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应用生态学报 ›› 2025, Vol. 36 ›› Issue (10): 3161-3174.doi: 10.13287/j.1001-9332.202510.025

• 研究报告 • 上一篇    下一篇

一种非线性距离优劣解法在西安市中心城区人居环境适宜性评价中的应用

李尚志, 张猛*   

  1. 西安交通大学人居环境与建筑工程学院, 西安 710049
  • 收稿日期:2025-02-13 修回日期:2025-08-03 发布日期:2026-05-04
  • 通讯作者: *E-mail: zhangmeng01@mail.xjtu.edu.cn
  • 作者简介:李尚志, 男, 1996年生, 博士研究生。主要从事3S技术在人居环境评价与空间感知优化中的应用研究。E-mail: lishangzhi@stu.xjtu.edu.cn
  • 基金资助:
    中国科学院战略性先导科技专项(XDB40020200)和国家自然科学基金项目(41871315)

Application of a nonlinear TOPSIS algorithm to human settlement suitability evaluation in central Xi’an, Northwest China

LI Shangzhi, ZHANG Meng*   

  1. School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an 710049, China
  • Received:2025-02-13 Revised:2025-08-03 Published:2026-05-04

摘要: 传统人居环境适宜性评价方法难以有效刻画指标数值对整体适宜性的非线性贡献(如边际效应递减或过量反作用等)。为此,本研究以西安市中心城区为研究对象,提出了一种非线性距离优劣解法(TOPSIS),以实现人居环境适宜性的精细化定量评估。在方法上,构建以街区单元为基本分析粒度的评价框架,从自然环境、经济繁荣程度、生活便利性和建筑格局4个维度构建评价体系。基于各指标数据的分布特征,引入幂率函数、高斯函数、Beta函数和高斯混合模型等非线性拟合方法,刻画指标对人居环境的非线性影响与边际效应,进而建立“基于非线性函数识别理想解与负理想解”的改进TOPSIS模型。同时,对比多种主、客观赋权方法为评价算法遴选更为合理的权重分配策略。结果表明:研究区人居环境适宜性指数值近似正态分布,空间上呈现出以城市街区单元为单位的混合型空间分布特征。高适宜性区域占地面积为167.82 km2(占比17.5%),主要分布于碑林区、新城区及雁塔区部分街区,普遍呈现出绿化率、建筑密度适中及生活设施完善的特征;低适宜性区域集中在城市老城区及开发不足地带,表现为绿化率偏低、建筑密度偏高或基础设施薄弱等空间失衡现象。空间滞后模型和空间误差模型进一步揭示了评价方法的适用性和稳健性。本研究提出的非线性TOPSIS算法丰富了适宜性评价的理论体系,拓展了空间决策支持方法,可为城市空间优化和精细化治理提供理论依据和方法支持。

关键词: 人居环境适宜性, 非线性函数, 距离优劣解法, 顾及相关性的标准重要性法, 城市街区单元

Abstract: Traditional methods for evaluating human settlement suitability often fail to effectively characterize the nonlinear influence of indicator values on overall suitability, such as diminishing marginal effects or counterproductive outcomes from excessive input. To overcome those shortages, we proposed a Nonlinear Technique for Order Preference by Similarity to Ideal Solution (nonlinear-TOPSIS) to achieve a refined quantitative evaluation of human settlement suitability, with the central urban area of Xi’an as the study area. We constructed an evaluation framework based on urban block units as the fundamental analysis granularity, and developed an indicator system from four dimensions: natural environment, economic prosperity, living convenience, and building morphology. Based on the distributional characteristics of each indicator, we introduced nonlinear fitting methods, including power-law functions, Gaussian functions, Beta functions, and Gaussian mixture models, to characterize their nonlinear impacts and marginal effects, and then established an improved TOPSIS model based on nonlinear function to identify ideal and negative ideal solutions. Meanwhile, we compared multiple subjective and objective weighting methods to provide a more rational weight assignment for the evaluation algorithm. The results showed that the human settlement suitability index values within the research area approximated a normal distribution and exhibited a mixed spatial pattern at the parcel level. High-suitability areas covered 167.82 km2(accounting for 17.5% of the total area), mainly distributed in Beilin District, Xincheng District, and parts of Yanta District. These areas were generally characterized by moderate greening rates, appropriate building density, and well-developed living facilities. Low-suitability areas were concentrated in old urban neighborhoods and underdeveloped zones, exhibiting spatial imba-lances in greening rates, building density, and infrastructure. The spatial lag model and spatial error model further validated the applicability and robustness of the proposed evaluation method. The nonlinear-TOPSIS algorithm proposed here would enrich the theoretical framework of human settlement suitability assessment, expand the methodological approach of spatial decision support, and provide theoretical basis and methodological support for urban spatial optimization and refined governance.

Key words: human settlement suitability, nonlinear function, technique for order preference by similarity to ideal solution (TOPSIS), criteria importance through intercriteria correlation (CRITIC), urban block unit