Topographical relief is a key factor that limits population distribution and economic development in mountainous areas. The limitation is especially apparent in the mountain-plain transition zone. Taking the transitio...Topographical relief is a key factor that limits population distribution and economic development in mountainous areas. The limitation is especially apparent in the mountain-plain transition zone. Taking the transition zone between the Qinling Mountains and the North China Plain(i.e. the mountainous area in western Henan Province) as an example and based on the 200-m resolution DEM data, we used the mean change-point analysis to determine the optimal statistical unit for topographical relief, and thereafter extracted the relief degree. Taking the 1:100,000 land use data, township population and county-level industrial data, population and economic spatial models were constructed, and 200-m resolution grid population and economic density maps were generated. Afterwards, statistical analysis was carried out to quantitatively reveal the impact of topographical relief on population and economy. In addition, the impacts of other topographical factors were discussed. The results showed the following.(1) The relief degree in western Henan is generally low, where 58.6% of the regional topography does not exceed half the height of a reference mountain(relative elevation ≤250 m). Spatially, the relief degree is high in the west while low in the east, and high in the middle while low in the north and south. There is a positive correlation between relief degree and elevation, and a much stronger correlation between relief degree and slope.(2) The linear fitting degree between the population and economic validation data and the corresponding simulation data are 0.943 and 0.909, respectively, indicating that the spatialized results can reflect the actual population and economic distribution.(3) The impact of topographical relief on population and economy was stronger than that of other topographical factors. The relief degree showed a good logarithmic fit relationship with population density(0.911) and economic density(0.874). Specifically, 88.65% of the population lives in areas where the topographical relief is ≤0.5 and 88.03% of the gross regional product was from areas where the relief is ≤0.3. Compared with the population distribution, the economic development showed an obvious agglomeration trend towards low relief areas.展开更多
基金National Natural Science Foundation of China,No.41671090National Basic Research Program(973 Program),No.2015CB452702.
文摘Topographical relief is a key factor that limits population distribution and economic development in mountainous areas. The limitation is especially apparent in the mountain-plain transition zone. Taking the transition zone between the Qinling Mountains and the North China Plain(i.e. the mountainous area in western Henan Province) as an example and based on the 200-m resolution DEM data, we used the mean change-point analysis to determine the optimal statistical unit for topographical relief, and thereafter extracted the relief degree. Taking the 1:100,000 land use data, township population and county-level industrial data, population and economic spatial models were constructed, and 200-m resolution grid population and economic density maps were generated. Afterwards, statistical analysis was carried out to quantitatively reveal the impact of topographical relief on population and economy. In addition, the impacts of other topographical factors were discussed. The results showed the following.(1) The relief degree in western Henan is generally low, where 58.6% of the regional topography does not exceed half the height of a reference mountain(relative elevation ≤250 m). Spatially, the relief degree is high in the west while low in the east, and high in the middle while low in the north and south. There is a positive correlation between relief degree and elevation, and a much stronger correlation between relief degree and slope.(2) The linear fitting degree between the population and economic validation data and the corresponding simulation data are 0.943 and 0.909, respectively, indicating that the spatialized results can reflect the actual population and economic distribution.(3) The impact of topographical relief on population and economy was stronger than that of other topographical factors. The relief degree showed a good logarithmic fit relationship with population density(0.911) and economic density(0.874). Specifically, 88.65% of the population lives in areas where the topographical relief is ≤0.5 and 88.03% of the gross regional product was from areas where the relief is ≤0.3. Compared with the population distribution, the economic development showed an obvious agglomeration trend towards low relief areas.
