Research On Spatialization Of GDP Based On Multi-Source Data Coupling And Applicability Analysis Of Luojia-1 Nighttime Light Data

Since the reform and opening up,China has experienced a stage of rapid economic take-off.Research on the current economic situation is of great significance for China to implement more economic policies that benefit the country and the people and adjust the overall economic layout.The traditional economic data survey is based on the census and statistics within the administrative divisions,and is aggregated into a data table,which cannot reflect the economic distribution differences between regions.The spatialization of economic data assisted by remote sensing data quantifies and locates the statistical data to a certain scale of geographic space on the grid,it can more intuitively reflect the economic distribution of different regions.Previously,a large number of studies have proved that there is a certain correlation between night lighting data and Gross Domestic Product(GDP),which can be used to achieve economic spatialization and reflect the distribution of GDP in geographical units.However,with the continuous improvement of the accuracy and quality requirements of spatialized products,the commonly used nighttime lighting data has certain limitations in resolution and data accuracy,so it is particularly important to seek better quality lighting product data.At the same time,the economic status quo is generated by the huge social system in complex operations.Using only a single light data as an impact factor to estimate GDP does not completely map the accurate GDP spatial layout.More social impact factors need to be considered to improve The accuracy of the estimate.In response to the existing problems,this study is divided into two parts:1.Taking Beijing as a research area,on the basis of the commonly used night lighting data NPP-VIIRS(Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite,NPP-VIIRS)estimated GDP spatial distribution,added to reflect the economic entity distribution big data Point of Interest(POI)as an influencing factor,converted POI point data into density layers,explored the modeling method of the coupling of POI core density and night lights,and studied the accuracy of POI data after participating in the spatialization of GDP changes and effects of spatial distribution of GDP,study its availability,and explore the spatialization method of GDP coupled with multi-source data.2.In the five provinces and cities along the southeast coast of China,compare the night light data source produced by the domestic satellite Luojia-1 with the NPP-VIIRS data,compare the advantages and disadvantages of the two data,the accuracy of the spatial application of GDP and the spatialization effect.Demonstrate the data quality,applicable scope and application of spatial data of Luojia-1 nighttime lighting data.The conclusions of this study are as follows:(1)After adding POI data and NPP-VIIRS night light data for multi-source data coupling,the fitting accuracy with GDP statistical data is improved by 7.5%,the overall error is reduced,and the visualization effect can be significantly improved,More clearly show the distribution characteristics of GDP in different spaces in detail.As social perception big data,POI can participate in the GDP spatialization research and achieve good results.(2)Compared with the NPP-VIIRS night light data,the brightness value has a high degree of fit,but in the image,the Luojia-1 data has a higher resolution and a larger spectral range,showing the distribution of subtle lights and small spaces.The effect is better;the spatialization result boundary generated by Luojia-1 is obvious,which is more in line with the GDP distribution law,and is suitable for small-scale refined GDP spatialization applications;Luojia-1 data,NPP-VIIRS night lighting data and GDP statistics in the simulation of data at different scales,different function models,and different lighting parameters,the fitting law is similar,but the fitting accuracy of Luojia-1 is less than that of NPP-VIIRS data.As a data source for GDP spatialization,Luojia-1 is not as accurate as NPP-VIIRS data,but the spatialization effect in fine space has certain advantages.Researchers can choose a suitable data source for experiments according to their own needs the study.