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Articles

Spatiotemporal Evolution of Specialized Villages in the Yellow River Basin and Its Influencing Factors

, , , , &
Pages 217-234 | Published online: 20 Sep 2021
 

Abstract

We collected information on 35,353 specialized villages (SVs) from the nine provinces in the Yellow River Basin from 2008 to 2014. Using the nearest neighbor index (NNI), exploratory spatial data analysis (ESDA), kernel density estimation (KDE), and the geography detector (geodetector) method, we demonstrated the spatiotemporal evolution of these 35,353 SVs and analyzed the influencing factors that triggered change. We arrived at the following conclusion: (1) In the upstream area of the Yellow River Basin, these SVs were fewer in number and more dispersed, and the distribution of these SVs presented in a zonal region. The distribution of SVs in the middle and lower reaches was dense and blocky. The average observation distance of the SVs in the Yellow River Basin decreased from 3.17 km in 2008 to 2.74 km in 2014, and Moran’s I in the county level increased from 0.2640 in 2008 to 0.3449 in 2014, with the degree of concentration increasing. (2) These SV agglomerations in the Yellow River Basin were located in the Guanzhong region in the middle reaches and in the north Shandong province in the downstream region. The agglomeration degree in Guanzhong region was the highest, and the change from 2008 to 2014 grew increasingly stronger. The hotspot concentrated areas were distributed primarily in the downstream region of Shandong Province, the middle reaches of the Weihe Plain, and the Longdong Loess Plateau. The cold-spot concentrated areas were distributed mainly along the borders of Qinghai and Gansu, Inner Mongolia, and Shanxi province. (3) The natural environmental factors always had a great impact on the distribution of SVs, but this influence had decreased. In contrast, the local economic development level also played a very important role in the formation and development of SVs, and the influence of market conditions and technical conditions was gradually strengthening. The driving factors for the agglomeration of SVs in different regions were different and the differences were gradually increasing. The development model of SV was still an effective model to promote China’s Rural Revitalization. In the future, the research on the formation mechanism of SV agglomeration should be strengthened. According to the fact of regional development, the spatial interface theory provides a new path and thought to better study the internal mechanism of SV agglomeration.

Additional information

Funding

Funding for this research came from the National Science Foundation of China (NSFC Grants 42071220, 42001190).

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