摘要
GDP是社会经济发展、区域规划和资源环境保护的重要指标之一。然而,传统以各级行政单元为主的GDP统计资料无法显示区域内部GDP的差异,尝试通过GDP空间化来解决这个问题,以满足资源环境研究领域对空间型社会经济数据的需求。在分析总结国内外社会经济数据空间化技术方法的基础上,第一产业基于土地利用数据建模、第二产业和第三产业基于DMSP/OLS与土地利用数据结合生成的土地灯光参数建模。为提高模型质量,全国按照省级行政边界分区,将因变量GDP分产业分区建模,第一产业绝大部分区域的模型精度在0.7～0.95之间,第二产业和第三产业绝大部分区域的模型精度在0.8～0.98之间。通过与其他GDP空间化技术和结果的比较分析,本研究中的GDP空间化方法无论是模型精度还是GDP密度分布结果都具有一定的优势。生成的GDP密度图能较完整地反映全国GDP分布细节以及宏观分布特征,可为将来经济策略和发展路线的绘制提供一定依据。
GDP is a key indicator of socioeconomic development,urban planning,and environmental protection,accurate estimates of the magnitude and spatial distribution of economic activity have many useful applications in resources and environmental sciences.Developing alternative methods may prove to be useful for making estimates of gross domestic product when other measures are of suspect accuracy or unavailable.Based on the summary and analysis of existing economic activity spatialization approaches,this paper explored the potential for spatializing GDP through China using night-time satellite imagery（DMSP/OLS） and land-use data.In creating the GDP linear regression model of secondary industry and tertiary industry,night-time light intensity and lit areas,under different types of land use,were employed as predictor variables,and the GDP statistical data was as dependent variable,meanwhile,model of primary industry based on the landuse data.To improve model performance,31 zones were created according to provincial administrative boundary.The model of primary industry is observed to have a correlation（R2） ranging from 0.7 to 0.95 in majority zones and R2 of secondary industry and tertiary industry modle is ranging from 0.8 to 0.98 in majority zones.A comparison of the results of this research with other researches shows that spatialized GDP density map,prepared on night-time imagery and land-use data,which reflects the GDP distribution characteristics more explicitly and greater detail.Meantime,the density map is significant sustainable economic development policies and basically explores the relationship between socioeconomic and regional ecological environment interaction.
出处
《遥感技术与应用》
CSCD
北大核心
2012年第3期396-405,共10页
Remote Sensing Technology and Application
基金
国家科技支撑计划项目"主体功能区动态监测评价系统研究"(2008BAH31B03)资助
