Abstract

The phenomenon of village abandonment has occurred during the past decades as an extreme result of rural migration in many developing countries. It has brought about many socio-economic and environmental problems, such as farmland abandonment, decapitalization of properties, rural economic stagnation or decline, disappearance of rural settlements, secondary vegetation succession, landscape homogenization and increasing risks of wild fires. Village abandonment has been happening widely in mountainous areas of China in response to increasing urbanization and industrialization. But the spatial patterns and determinants of village abandonment are not well understood. The aim of this study is to investigate the spatial patterns of abandoned villages using Kernel Density analysis, and to identify determinants of village abandonment using the Ordinary Least Square regression based on a case study in Pucheng County, Southeast China. Our results show that abandoned villages mainly agglomerate in some scattered kernels with higher elevations and poor accessibility or with thriving local industrialization and Insitu urbanization. These results corroborate previous findings elsewhere. Research on determinants identifies that public goods provision and accessibility are the most important predictors to explain substantial variations in village abandonment. Remote villages with poor public goods provision (such as road, healthcare and education) and poor accessibility are most possibly abandoned. With projected increasing concentration of elementary schools in townships and cities and rising urbanization, village abandonment is likely to increase in remote rural areas. However, natural conditions are surprisingly the least significant determinants, which is contrary to previous studies. In addition, hamlet size and the progress on characteristic agriculture have some negative impacts on village abandonment. Finally, several research prospects and policy implications on village abandonment have been proposed to promote future studies and rural sustainability respectively.

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