长江流域资源与环境 >> 2019, Vol. 28 >> Issue (09): 2019-2029.doi: 10.11870/cjlyzyyhj201909001

• 区域可持续发展 •    下一篇

基于Pareto最优和多目标粒子群的土地利用优化配置研究

王帝文, 李飞雪, 陈  东   

  1. (南京大学地理与海洋科学学院,江苏 南京 210023)
  • 出版日期:2019-09-20 发布日期:2019-09-17

Research on Optimal Land Use Allocation Based on Pareto Optimal and Multiparticle Swarm Algorithm

WANG Di-wen, LI Fei-xue, CHEN Dong   

  1. (School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China)
  • Online:2019-09-20 Published:2019-09-17

摘要: 土地利用优化配置主要是研究土地资源在数量结构、空间布局及综合效益的优化,过程中需考虑土地资源、生态环境、政策影响等多方面因素,因此很难得到最优方案,给土地利用配置带来了很大的挑战。该文以常州市武进区为研究区,采用基于Pareto最优的多目标粒子群算法构建了土地利用优化配置模型,分析了优化后的土地利用配置方案在数量结构和空间布局上的变化特征。研究表明:该模型能够利用粒子群在空间中的分布模拟土地利用的空间布局,并能在多目标控制和条件约束下进行全局优化处理,模型得到的一组符合Pareto最优的土地利用配置方案,能够提高土地的集聚度、适宜度以及区域整体的生态服务价值,从而为土地规划提供了具有不同数量和空间布局特征的方案支持。

Abstract: In the process of economic development, the unreasonable land allocation had led to deterioration of urban ecological environment which includes soil and water loss, farmland degradation and traffic jam. Therefore, optimal land use allocation has been regarded as one of the keys to the sustainable development of cities. Since some significant contradictions often exist between land development and nature conservation, land use allocation confronts great challenges to balance land use suitability, compactness and ecosystem services values.
In order to solve this problem, this paper aims to propose an ideal solution by using the multiobjective particle swarm optimization algorithm based on principle of pareto optimization. Six major land use types are arranged in study area which included cultivated land, forest land, wetland, waterbody, habitat and industry land. Three objective functions are defined: maximizing suitability, maximizing ecosystem service value, maximizing land use compactness. As the initial swarm was created, the values of the objective functions were calculated, and nondominated answers were preserved in an external archive. To prevent particle swarm sticking into local convergence, mutation operators were added to the particle swarms to promote the uniform distribution of particles. Combining with the constraints of the land policy, the Paretofront that meets the realistic requirements was finally formed in the threedimensional space. We selected Wujin district of Changzhou as study area, which had the land use maps, urban planning and socioeconomic data for the experiment of optimal land use allocation.
The results show that a uniform set of ParetoFrontiers can be obtained by applying the model, which means that each result is an optimal land use allocation. The optimized allocation improves the land suitability, ecosystem service value and land compactness by 9.96%, 4.27%, and 5.23% respectively. Compared with singleobjective model that can only produce one result, the model can obtain more optimized allocations with the same optimal level, different quantity structure and spatial characteristics, which can be better support for land use planning.

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