基于POI数据和引力模型的村庄分类方法研究
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国家自然科学基金青年基金项目(41901259)


Village Classification Method Based on POI Data and Gravity Model
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    摘要:

    村庄分类是实施乡村振兴规划的重要前提,是科学合理分配公共资源的基础。本文以新郑市为例,从乡村主体、区位条件、资源禀赋、产业基础、生活网络5方面构建乡村振兴潜力评价指标体系,并借助POI数据和引力模型分析村庄与周围地理实体间的空间相互作用,最后基于乡村振兴潜力评价成果和村庄所受空间作用效应,将村庄划分为城郊融合类、集聚提升类、规模控制类、搬迁撤并类4类。研究表明:新郑市乡村振兴潜力整体较好,但村庄发展已初显两极化态势;新郑市拥有28个城郊融合类村庄、73个集聚提升类村庄、78个搬迁撤并类村庄和141个规模控制类村庄,占比分别为8.75%、22.81%、24.38%、44.06%;总的来说,新郑市未来乡村振兴发展工作应着重关注西北部和中南部地区,需注重分类施策、分步推进。

    Abstract:

    Village classification is an important prerequisite for the implementation of the village revitalization plan. It is a scientific and rational allocation of public basic resources. It is of great theoretical and practical significance to carry out research on county village classification. A rural revitalization potential evaluation index system was built from five aspects: rural main body, location conditions, resource endowment, industrial foundation, and living network. The POI data and gravity model were used to analyze the spatial effect of the village. Finally, based on the evaluation results of rural revitalization potential and the spatial effects of villages, the villages were divided into four types of villages: urbansuburban integrated villages, agglomeration villages, scalecontrolled villages, and relocated villages. The results showed that revitalization potential of rural in Xinzheng City was good, but the village development began to show a polarization. Xinzheng City had 28 urbansuburban integrated villages, 73 agglomeration villages, 78 relocated villages and 141 scalecontrolled villages, each accounting for 8.75%, 22.81%, 24.38% and 44.06%, respectively. In general, the future rural revitalization and development of Xinzheng City should focus on the northwest and central southern regions, and it needed to implement policies by stages and proceed step by step.

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陈伟强,代亚强,耿艺伟,高涵,马月红.基于POI数据和引力模型的村庄分类方法研究[J].农业机械学报,2020,51(10):195-204. CHEN Weiqiang, DAI Yaqiang, GENG Yiwei, GAO Han, MA Yuehong. Village Classification Method Based on POI Data and Gravity Model[J]. Transactions of the Chinese Society for Agricultural Machinery,2020,51(10):195-204.

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  • 收稿日期:2020-02-11
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  • 在线发布日期: 2020-10-10
  • 出版日期: 2020-10-10