Research On Spatialization Of Regional Economic Indicators Of Eastern China Based On Luminous Remote Sensing

The socio-economic level is one of the important aspects to measure regional development,and population and economy have always been the focus of research.Traditional research of population and economic is based on administrative divisions,assuming that the population and economic distribution is even,ignoring geographic location of relevant information,it cannot reflect the population and economic development structure within the city.With the development of luminous remote sensing technology,and the luminous remote sensing data have some characteristics of easy access,long-time sequence and wide coverage,it has become more and more extensive in the application research of spatial analysis of social and economic indicators.This paper selects eastern China(Jiangsu province,Zhejiang province,Anhui province,Fujian province,Jiangxi province and Shanghai city)as the research area,takes the population and GDP in 2016 as the research objects,and selects NPP-VIIRS nighttime data and multiple environmental variables,constructed the spatial regression model of population and GDP.Firstly,perform global and local spatial autocorrelation analysis on population and GDP data,then,construct spatial regression models of different variables,compare and analyze the superiority of the models,select a model with a better fitting effect,and based on the simulation results of the model,use ArcGIS 10.3 software to calculate the raster results of different models,draw the spatial distribution map of population density and economic density,and evaluate the accuracy of the modeling results.The main conclusions are as follows:1)The results of spatial autocorrelation analysis show that the indicators of population and economic(GDP,GDP2,GDP3)of the study area have significant global spatial autocorrelation(P<0.01),and the Global Moran's I values are 0.482,0.530,0.592,0.418,in general,there are spatial clustering characteristics;local spatial map shows that the distribution of population and economic agglomeration is relatively similar.High-High agglomeration is mainly distributed in Shanghai city and its surrounding cities,and Low-Low agglomeration is mainly distributed in the adjacent areas of Jiangxi Province and Fujian Province.2)The spatial modeling results of population density and GDP density show that the spatial distribution of population and economy in plain areas are relatively similar.The model after adding environmental variables reduces the density peak in the central area,but in mountainous and hilly areas,a single night light data model The spatial distribution of population and economic density shown in the result map is more in line with reality,and the result is more accurate.From the perspective of the accuracy test of the model results,a single model based on night light data has higher accuracy and better simulation effect;after adding environmental variables,the local area of the model has a larger error value,and the model error constructed by a single night light data is more stable,For regions with large spatial differences,the model prediction results are more accurate.3)The spatial distribution characteristics of population density and economic density after gridding in the study area are more consistent with the actual situation.The spatial distribution characteristics of population density mainly present a high-density and diffuse planar distribution pattern,a high-density band distribution pattern,and a low-density and concentrated point-like distribution pattern.The spatial distribution map of economic density clearly shows that the economic center of gravity of the study area is in coastal cities such as Shanghai,Hangzhou,and Fuzhou,and the economic density of coastal areas is significantly higher than that of inland cities.Figure[28]table[15]reference[99]...