Evaluation and development of sustainable urban land use plans through spatial optimization

Yao, J. , Murray, A. T., Wang, J. and Zhang, X. (2019) Evaluation and development of sustainable urban land use plans through spatial optimization. Transactions in GIS, 23, pp. 705-725. (doi: 10.1111/tgis.12531)

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Along with rapid global urbanization, cities are challenged by environmental risks and resource scarcity. Sustainable urban planning is central to address the dilemma of economic growth and ecosystem protection, where the use of land is critical. Sustainable land use patterns are spatially explicit in nature, and can be structured and addressed using spatial optimization integrating GIS and mathematical models. This research discusses prominent sustainability concerns in land use planning and suggests a generalized multi‐objective spatial optimization model to facilitate conventional planning. The model is structured to meet land use demand while satisfying the requirements of the physical environment, society and economy. Unlike existing work relying on raster data, due to its simple data structure and ease of spatial relationship evaluation, this research develops an approach for identifying land use solutions based on vector data that better reflects the actual shape and spatial layout of land parcels as well as the ways land use information is managed in practice. An evolutionary algorithm is developed to find the set of efficient (Pareto) solutions given the complexity of vector‐based representations of space. The proposed approach is applied in an empirical study of Dafeng, China in order to support local urban growth and development. The results demonstrate that spatial optimization can be a powerful tool for deriving effective and efficient land use planning strategies. A comparison to results using a raster data approach supports the superiority of land use optimization using vector data as part of planning practice.

Item Type:Articles
Additional Information:Funded by the National Natural Science Foundation of China, Grant/Award Number: 41201117, 41201394 and 41330750.
Glasgow Author(s) Enlighten ID:Yao, Dr Jing
Authors: Yao, J., Murray, A. T., Wang, J., and Zhang, X.
College/School:College of Social Sciences > School of Social and Political Sciences > Urban Studies
Journal Name:Transactions in GIS
ISSN (Online):1467-9671
Published Online:25 April 2019
Copyright Holders:Copyright © 2019 John Wiley & Sons
First Published:First published in Transactions in GIS 23:705-725
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

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