利用DMSP/OLS夜间灯光影像模拟中国经济参量

摘要

In view of traditional survey method cannot accurately and efficiently reveal the economic parameter spatial temporal information,this study proposed a method to model China economic parameter by combing DMSP/OLS nighttime light imagery and statistical yearbook data.Gross regional domestic product(GDP),primary industry(PI),secondary industry(SI) and tertiary industry(TI)at provincial scale were selected and linear regression models were established between total nighttime light index and economic parameter in the year of 1992,2002 and 2012 respectively.Furthermore,according the regression coefficient of liner model,sensitive nighttime-economic parameters were selected and spatial model was employed to simulate economic parameter at pixel scale.The results show that the economic parameter rapidly increased around the capital cities during the past 21 years and the three urban agglomerations(Yangtze river delta urban agglomeration,pearl river delta urban agglomeration and Beijing-Tianjin-Hebei urban agglomeration)have formed stretch area.This result is consistent with the actual situation and it demonstrates that DMSP/OLS nighttime light data has advantages in modelling time series economic parameter.%鉴于传统统计调查方法难以准确、高效和客观揭示经济参量时空信息,提出结合DMSP/OLS夜间灯光数据和统计年鉴数据模拟中国经济参量.选取省级尺度地区生产总值(GDP)、第一产业生产总值(PI)、第二产业生产总值(SI)、第三产业生产总值(TI)4个经济参量,分别构建1992年、2002年和2012年3期DMSP/OLS夜间灯光总值参量与4个经济参量一元线性回归模型,遴选夜间灯光-经济敏感参量,构建空间化模型模拟经济参量.结果表明,地区生产总值(GDP)和第二产业生产总值为敏感参量,模拟结果表明过去21年中国经济参量主要围绕中心城市(省会城市和直辖市)快速增长,其中三大城市群(长三角城市群、珠三角城市群和京津冀城市群)形成高值绵延区,与实际情况相符合,展现了利用DMSP/OLS模拟时序经济参量的优势.