期刊
HABITAT INTERNATIONAL
卷 50, 期 -, 页码 354-365出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.habitatint.2015.09.005
关键词
Driving factors; Land use/land cover change; Multiple scenarios; Neural network; Pen-urban; Urban growth modeling
资金
- Asian Institute of Technology, Thailand
- Japanese Government
- Urban Unit, Lahore
- Bureau of Statistics, Lahore
- Department of City and Regional Planning (CRP), University of Engineering & Technology (UET), Lahore
- Metropolitan Wing, Lahore Development Authority (LDA), Lahore
Metropolitan regions worldwide are experiencing rapid urban growth and the planners often employ prediction models to forecast the future expansion for improving the land management policies and practices. These regions are a mix of urban, pen-urban and rural areas where each sector has its unique expansion properties. This study examines the differences in urban and pen-urban growth characteristics, and their impact at different stages of prediction modeling, in city district Lahore, Pakistan. The analysis of multi-temporal land use/land cover maps revealed that the associations between major land transitions and the factors governing land changes were unique at city district, urban and pen-urban scales. A multilayer perceptron neural network was employed for modeling urbanization, and it was found that the sub-models developed for urban and pen-urban subsets returned better accuracies than those produced at the city district scale. The prediction maps of 2021 and 2035 were also produced through this approach. (C) 2015 Elsevier Ltd. All rights reserved.
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