Driving forces of the villages hollowing based on geographically weighted regression model: a case study of Longde County, the Ningxia Hui Autonomous Region, China

Chenxi Li () and Kening Wu ()
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Chenxi Li: China University of Geosciences (Beijing)
Kening Wu: China University of Geosciences (Beijing)

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2017, vol. 89, issue 3, No 4, 1059-1079

Abstract: Abstract The reconstruction of hollowed villages comes into being an important measure for taking targeted measures in poverty alleviation in China. Many scholars studied hollowed villages from the geographical perspective. However, from the perspective of the village collective economic development, the quantitative analysis about the formation of hollowed villages was few. The present research analyzed the driving force of the hollowed villages’ formation process. Based on village collective economy development status survey data of Longde County, the Ningxia Hui Autonomous Region, China, we chose eight factors from the geographic, economic, resources, traffic, demographic and geological conditions by using the geographically weighted regression (GWR) model. Moreover, we drew driving force factors outlines of different figures’ spatial results by using ArcGIS 10.1. The results showed that: (1) GWR model can reveal much more profound spatial differential of driving force than that by the traditional OLS method; (2) driving factors of hollowed village’ rate were various among different administrative villages, showing an obvious spatial differential; (3) according to the main factors driving hollowed villages’ formation, we proposed differentiated strategies to control hollowing village problem in Longde County.

Keywords: Village; Hollowing; Geographically weighted regression (GWR); Driving force; China (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s11069-017-3008-y

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