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Relief degree of land surface and population distribution of mountainous areas in China

Relief degree of land surface and population distribution of mountainous areas in China Evaluation on the population pressure in the mountainous areas is a necessary condition for the protection and good governance. The evaluation depends on accurate population density assessment. Traditional methods used to calculate population density often adopt the administrative region as a scale for statistical analysis. These methods did not consider the effects of the relief degree of land surface (RDLS) on the population distribution. Therefore they cannot accurately reflect the degree of population aggregation, especially in mountainous areas. To explore this issue further, we took the mountainous areas of China as the research area. China has A total area of 666 km2 can be classified as mountainous area, accounting for 69.4% of the country’s total landmass. The data used in this research included the digital elevation model (DEM) of China at a scale of 1:1,000,000, National population density raster data, the DEM and the national population density raster data. First, we determined the relief degree of land surface (RDLS). Next, we conducted a correlation analysis between the population distribution and the RDLS using the Statistical Package for Social Science (SPSS). Based on the correlation analysis results and population distribution, this new method was used to revise the provincial population density of the mountainous areas. The revised results were used to determine the population pressure of different mountainous areas. Overall, the following results were obtained: (1) The RDLS was low in most mountainous areas (with a value between 0 and 3.5) and exhibited a spatial pattern that followed the physiognomy of China; (2) The relationship between the RDLS and population density were logarithmic, with an R2 value up to 0.798 (p<0.05), and the correlation decreased from east to west; (3) The difference between the revised population density (RPD) and the traditional population density (PD) was larger in the southeastern region of China than in the northwestern region; (4) In addition, compared with traditional results, the revised result indicated that the population pressure was larger. Based on these results, the following conclusions were made: (1) the revised method for estimating population density that incorporates the RDLS is reasonable and practical, (2) the potential population pressure in the southeastern mountainous areas is substantial, (3) the characteristics of the terrain in the high mountainous areas are important for the scattered distribution of the population, and (4) the population distribution of mountainous areas in China should be guided by local conditions, such as social, economic, and topographic conditions. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Mountain Science Springer Journals

Relief degree of land surface and population distribution of mountainous areas in China

Journal of Mountain Science , Volume 12 (2) – Mar 24, 2015

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References (28)

Publisher
Springer Journals
Copyright
Copyright © 2015 by Science Press, Institute of Mountain Hazards and Environment, CAS and Springer-Verlag Berlin Heidelberg
Subject
Earth Sciences; Earth Sciences, general; Geography (general); Environment, general; Ecology
ISSN
1672-6316
eISSN
1993-0321
DOI
10.1007/s11629-013-2937-5
Publisher site
See Article on Publisher Site

Abstract

Evaluation on the population pressure in the mountainous areas is a necessary condition for the protection and good governance. The evaluation depends on accurate population density assessment. Traditional methods used to calculate population density often adopt the administrative region as a scale for statistical analysis. These methods did not consider the effects of the relief degree of land surface (RDLS) on the population distribution. Therefore they cannot accurately reflect the degree of population aggregation, especially in mountainous areas. To explore this issue further, we took the mountainous areas of China as the research area. China has A total area of 666 km2 can be classified as mountainous area, accounting for 69.4% of the country’s total landmass. The data used in this research included the digital elevation model (DEM) of China at a scale of 1:1,000,000, National population density raster data, the DEM and the national population density raster data. First, we determined the relief degree of land surface (RDLS). Next, we conducted a correlation analysis between the population distribution and the RDLS using the Statistical Package for Social Science (SPSS). Based on the correlation analysis results and population distribution, this new method was used to revise the provincial population density of the mountainous areas. The revised results were used to determine the population pressure of different mountainous areas. Overall, the following results were obtained: (1) The RDLS was low in most mountainous areas (with a value between 0 and 3.5) and exhibited a spatial pattern that followed the physiognomy of China; (2) The relationship between the RDLS and population density were logarithmic, with an R2 value up to 0.798 (p<0.05), and the correlation decreased from east to west; (3) The difference between the revised population density (RPD) and the traditional population density (PD) was larger in the southeastern region of China than in the northwestern region; (4) In addition, compared with traditional results, the revised result indicated that the population pressure was larger. Based on these results, the following conclusions were made: (1) the revised method for estimating population density that incorporates the RDLS is reasonable and practical, (2) the potential population pressure in the southeastern mountainous areas is substantial, (3) the characteristics of the terrain in the high mountainous areas are important for the scattered distribution of the population, and (4) the population distribution of mountainous areas in China should be guided by local conditions, such as social, economic, and topographic conditions.

Journal

Journal of Mountain ScienceSpringer Journals

Published: Mar 24, 2015

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