Research on Village Type Identification and Development Strategy under the Background of Rural Revitalization: A Case of Gaochun District in Nanjing, China

Int J Environ Res Public Health. 2022 Jun 3;19(11):6854. doi: 10.3390/ijerph19116854.

Abstract

In the context of rural revitalization, it is of great significance for the implementation of a Rural Revitalization Strategy to carry out the research on scientifically identifying village types and clarifying the differences and pluralistic trends within villages. Taking Gaochun District of Nanjing in China as an example, this paper constructs an index system of development level and reconstruction intensity from a dynamic and static perspective, uses the polygon area method to calculate the comprehensive score of each index, divides village types based on the combination of development level and reconstruction intensity, and then puts forward the differentiated development strategies of various villages. The results show that the identification method of village types based on combined features is multi-dimensional and comprehensive, and the recognition results are more in line with the objective reality. Villages in Gaochun district have a medium overall development level and high overall reconstruction intensity. There are a large number of low-value villages with development level and high-value villages with reconstruction intensity. According to the three-step strategy of village type identification, the list of characteristic villages, the location of villages and the characteristics of index combination, five village types were identified: the characteristic protection type, the urban-suburban integration type, the agglomeration and upgrading type, the improvement and development type, and the relocation and merger type.

Keywords: China; Gaochun District in Nanjing; development level; development strategy; reconstruction intensity; village type.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China
  • Health Services*
  • Humans
  • Rural Population*

Grants and funding

This research was funded by National Natural Science Foundation of China (41871178), Graduate Research and Innovation Projects of Jiangsu Province (KYCX21_1300) and Natural Resources and Technology Program of Jiangsu Province (KJXM2019005).