Big Data-based Evaluation Of Blue-Green Spatial Vitality Characteristics Of Jilin City In The Perspective Of Epidemic And Optimization Strategy Researchs

Since the outbreak of COVID-19 in early 2020,it has caused profound impacts on people’s daily lives and physical and mental health,requiring corresponding measures to alleviate emotional stress and psychological distress.In the post-pandemic era,the long-term travel restrictions and anxiety about high-density crowds have led to an increasing demand for high-quality blue-green spaces.This conclusion is a prerequisite for studying the evaluation and optimization strategies of the vitality characteristics of blue-green spaces.Space vitality can reflect the quality of a place well and can more significantly and detailedly show the characteristics of blue-green spaces that people need in the post-pandemic era.This study used big data to obtain relevant information for a more comprehensive evaluation system construction.Therefore,this article will evaluate and optimize the vitality characteristics of blue-green spaces in Jilin City from an epidemic perspective using big data methods.Based on the composition of spatial vitality,this study constructed a model for evaluating blue-green space vitality from the subjective behavior perspective of people and the objective perspective of the environment.Three activity characteristics in social media performance and population behavior characteristics were selected as subjective behavioral factors,and thirteen environmental impact factors were selected from blue-green spaces,artificial environments and facilities,geographic information,and transportation elements as objective environmental factors.Excluding the time period of action restriction during the epidemic,35,809 sets of data were obtained by crawling open-source data from Sina Weibo between 2018 and 2022,and24,539 sets of valid data were retained after data cleaning,including location information,time,text comments,photos,etc.Based on this,the characteristics of subjective factors and some environmental factor indicators were calculated and quantified through STDEV function calculation,Gooseeker sentiment semantic analysis,FCN visual semantic analysis,etc.After accessing the API interface through the developer mode of Gaode Maps,the POI data of the research area were obtained and imported into Arc GIS for data processing and obtaining other related data for the remaining environmental indicator quantification research.Finally,partial least squares regression(PLS)was selected to construct the spatial vitality evaluation model.This study constructed two models before the epidemic(2018 and 2019)and after the epidemic(2020,2021,and 2022)and firstly determined the number of principal components,and then constructed the models separately to draw the following conclusions.Before the epidemic,people’s evaluation of the research area was more focused on several indicators,such as blue-green rate,accessibility,human vision rate,and water-land area ratio.Accessibility,traffic facility density,and location centrality had a greater impact on time period fluctuation characteristics,and POI richness had a more obvious negative correlation with them.Green rate,green vision rate,and human vision rate had a greater impact on accumulated population density,while land-use mix had a significant negative correlation.After the epidemic,traffic facility density,blue-green rate,sky rate,and water-land area ratio had a greater impact on people’s evaluation of space,among which POI total quantity,human vision rate,land-use mix,and accessibility had a negative correlation.Land-use mix,water-land area ratio,and location centrality had a significant impact on time period fluctuation characteristics after the epidemic.Traffic facility density,green rate,and water-land area ratio had a significant positive impact on accumulated population density after the epidemic.Through a comparison of vitality evaluation models before and after the epidemic,it can be concluded that people had a high demand for blue spaces before and after the epidemic,and after the epidemic,the demand for blue spaces,green spaces,and open spaces such as sky rate also increased significantly.Additionally,blue-green spaces further away from the city center were favored,which may be related to people’s cautious attitude towards traveling.Before the epidemic,people preferred high-rated and popular places with rich facilities and large crowds,while after the epidemic,people tended to choose high-quality blue-green spaces with fewer people and more specialized land use for physical and mental relaxation.Based on these conclusions,this paper proposes six optimization strategies,including the construction of targeted high-quality blue-green spaces,the creation of distinctive landscape areas,the promotion of landscape fairness,psychological healing through horticultural therapy and other activities,the enhancement of disaster prevention and reduction facilities,and the construction of smart cities combined with blue-green spaces.These strategies aim to improve the vitality of blue-green spaces in Jilin City in the post-epidemic era,better serving people’s lives and health.