Study On The Green View Index Based On Street View

With the development of our country’s urbanization and the enhancement of people’s demand for city space quality,Green View Index(GVI)has gradually entered into people’s vision as a quantitative index of urban greenery.The formation of the new data environment provides the basic conditions for the measurement of the GVI and the breakthrough and extension of the application scope,the large-scale and automatic GVI acquisition and calculation methods become possible.In order to explore the application prospects and shortcomings of GVI in urban research,this paper makes an in-depth study on the workflow,influencing factors of GVI.This paper first summarizes and designs the workflow of GVI acquisition and puts it into practice by combing through the evolution of the theory of GVI,comparing the GVI measurement technology process and technological evolution at different stages.Secondly,this paper takes the road space of Nanjing city(with the inner circle of Nanjing as the boundary)as study area,and uses the compilation of Baidumap street view service parameters and codes to obtain street view pictures of specific sampling points in batches.Use the code to analyze the acquired street view image and calculate the GVI value of the sampling point.Finally,this paper uses Arc GIS spatial analysis function to describe the spatial distribution of GVI values and visualize the results.The second half of this paper uses urban open-source data combined with field research to filter and sort out urban roads and road greening parameters in the study area,and to road parameters such as road length,road width,road structure,road breakpoint number,road traffic level and other parameters Correlation analysis with GVI.Analyze the correlation between plant parameters such as plant diameter,species,planting layers and other data nd the value of Green View Index.Using open-source POI(points of interests)data,combined with Arc GIS Kernel Density Estimation(KDE)analysis function to identify urban functional areas,and to explore the correlation between it and the green rate of urban roads,the conclusions are as follows:(1)The road structure characterized by the number of green belts and the width of the road has a significant impact on the GVI of the road.The width of the road is negatively correlated with the GVI,and the number of green belts is positively correlated with the GVI;(2)There is a positive correlation between the road traffic level in the study area and the GVI,which is related to the specific road conditions in the study area.From the comprehensive road layout,road design specifications and correlation analysis results, it shows that the number of road intersections and the GVI are negatively correlated.(3)There is a positive correlation between the number and level of sidewalk trees planted and the GVI.Different types of sidewalk trees have significant differences in the impact of road greenness rate.However,the diameter at breast height and the average planting distance of the sidewalk trees in the study area have no obvious correlation with the changes of the GVI.(4)here are significant differences in the impact of different land use forms on GVI,and the magnitude of the difference has a certain relationship with the history of urban construction and the architectural characteristics of the site.Among the land types with unnatural attributes,the average GVI value of composite land attribute is higher than that of single land attribute.The innovation of this paper is to combine the previous research to form the technical workflow of obtaining the GVI of urban roads,and to generate the GVI distribution map.This paper standardizes and quantifies the road parameters,basic parameters of road greening,and urban land attribute elements,studies the correlation between them and the GVI of urban roads,and uses statistical analysis methods to demonstrate.The research results have certain reference value for urban green space planning and urban road design.