Abstract
The keys to realizing spatial restructuring in rural areas are the optimization of the spatial pattern of rural settlements and the integration of rural resources. Based on a 2015 Google Earth remote sensing image, this study employed kernel density estimation (KDE), the minimum cumulative resistance (MCR) method, and a logistic regression model to apply quantitative analysis to the spatial distribution characteristics and influencing factors of a rural area. The results revealed that the density of rural settlements is significantly spatially different in Baota District; the density core area in the district was located in the valley area with industrial agglomeration. Rural settlements in Baota District were located near the county seat and township seat, near a river, farmland and county-level road, on sunny slopes. Traffic accessibility to the townships had a greater impact on the spatial distribution of rural settlements than the traffic accessibility to the county. Thus, county-level road development plays a more important role in the optimization of town-village systems. Hence, we suggest constructing a complete transportation network system in the optimization of the town-village spatial pattern in the county, thereby improving the central service functions of towns to strengthen the spatial connection between townships and the central agglomeration effects of towns.
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