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[1]SHU Bang-rong,QU Yi,LI Yong-le,et al.Driving Forces of Rural Settlement Change of Township at Various Resolution—A Case Study of Liuhe Township, Taicang County[J].Research of Soil and Water Conservation,2014,21(02):127-132.

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Driving Forces of Rural Settlement Change of Township at Various Resolution—A Case Study of Liuhe Township, Taicang County

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 21 Number of periods: 2014 02 Page number: 127-132 Column: Public date: 2014-04-28

Title:: Driving Forces of Rural Settlement Change of Township at Various Resolution—A Case Study of Liuhe Township, Taicang County

Author(s):: SHU Bang-rong¹, QU Yi^2,3, LI Yong-le⁴, YONG Xin-qin¹, MEI Yan¹; 1. School of Geodesy and Geomatics, Jiangsu Normal University, Xuzhou, Jiangsu 221116, China;
2. Institute of Geographic and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;
3. University of Chinese Academy of Sciences, Beijing 100049, China;
4. College of Public Management, Nanjing University of Finance & Economics, Nanjing 210023, China

Keywords:: land use change; rural settlement area; driving forces; resolution of raster data; logistic regression model

CLC:: F301.24

DOI:: -

Abstract:: Scale plays a key role in the studies of driving mechanism of rural settlement changes when raster data were used with the aid of geographic information system. This paper thus explored the impacts of various scales on the driving force analysis of rural settlement changes and the related driving mechanism in the developed township of Liuhe Township, Taicang County by the method of binary logistic regression model. The results showed that the driving force model best fit the data from 1996 to 2008 at the resolution of 10 m, farmers’ net income per capita was found to be the impetus of the spatial adjustment of rural settlements, and attractiveness of roads could also promote the spatial adjustment of rural settlements for convenient transportation. Population density, agricultural production value per area, arable land per capita, basic farmland and distance to main irrigation system had impacts on increase of rural settlement area, while industrial output per area, residential area per capita and the distance to town had merely impacts on decrease of rural residents. Our study illustrated that the impacts of various resolutions on the accuracy, interpretation power and goodness of fit of the constructed model, which further influenced the identification of driving factors and their substance. Therefore, resolution of raster data should be decided in the initial period of research before further analysis. Additionally, measures for the optimization of rural settlements include development of rural economy, increasing farmers’ income, planning of rural village roads, construction of exit and compensation mechanism of rural settlements, and protection of the basic farmland.

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