study conducted a series of analyses which included spatial autocorrelation analysis, principal component analysis, cluster analysis, kriging interpolation analysis and multiple regression analysis in developing the urban sprawl model. Through these analyses, it was discovered that the urban sprawl model in Johor Bahru is characterized by similar housing quality characteristics and dissimilar main infrastructure characteristics. Specifically, the housing developments in the city centre of Johor Bahru have similar housing quality characteristics. As the housing developments sprawled towards Kulai and Pasir Gudang respectively, it also demonstrated similar housing quality characteristics. Nevertheless, when the housing developments sprawled towards Iskandar Puteri, it is characterized by the dissimilar characteristics of main infrastructure. This urban sprawl model aids in describing the current and future urban sprawl phenomena in Johor Bahru. This research has contributed to the existing body of knowledge by generating a novel spatial autocorrelation index which consists of urban sprawl characteristics in Johor Bahru. The findings of this study will aid urban planners, developers and home buyers in gaining a deeper understanding of the characteristics of urban sprawl in Johor Bahru from the aspect of housing market 2023-09 Thesis NonPeerReviewed text en http://eprints.uthm.edu.my/11050/1/24p%20NUR%20ASYIKIN%20MOHD%20SAIRI.pdf text en http://eprints.uthm.edu.my/11050/2/NUR%20ASYIKIN%20MOHD%20SAIRI%20COPYRIGHT%20DECLARATION.pdf text en http://eprints.uthm.edu.my/11050/3/NUR%20ASYIKIN%20MOHD%20SAIRI%20WATERMARK.pdf Mohd Sairi, Nur Asyikin (2023) Spatial autocorrelation prediction model of housing market in sprawl area. Doctoral thesis, Universiti Tun Hussein Onn Malaysia. |
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Urban sprawl is one of the most widely discussed urban issues as it leads to poorly planned patterns of development that result in negative consequences. In fact, research and modelling studies of urban sprawl are considered critical towards ensuring a sustainable urban growth. Therefore, this study aims to develop an urban sprawl model specifically for Johor Bahru by achieving four objectives: to investigate the clustering of housing location based on spatial proximity, to generate the urban sprawl characteristics based on the clustering characteristics of housing, to predict the future urban sprawl pattern based on spatial autocorrelation index and to develop urban sprawl models based on the spatial autocorrelation index. The land use and housing transaction data was acquired from the Department of Town and Country Planning Johor as well as Valuation and Property Services Department respectively. However, the use of spatial data prompted concerns about the possibility of spatial autocorrelation. Thus, to address the urban sprawl issue and methodological issues, this study conducted a series of analyses which included spatial autocorrelation analysis, principal component analysis, cluster analysis, kriging interpolation analysis and multiple regression analysis in developing the urban sprawl model. Through these analyses, it was discovered that the urban sprawl model in Johor Bahru is characterized by similar housing quality characteristics and dissimilar main infrastructure characteristics. Specifically, the housing developments in the city centre of Johor Bahru have similar housing quality characteristics. As the housing developments sprawled towards Kulai and Pasir Gudang respectively, it also demonstrated similar housing quality characteristics. Nevertheless, when the housing developments sprawled towards Iskandar Puteri, it is characterized by the dissimilar characteristics of main infrastructure. This urban sprawl model aids in describing the current and future urban sprawl phenomena in Johor Bahru. This research has contributed to the existing body of knowledge by generating a novel spatial autocorrelation index which consists of urban sprawl characteristics in Johor Bahru. The findings of this study will aid urban planners, developers and home buyers in gaining a deeper understanding of the characteristics of urban sprawl in Johor Bahru from the aspect of housing market |
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Thesis |
author |
Mohd Sairi, Nur Asyikin |
author_facet |
Mohd Sairi, Nur Asyikin |
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Mohd Sairi, Nur Asyikin |
title |
Spatial autocorrelation prediction model of housing market in sprawl area |
title_short |
Spatial autocorrelation prediction model of housing market in sprawl area |
title_full |
Spatial autocorrelation prediction model of housing market in sprawl area |
title_fullStr |
Spatial autocorrelation prediction model of housing market in sprawl area |
title_full_unstemmed |
Spatial autocorrelation prediction model of housing market in sprawl area |
title_sort |
spatial autocorrelation prediction model of housing market in sprawl area |
publishDate |
2023 |
url |
http://eprints.uthm.edu.my/11050/1/24p%20NUR%20ASYIKIN%20MOHD%20SAIRI.pdf http://eprints.uthm.edu.my/11050/2/NUR%20ASYIKIN%20MOHD%20SAIRI%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/11050/3/NUR%20ASYIKIN%20MOHD%20SAIRI%20WATERMARK.pdf http://eprints.uthm.edu.my/11050/ |
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