陕西省人口资源分布格局变化趋势及驱动力研究

发布时间：2018-11-14 15:24

【摘要】：基于两期人口普查数据,运用ESDA方法,分析陕西省2000年至2010年人口分布变化空间格局与自然、经济、社会驱动力。将驱动力进行多元回归并进行空间栅格拟合,得出不同尺度的人口变化趋势。结果表明:陕西省人口变化北部快南部慢,全局集聚程度提高,人口变化率局部集聚中部高北部低,人口重心北移,在人口变化趋势与植被变化的关系上多数地区人口对植被有正向影响但南部少数区县为负向;建立多元回归方程能近似的模拟人口变化规律,人口的增长多在河谷地带与高速公路沿线,地势平坦的区域经济中心与交通便利区域。趋势拟合显示,自然因素本身并不在短时间内决定人口迁移,但受到经济拉力作用时,自然条件较差地区往往人口减少会较快。根据不同驱动因子的作用,将其按主成分分析法和系统聚类法进行分类,为后续的因子选取提供依据。
[Abstract]:Based on the data of two population censuses and using ESDA method, this paper analyzes the spatial pattern and natural, economic and social driving forces of population distribution changes from 2000 to 2010 in Shaanxi Province. The driving force is regressed and the spatial grid fitting is carried out, and the trend of population change in different scales is obtained. The results show that population change in the north of Shaanxi Province is fast and slow in the south, the overall concentration degree is increased, the population change rate is local concentration, the central part is high and the northern part is low, and the population center of gravity moves northward. In the relation between population change trend and vegetation change, population has positive influence on vegetation in most areas, but it is negative in a few counties in southern China. The multivariate regression equation can approximate simulate the law of population change, the population growth is mostly along the river valley and highway, flat regional economic center and convenient traffic area. Trend fitting shows that natural factors themselves do not determine population migration in a short period of time, but when affected by economic pull, the population decreases rapidly in areas with poor natural conditions. According to the function of different driving factors, it is classified by principal component analysis method and systematic clustering method, which provides the basis for the subsequent selection of factors.
【作者单位】：陕西师范大学旅游与环境学院;陕西师范大学西北国土资源研究中心;
【基金】：国家自然科学基金项目(41071057) 教育部人文社会科学重点研究基地重大项目(2009JJD770025) 陕西省科学计划自然基金项目(2011JQ5014) 陕西省社会科学基金项目(11E045)资助
【分类号】：C922

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