基于NPP-VIIRS夜間燈光數(shù)據(jù)的北京市GDP空間化方法

摘要： 為了分析像素級(jí)社會(huì)經(jīng)濟(jì)活動(dòng)的空間分布狀況,以Landsat8和NPP-VIIRS夜間燈光影像為數(shù)據(jù)源,分別對(duì)北京市第一產(chǎn)業(yè)和第二、三產(chǎn)業(yè)GDP進(jìn)行空間化操作。利用分類回歸樹(classification and regression tree,CART)算法,通過Landsat8影像生成北京市的土地利用圖,在分析第一產(chǎn)業(yè)GDP與土地利用類型面積相關(guān)性的基礎(chǔ)上,構(gòu)建了第一產(chǎn)業(yè)GDP與耕地面積的線性回歸模型。建立了5種燈光指標(biāo)與第二、三產(chǎn)業(yè)GDP的數(shù)學(xué)關(guān)系,通過相關(guān)性和回歸分析確定第二、三產(chǎn)業(yè)GDP與綜合燈光指數(shù)呈明顯的冪函數(shù)關(guān)系。根據(jù)以上2種模型分別生成對(duì)應(yīng)2類產(chǎn)業(yè)的像素級(jí)GDP密度圖,再分別對(duì)其進(jìn)行線性糾正并求和后制作出北京市500 m格網(wǎng)尺寸的GDP密度圖。誤差分析發(fā)現(xiàn),第一產(chǎn)業(yè)GDP、第二、三產(chǎn)業(yè)GDP和GDP總量與實(shí)際統(tǒng)計(jì)值的平均相對(duì)誤差分別為0.86%,0.61%和1.37%。結(jié)果表明,結(jié)合土地利用數(shù)據(jù)的NPP-VIIRS夜間燈光GDP空間化方法可以精確估算北京市GDP產(chǎn)值,反映北京市經(jīng)濟(jì)空間分布特征。
In order to analyze spatial distributions of socioeconomic activities at pixel scale,the authors used Landsat8 and NPP- VIIRS night- time light images as data sources and produced spatialization maps of primary industry GDP and the secondary, tertiary industry GDP in Beijing. The land use map of Beijing for the spatialization was produced from Landsat8 image with CART decision- tree algorithm. According to the correlation results between the primary industry GDP and areas of land use,a linear regression model was built based on the primary industry GDP and areas of plough. By analyzing the correlation relationships between five light indexes and the secondary,tertiary industry GDP,compounded night light index( CNLI) and the secondary,tertiary industry GDP presented apparent power function's correlation relationship. Using linear corrections and summation of two types of pixel level's GDP density maps produced both modes listed above,and a total GDP density map was generated with the resolution of five hundred meters in Beijing. The results of GDP relative errors show that the primary industry GDP and the secondary,tertiary industry GDP were 0. 86%,0. 61% and 1. 37% respectively.This suggests that this approach of pixel level's GDP spatialization can be applied to estimate Beijing's GDP and reflect characteristics of its economic distribution.