Ziyuan Kexue (Jan 2024)

Simulation of flexible space of land use layout in Xuzhou City based on the PLUS model

  • XU Haibin, XIAO Changjiang, LIU Yawen, DENG Shiqi, LI Xin

DOI
https://doi.org/10.18402/resci.2024.01.13
Journal volume & issue
Vol. 46, no. 1
pp. 175 – 186

Abstract

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[Objective] As an innovative way of regulating territorial space, the planning of flexible space is of great significance for improving the scientific quality and effectiveness of spatial planning, and reducing the disturbance and impact of uncertain factors. This study aimed to explore the delineation of land use layout flexible space under uncertain conditions. [Methods] The study took Xuzhou City, a typical resource-based city, as an example. First, an interval optimization model was used to obtain the flexible quantity interval of various land use types. Then, the upper and lower limits of the interval served as the quantity demand to import the PLUS model to simulate the spatial layout of various land use types, and the difference between the two simulated layouts was designated as flexible space. [Results] The results show that: (1) There are differences in the size of the flexible quantity interval of each land use type, among which land use types that contribute more to addressing future uncertainty are rural residential land, farmland, water, urban industrial and mining land, while the smaller ones are grassland and bare land. (2) The flexible space distribution of various land use types shows a certain pattern, and the flexible space of farmland is concentrated in the hotspots of land use change around urban and rural areas, the flexible space of garden plot and woodland is distributed in suitable growth areas such as river banks and low hills, and the flexible space of urban industrial and mining land and rural residential land is mainly distributed in the outer edge areas of their original scope. (3) Based on the flexible space of each land use type, the land types were merged according to the zoning function of the planning, and the conflicting parts of the flexible space were processed according to the suitability to obtain the flexible space of different spatial planning zones. Among them, the flexible space areas of agricultural production zones, ecological protection zones, urban construction zones, and rural development zones account for 1.74%, 0.20%, 1.09%, and 3.31% of the total area, respectively. [Conclusion] The probability distribution of possible conflicts in land use space is the prerequisite for the delineation of flexible space. It is necessary to delineate flexible space of land use layout from an uncertain perspective. Based on interval optimization and PLUS model, the delineation method of flexible space proposed in this study seems feasible, which can provide support for planning decisions.

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