Research on village classification and development based on particle swarm optimization model: Xiecun Township, Yuanping City, in Shanxi Province, China

Xiaoting Ma, Nangkula Utaberta, Nadzirah Zainordin

Article ID: 2603
Vol 8, Issue 1, 2024

VIEWS - 398 (Abstract) 165 (PDF)

Abstract


China’s village development confronts substantial challenges, inefficient land use due to the scattered village layout, sluggish development of village industries, and lack of proper planning for village development and construction, etc. Scientific classification of villages and village-based policy is the key to address these challenges. This study employs cell phone signaling big data to construct a population flow model based on particle swarm optimization algorithm This model takes into account spatial driving force and social connection strength as dual conditions. Also, it analyzes the settlement redistribution optimization scheme under the model through empirical research on Xiecun Township of Yuanping City, Shanxi Province, in order to classify villages scientifically and apply different strategies to village development according to the classification results. The findings of the study indicate that the area characterized by the densest distribution of optimized particle clusters, with good land conditions and high economic income, are classified as “cluster-enhanced villages”. Regions with the densest distribution of the initial particle distance factor and the densest distribution of optimized particle clusters are closer to the urban centers, which are better positioned to take advantage of the city’s financial and technological resources and continuously improve the added value of agricultural products, so they are classified as “peri-urban integrated villages”. Areas characterized by sparse distribution of optimized particle clusters need to actively cultivate the advantageous and characteristic industries in the countryside, and bolster transportation conditions and the protection of local culture, so as to realize the green development of urban and rural regional economy. Such areas are classified as “characteristic conservation villages”. In areas without optimized particle cluster distribution or areas with extremely sparse distribution of optimized particle clusters, the rational layout of urban and rural settlement spatial organization should be vigorously promoted, with emphasis on the enhancement of ecological environment, and they are classified as “relocated and annexed villages”. According to the results of village classification, corresponding strategies to promote the development of different types of villages are proposed in terms of spatial optimization, industrial upgrading and planning.

Keywords


big data; village classification; development strategies; particle swarm optimization

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DOI: https://doi.org/10.24294/jipd.v8i1.2603

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