中国贫困县空间格局与地形的空间耦合关系

Spatial Distribution of Poverty-Stricken Counties in China and Their Natural Topographic Characteristics and Controlling Effects

以90 m分辨率全国DEM数据和GIS空间分析方法为基础,以中国贫困县为研究对象,探讨影响县域财富空间分布的地形环境动因。通过计算地面坡度、地形起伏度、河网长度与密度等,探讨地形因子与县域财富分布的空间耦合关系。结果表明,贫困县主要位于我国三大地形阶梯的第二阶梯,以黄土高原、秦巴山地、云贵高原最为集中,该区域也位于胡焕庸人口分界线两侧附近。研究表明,复杂的地形条件对贫困县的空间分布具有相当强度的正向驱动作用。其中,70%的贫困县位于地面平均坡度在10°以上的区域;72%的贫困县位于3×3邻域窗口内(270 m×270 m)地形起伏度达50 m以上的区域。值得注意的是,山区地域90 m分辨率DEM数据在相当程度上弱化了坡度和地形起伏度计算结果,而贫困县地形环境在真实情况下更为恶劣,严重阻碍经济发展,进一步印证地形条件对贫困县分布的影响。可见,贫困摘帽已不能依赖先天不足的第一产业,政府主导性产业向贫困县地域的强势布局,及由此产生可能的羊群效应有望推动区域平衡发展。

On the Bases of DEM data and GIS spatial analysis method, this paper takes the poverty-stricken counties in China as the case to explore the influential factors of the spatial distribution of the county＇s wealth by natural topographic environment. The indexes of slope, terrain relief based on DEM and river length and river density based on DLG are calculated to investigate the spatial relationship between the distribution of county wealth and the natural topographic condition. The results show that the poverty-stricken counties in China are mainly located on the second Gradient Terrain of the Three Gradient Terrains in China and particularly concentrated in areas of Loess Plateau, Qinling-Daba Mountains, Yunnan-Guizhou Plateau. These areas are also located near the both sides of the traditional Hu Line of China. The results show that the complex conditions of natural topography have a positive driving effect on the spatial distribution of poverty-stricken counties, while the non-poverty counties are mainly located in the areas with better topographic conditions. Among all counties, 70% of the poverty-stricken counties are suffered by a severe topographic condition with an average slope more than 10° calculated from 90 m cell size DEM, while only 32% of the non-poor counties could be found for that severe topographic condition. In addition, 72% of the poverty-stricken counties accompany with an averageterrain relief of more than 50m in a local 3 ×3 cell size （270m×270m）, while non-poor counties accounted for only 34%. The distribution of water resources has limited influence on the distribution of poor counties. Furthermore, the calculated results of slope and terrain relief could be weakened to a certain extent because the scale effect of terrain index calculation from DEM with 90 m cell size in the mountainous area. This scale effect makes the real topographic condition of the poverty-stricken counties even worse, and the land should be more difficult to cultivate. This further demonstrates that the natural topographic condition exists significant impact on the wealth creation of the county, especially controls the spatial distribution of poor counties. Finally, the primary industry seems difficult to address poverty in poverty- stricken counties. The shepherding effect of government-led industries enter into poor counties is expected to be an important policy direction for a balanced regional development. This paper can provide a reference to the driving force of the natural topographic conditions on county＇s wealth accumulation for the balanced and sustainable development of the region.