Natural topographic controls on the spatial distribution of poverty-stricken counties in China

Abstract

The spatial distribution pattern of the economic development among counties is an important external representation of a balanced and sustainable regional development in China. The natural topography has been regarded as one of the most important factors that controls the economic development of a county. Moreover, natural topography determines land availability and regional accessibility and further influences the objective environment of wealth creation. On the basis of the digital elevation model (DEM) data and geographic information science (GIS) spatial analysis method, this study utilizes the poverty-stricken counties in China to explore the influential factors of the spatial distribution of county's wealth by considering the natural topographic environment. The indexes of slope gradient, terrain relief, river length and river density are calculated to investigate the spatial relationship between the wealth distribution of counties and their natural topographic condition. Results show that the poverty-stricken counties in China are mainly located on the second Gradient Terrain of the Three Gradient Terrains in the country and are particularly concentrated in the Loess Plateau, Qinling-Daba Mountains, and Yunnan–Guizhou Plateau. These areas are also located near both sides of the traditional Hu Huanyong Population Line of China. Results also show that the complex conditions of the natural topography have a positive driving effect on the spatial distribution of the poverty-stricken counties. By contrast, non-poverty-stricken counties are mainly located in areas with good topographic conditions. A total of 70% of the poverty-stricken counties are characterized by severe topographic condition with an average slope gradient of over 10° calculated from the 90 m cell size DEM. However, only 32% of the non-poverty-stricken counties are characterized by severe topographic condition. In addition, 72% of the poverty-stricken counties have an average terrain relief of over 50 m in a local 3 × 3 cell size (270 m × 270 m), whereas non-poverty-stricken counties accounted for only 34%. Furthermore, the scale effect of the topographical feature derivation from DEM makes the actual topographic condition of the poverty-stricken counties even worse, and the land should be considerably difficult to cultivate. Finally, the primary industry seems to experience difficulty in addressing poverty in poverty-stricken counties. The sheep-flock effect of government-led industries that enter the poverty-stricken counties is expected to be an important policy direction for a balanced regional development. This study provides a reference to the driving force of the natural topographic conditions on the wealth accumulation among counties for a balanced and sustainable regional development.