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中国森林乡村的多尺度分异特征与分区优化
引用本文:孔雪松,府梦雪,孙建伟,崔家兴.中国森林乡村的多尺度分异特征与分区优化[J].地理研究,2022,41(7):2051-2064.
作者姓名:孔雪松  府梦雪  孙建伟  崔家兴
作者单位:1.武汉大学资源与环境科学学院,武汉 4300792.贵州师范大学地理与环境科学学院,贵阳 5500253.华中师范大学地理过程分析与模拟湖北省重点实验室,武汉 430079
基金项目:国家自然科学基金项目(41871182、41961031);;国家重点研发计划项目(2018YFD1100801);;贵州省科技计划项目(黔科合基础-ZK[2022]一般313);
摘    要:国家森林乡村建设是实施乡村振兴战略和改善农村人居环境的重要措施,但森林乡村在不同尺度的分异特征及优化方向尚不明晰。本文综合运用探索性空间数据分析、耦合度模型和Voronoi图分析等研究方法,从全国、区域和行政尺度分析了国家森林乡村空间格局、数量规模和内部分异特征,并基于森林乡村与人口耦合关系及乡村可达类型识别,分析了全国森林乡村的分区格局及其优化方向。结果表明:全国森林乡村密度具有明显的东高西低分异特征,长江三角洲地区是森林乡村高密度集中分布最大的连片区。基于县域单元的省域森林乡村泰尔指数差异较大,东南区域森林乡村分布相对均衡,西南和东北区域内部差异显著。森林乡村空间可达性呈现自东向西的梯度递减,森林乡村与人口密度的耦合类型分布具有较强的内部分异性。文章基于森林乡村可达类型与耦合分区的组合分析,将全国划分为重点发展区、特色挖掘区、集聚提升区、适度引导区和功能转型区五类,明确了不同类型区森林乡村建设的重点方向,将为面向乡村振兴的全国森林乡村建设与分区优化提供决策依据。

关 键 词:森林乡村  空间分异  耦合分析  Voronoi图  分区优化  
收稿时间:2021-07-19

Multi-scale differentiation characteristics and optimization zones of forest villages in China
KONG Xuesong,FU Mengxue,SUN Jianwei,CUI Jiaxing.Multi-scale differentiation characteristics and optimization zones of forest villages in China[J].Geographical Research,2022,41(7):2051-2064.
Authors:KONG Xuesong  FU Mengxue  SUN Jianwei  CUI Jiaxing
Institution:1. School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China2. School of Geographical and Environmental Science, Guizhou Normal University, Guiyang 550025, China3. Hubei Provincial Key Laboratory for Geographical Process Analysis and Simulation, Central China Normal University, Wuhan 430079, China
Abstract:National forest villages construction is an important path to promote the implementation of rural revitalization strategy and the improvement of rural living environment; however, the differentiation characteristics of forest villages at different scales and the optimization directions at the national scale are unclear. This study analyzed the characteristics in spatial pattern, quantitative scale, and internal differentiation of forest villages at national, regional, and administrative scales by using the kernel density estimation, the Lorenz curve, and the Theil index. The coupling degree between forest villages and population, and the spatial accessibility of forest villages were explored based on the coupling model and the Voronoi diagram, which provided important information for optimization zones of forest villages. The results showed that the density of forest villages in China has obvious differentiation characteristics of high density in the east and low density in the west, and the Yangtze River Delta is the largest contiguous area with high density of forest villages. There was a significant difference of provincial Theil index of forest villages based on county units. The distribution of forest villages was relatively balanced in the southeast region, whereas the difference was great in the southwest and northeast regions. Xinjiang, Tibet, Qinghai, and the three provinces of northeast China had high Theil index values, and the forest villages in these regions showed typical characteristics of small agglomeration and large dispersion. The spatial accessibility of forest villages had a high spatial correlation with the Hu Huanyong Line (hereafter Hu Line), presenting a pattern of high in the east and low in the west bounded by the Hu Line. Although the distribution of forest villages and population density showed a similar pattern of high in the east and low in the west, the spatial heterogeneity of the coupling degrees between east and west was obviously stronger. The paper divided the whole country into five types, namely, key development areas, characteristic mining areas, agglomeration and upgrading areas, moderate guidance areas, and functional transformation areas, based on the combination analysis between coupling degree and spatial accessibility. The key optimization directions of different zones were proposed. The results would provide valuable information for the construction of national forest villages and the optimization paths under the rural revitalization strategy in China.
Keywords:forest villages  spatial heterogeneity  coupling analysis  Voronoi diagram  zoning optimization  
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