Study On The Change Of Urban Spatial Pattern In Shandong Province Based On NPP/VIIRS

Urbanization is the result of the development of social economy and science and technology.Excessive urban expansion has produced a series of land and environmental problems,How to balance the relationship between urban expansion and environmental protection is a hot topic of current research.In the past two decades,with the rapid development of earth observation technology,it is possible to monitor urban spatial expansion and urban form change in a long time sequence and dynamically.This article takes into account the background noise,abnormal value and inter-annual data discontinuity in the NPP/VIIRS night light data,and corrects the data.Taking Shandong Province as the research object,based on the corrected NPP/VIIRS light data and MODIS EVI data,The vegetation correction light index method was used to extract the urban built-up area,and the dynamic evolution characteristics of the urban space in Shandong Province from 2012 to 2019 were analyzed,and the gray driving force prediction model and the BP neural network prediction model were constructed to explore the urban development and economic and social factors.The driving force mechanism between.The main research conclusions are as follows:(1)Use the mask denoising method to denoise the original light data,then perform outlier elimination and continuity correction to obtain long-term sequence and usable light data,and perform statistics on the corrected light brightness value pixels It is linearly fitted to GDP.The result shows that the number and total amount of bright value pixels show a continuous growth trend,and the degree of fitting with GDP economic parameters is relatively high.The correlation coefficient R2 is greater than 0.9,indicating that the corrected light data has a relatively high High applicability and reliability.(2)The neighborhood analysis method,support vector machine method,and index construction method are used to carry out built-up area extraction experiments,and the accuracy of the three methods is compared.The results show that the modified light index constructed in conjunction with the vegetation index has a better performance in built-up area extraction.High accuracy,0.33%difference from statistical data,and accuracy rate of 83%.The extracted results can be used to study the law of urban expansion.(3)Discuss the temporal and spatial laws of urban spatial expansion in Shandong Province from three aspects:temporal changes in spatial expansion,changes in spatial form measurement,and urban land use scale.The research results show that the urban expansion of Shandong Province has experienced three main stages.The provincial capital metropolitan area with Jinan as the center develops first,then migrates to the eastern coastal area,and then develops to the southwestern part of Shandong.The urban development tends to be balanced,and the inter-regional coordination is sustainable.Development,the boundary and scope of built-up areas are developing towards concentration and standardization.(4)Use gray correlation analysis to explore the degree of correlation between urban expansion and economic driving factors in Shandong Province.Overall analysis,the correlation degree between regional GDP,population of municipal districts,social consumer retail sales and built-up area Both are more than 0.7,with high relevance.Select the top five economic driving force factors,respectively construct the gray driving force prediction model and the BP neural network prediction model to simulate and predict the urban expansion of Shandong Province.The results show that the relative error between the simulated value and the actual value obtained by the BP neural network model is about 2%,and the accuracy is higher,which can be applied to the analysis of urban expansion in Shandong Province.