摘要
本文以1996年、2000年2、003年、2006年中国29省(市、区)(上海市和西藏数据缺失)农村生活能源为研究对象,应用因子分析、聚类分析和回归分析,借助SPSS和ArcGIS软件,对中国农村生活能源消费空间格局及空间格局变化的影响因素进行分析探讨。结果表明:在1996-2006年间,我国农村生活能源消费水平的空间格局基本形成以华北-西南地区为轴线向两边逐渐递减的态势,且趋势愈加明显;华北地区和西南地区高水平特点不断强化;轴线两侧区域差异不断扩大的同时,各自区域内的一致性趋向明显。经过经济发展水平、人口分布与能源消费水平的叠加显示:西北地区属于贫困型低消费地区,华北和西南地区属于人口规模型高消费地区,东南沿海地区属于高效型低消费地区。回归分析结果表明:影响农村生活能源消费空间格局变化的首要因素为能源消费强度,其次是能源消费增长速度和能源消费结构,其中前两者为负向影响,后者为正向影响。
In this article,the change in spatial distribution and influencing factors of rural energy consumption in 29 provinces (cities, districts) ( Data absence of Shanhai and Tibet) of China in 1996,2000,2003 and 2006 are analyzed by using factor analysis, cluster analysis and regression analysis methods in SPSS16.0 statistical analysis software. The article obtained following results: the decreasing trend of rural energy consumption spatial pattern is more and more obvious from the middle China to both sides by the axis of North China -Southwest China from 1996 to 2006; high-level features in North China and the Southwest China had increasingly strengthened high rural energy consumption level; while regional differences in both sides of the axis enlarged, each region apparently had the trend of consistency. Comprehensive eomparison among economic development level, population distribution and energy consumption distribution shows that the Northwest China is the low consumption area of poverty type, North China and Southwest China are the high consumption of areas of scale population type, and the coastal area of Southeast China belongs to the low consumption of high-efficient type. According to the results of regression analysis, the main influencing factors on spatial distribution of rural energy consumption are variance ratio of intensity factor, structure factor and gross factor; the former two factors influence rural energy consumption negatively and the latter positively.
出处
《中国人口·资源与环境》
CSSCI
北大核心
2010年第4期29-34,共6页
China Population,Resources and Environment
基金
国家哲学社会科学基金重大项目(项目编号:04-ZD018)
关键词
农村生活能源
消费水平
空间格局
影响因素
rural household energy
consumption level
change of spatial distribution
influencing factor