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| 基于空间相关性的高原山区村庄分类与布局优化 |
| Classification and layout optimization of plateau mountain villages based on spatial correlation |
| 投稿时间：2023-06-05 修订日期：2023-09-12 |
| DOI：10.13254/j.jare.2023.0355 |
| 中文关键词: 村庄分类，生态敏感性，发展潜力，建设适宜性，空间相关性，承载力，布局优化 |
| 英文关键词: village classification, ecological sensitivity, development potential, construction suitability, spatial correlation, bearing capacity, layout optimization |
| 基金项目:国家自然科学基金项目（41761081）；云南省哲学社会科学规划项目（PY202129，ZD202218）；云南省教育厅科学研究基金项目（2023J0115） |
| 作者 | 单位 | E-mail | | 冯怡翔 | 昆明理工大学国土资源工程学院, 昆明 650093
智慧矿山地理空间信息集成创新重点实验室, 昆明 650093
云南省高校自然资源空间信息集成与应用科技创新团队, 昆明 650211 | | | 陈国平 | 昆明理工大学国土资源工程学院, 昆明 650093
智慧矿山地理空间信息集成创新重点实验室, 昆明 650093
云南省高校自然资源空间信息集成与应用科技创新团队, 昆明 650211 | 115432640@qq.com | | 赵俊三 | 昆明理工大学国土资源工程学院, 昆明 650093
智慧矿山地理空间信息集成创新重点实验室, 昆明 650093
云南省高校自然资源空间信息集成与应用科技创新团队, 昆明 650211 | | | 林伊琳 | 昆明理工大学国土资源工程学院, 昆明 650093
智慧矿山地理空间信息集成创新重点实验室, 昆明 650093
云南省高校自然资源空间信息集成与应用科技创新团队, 昆明 650211 | | | 王荣耀 | 昆明理工大学国土资源工程学院, 昆明 650093
智慧矿山地理空间信息集成创新重点实验室, 昆明 650093
云南省高校自然资源空间信息集成与应用科技创新团队, 昆明 650211 | |
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| 中文摘要: |
| 村庄分类是编制村庄规划和制定发展策略的重要基础。本研究以典型高原山区——云南省玉龙县为研究对象，首先运用层次分析法构建“三评价”（生态敏感性评价、发展潜力评价、建设适宜性评价）指标体系；其次对“三评价”进行空间相关性分析，得到初始村庄分类结果；最后运用状态空间法计算村庄承载力，对初始村庄分类进行修正，得到最终的村庄分类。结果表明：研究区村庄具有显著的高原山区空间分布异质性，其“三评价”空间自相关系数分别为0.343、0.253、0.110；60%以上村庄处于可承载状态，承载力较高区域集中于研究区的东南、西北和中部地区；经综合承载力测算修正后，特色保护类占 23%，城郊融合类占4%，搬迁撤并类占15%，集聚提升类占40%，暂不明确类占18%。针对不同类型的村庄，结合承载力的计算结果，提出布局优化策略。研究结果可为乡（镇）级国土空间规划编制和“多规合一”实用性村庄规划实施提供方法参考和依据。 |
| 英文摘要: |
| Village classification is an important foundation for preparing village planning and formulating development strategies. This study takes a typical plateau mountain area—Yulong County, Yunnan Province as the research object. First, the analytical hierarchy process is used to build a“three evaluations”（ecological sensitivity, development potential, and construction suitability）indicator system. Second, spatial correlation analysis of the“three evaluations”was carried out to obtain the initial village classification results. Finally, the state space method was used to calculate the village bearing capacity, which could be used to correct the initial village classification. Thus, the final village classification could be obtained. The results show that a significant plateau mountain space distribution of heterogeneity was shown in the villages of the research area, and the spatial autocorrelation coefficients of the“three evaluations”were 0.343, 0.253, and 0.110, respectively; more than 60% of the villages were in a bearing state and the higher bearing capacity was concentrated in the southeast, northwest, and central regions of the research area. After the comprehensive carrying capacity was calculated and corrected, the special protection category accounted for 23%, the suburban integration category accounted for 4%, the relocation and withdrawal category accounted for 15%, the agglomeration and promotion category accounted for 40%, and the temporary unclear category accounted for 18%. For different types of villages, the layout optimization strategy should be proposed according to the carrying capacity calculation results.The results of this research can provide a reference and basis for the formulation of township（town）-level territorial spatial planning and the implementation of“multi-planning”practical village planning. |
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