标题: A large-scale village classification model for tailored rural revitalization: A case study of Hubei province, China

作者: Pan, YP (Pan, Yupiao); Zhao, X (Zhao, Xiang); Zhang, YQ (Zhang, Yiqing); Luo, HF (Luo, Haifeng)

来源出版物: JOURNAL OF GEOGRAPHICAL SCIENCES 卷: 34 期: 12 页: 2364-2392 DOI: 10.1007/s11442-024-2296-x Published Date: 2024 DEC

摘要: A comprehensive understanding of village development patterns and the identification of different village types is crucial for formulating tailored planning for rural revitalization. However, a model for large-scale village classification to support tailored rural revitalization planning is still lacking. This study aims to develop a large-scale village classification model using the Gaussian Mixture Models to support tailored rural revitalization efforts. Firstly, we propose a multi-dimensional index system to capture the diverse features of massive villages. Secondly, the GMM clustering algorithm is applied to identify distinct village types based on their unique features. The model was employed to classify the 25,409 villages in Hubei province in China into four classes. Villages in these classes exhibit discernible differences in spatial distribution, topography, location, economic development level, industrial structure, infrastructure, and resource endowment. In addition, the GMM-based village classification model demonstrates a high level of agreement with evaluations made by planning experts, confirming its accuracy and reliability. In the empirical study, our model achieves an overall accuracy of 95.29%, signifying substantial concordance between the classifications made by planning experts and the results generated by our model. Based on the identified features, tailored paths are proposed for each village class for rural revitalization efforts.

作者关键词: rural revitalization; village classification; Gaussian mixture models; rural regional development; Hubei province

KeyWords Plus: TYPOLOGY; AREAS; IDENTIFICATION

地址: [Pan, Yupiao; Zhao, Xiang; Zhang, Yiqing; Luo, Haifeng] Wuhan Univ, Sch Resources & Environm Sci, Wuhan 430079, Peoples R China.

通讯作者地址: Zhao, X (通讯作者)，Wuhan Univ, Sch Resources & Environm Sci, Wuhan 430079, Peoples R China.

电子邮件地址: yupiaopan@whu.edu.cn; zhaoxiang@whu.edu.cn

影响因子：4.3