基于NPP-VIIRS数据的山东省县级GDP分级空间建模
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摘要
传统的统计方法对国内生成总值(GDP)进行统计耗时耗力费财。而夜间灯光遥感影像能对人类社会活动进行最直观的反映,为社会经济研究提供了新的思路方法和技术支持。本文以山东省作为研究区域,采用NPP-VIIRS灯光影像数据与山东省137个县级GDP数据进行分级多方式空间建模,以找到两者空间分布的最优规律。试验结果表明总GDP与总灯光亮度值的各级最优拟合优度R~2均在0.9左右。单位面积GDP与平均灯光亮度值的各级拟合优度R~2均在0.85左右。而且通过最优模型进行县级和市级GDP预测精度优于未分级的预测精度。
Because of the traditional statistical methods,the time consuming and energy consuming spending on statistical the gross domestic product( GDP) is large. The night lighting remote sensing images can react directly to human social activities and provide a new way of thinking and technical support for the study of social economy. This paper takes Shandong Province as the research area,uses the NPP-VIIRS light image data and the GDP data of 137 counties in Shandong Province to establish many kinds of spatial relation models in order to find the optimal law of the spatial distribution of the two places. The experimental results show that the total GDP and the brightness of the total lighting are all about 0.9 at all levels of the goodness of fit R~2. The unit area GDP and the average lamplight brightness value are all about 0.85 at all levels of the goodness of fit R~2.The prediction accuracy of GDP at county level and city level by the optimal model is better than that of the unclassified one.
Because of the traditional statistical methods,the time consuming and energy consuming spending on statistical the gross domestic product( GDP) is large. The night lighting remote sensing images can react directly to human social activities and provide a new way of thinking and technical support for the study of social economy. This paper takes Shandong Province as the research area,uses the NPP-VIIRS light image data and the GDP data of 137 counties in Shandong Province to establish many kinds of spatial relation models in order to find the optimal law of the spatial distribution of the two places. The experimental results show that the total GDP and the brightness of the total lighting are all about 0.9 at all levels of the goodness of fit R~2. The unit area GDP and the average lamplight brightness value are all about 0.85 at all levels of the goodness of fit R~2.The prediction accuracy of GDP at county level and city level by the optimal model is better than that of the unclassified one.
引文
[1]王琪,袁涛,郑新奇.基于夜间灯光数据的中国省域GDP总量分析[J].城市发展研究,2013,20(7):44-48.
[2]何洋,程辉,唐亮.基于DMSP/OLS数据的我国省级经济发展水平研究[J].地理空间信息,2014,12(2):79-82.
[3]王旭,吴吉东,王海.基于夜间灯光和人口密度数据的京津冀GDP空间化对比[J].地球信息科学学报,2016,18(7):969-976.
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[9]李德仁,李熙.论夜光遥感数据挖掘[J].测绘学报,2015,44(6):591-601.
[10]李峰,卫爱霞,米晓楠,等.基于NPP-VIIRS夜间灯光数据的河北省GDP空间化方法[J].信阳师范学院学报(自然科学版),2016,29(1):152-156.
[11]江威,何国金,刘慧婵.NPP/VIIRS和DMSP/OLS夜光数据模拟社会经济参量对比[J].遥感信息,2016,31(4):28-34.櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂
[12]张梦琪,何宗宜,樊勇.DMSP/OLS稳定夜间灯光影像的校正方法[J].测绘通报,2017(12):58-62.
[13]韩向娣,周艺,王世新,等.夜间灯光遥感数据的GDP空间化处理方法[J].地球信息科学学报,2012,14(1):128-136.
[14]王宏莹.基于夜间稳定灯光数据的江苏省各市GDP估算[J].经纬天地,2018(2):3-9.
[15]LI X,XU H M,CHEN X L,et al.Potential of NPP-VIIRS nighttime light imagery for modeling the regional economy of China[J].Remote Sensing,2013,5(6):3057-3081.
[2]何洋,程辉,唐亮.基于DMSP/OLS数据的我国省级经济发展水平研究[J].地理空间信息,2014,12(2):79-82.
[3]王旭,吴吉东,王海.基于夜间灯光和人口密度数据的京津冀GDP空间化对比[J].地球信息科学学报,2016,18(7):969-976.
[4]DOLORES J F.Multi-scale analysis of the relationship between economic statistics and DMSP-OLS Night Light Images[J].Mapping Science and Remote Sensing,2013,50(5):483-499.
[5]FORBES D J.Statistical correlation between economic activity and DMSP-OLS night light images in Florida[J].Dissertations&Theses-Gradworks,2011,34:251-266.
[6]李宗光,胡德勇,李吉贺.基于夜间灯光数据的连片特困区GDP估算及其空间化[J].国土资源遥感,2016,28(2):168-174.
[7]柴子为,王帅磊,乔纪纲.基于夜间灯光数据的珠三角地区镇级GDP估算[J].热带地理,2015,35(3):379-385.
[8]袁姜红,陈二阳.基于夜间灯光数据的内蒙古省域GDP总量分析[J].安阳师范学院学报,2016(5):83-86.
[9]李德仁,李熙.论夜光遥感数据挖掘[J].测绘学报,2015,44(6):591-601.
[10]李峰,卫爱霞,米晓楠,等.基于NPP-VIIRS夜间灯光数据的河北省GDP空间化方法[J].信阳师范学院学报(自然科学版),2016,29(1):152-156.
[11]江威,何国金,刘慧婵.NPP/VIIRS和DMSP/OLS夜光数据模拟社会经济参量对比[J].遥感信息,2016,31(4):28-34.櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂櫂
[12]张梦琪,何宗宜,樊勇.DMSP/OLS稳定夜间灯光影像的校正方法[J].测绘通报,2017(12):58-62.
[13]韩向娣,周艺,王世新,等.夜间灯光遥感数据的GDP空间化处理方法[J].地球信息科学学报,2012,14(1):128-136.
[14]王宏莹.基于夜间稳定灯光数据的江苏省各市GDP估算[J].经纬天地,2018(2):3-9.
[15]LI X,XU H M,CHEN X L,et al.Potential of NPP-VIIRS nighttime light imagery for modeling the regional economy of China[J].Remote Sensing,2013,5(6):3057-3081.