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Investigation On Safety Risk Assessment Of Street Tree In Shanghai Based On VTA-Risk Matrix Method

Posted on:2022-03-31Degree:MasterType:Thesis
Country:ChinaCandidate:P SongFull Text:PDF
GTID:2493306722497484Subject:Safety engineering
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Urban trees are the green base and high-quality ecological products of urban development and ecological civilization construction.Assessing the safety risk level of urban trees and their regional characteristics is an important measure to improve the level of fine management of trees,it is also an important content to improve the city public security.Street trees are the main part of urban greening,which play an important role in optimizing the urban environment and improving the quality of life of residents.In order to detect and improve the potentially dangerous street trees and improve the safety of city life,it is urgent to detect and evaluate the risk degree.Based on the tree visual diagnosis(VTA)method and the risk matrix method,a rapid diagnosis method and assessment technique for the safety risk direction of street trees were developed,the purpose of this paper is to provide reference for the safety investigation of high-risk street trees.In this paper,the background and significance of the research on tree safety risk assessment are introduced,and then,based on the theoretical basis of previous studies,VTA diagnosis method and Risk Matrix method are used,from the risk possibility and the risk consequence severity two angles constructs the street tree safety risk appraisal index system,the potential risk possibility and the risk consequence severity carries on the quantification to obtain the risk grade;Finally,by using GIS technology and RDA redundancy analysis technology,combined with information collection and data processing analysis,the safety Risk Assessment of street trees in Shanghai was carried out.More than 90% of the 817 street trees surveyed had a risk rating R of Grade II or below,indicating that most of the street trees in Shanghai were at moderate risk level,which was negligible or acceptable risk.In terms of tree risk probability,Firmiana platanifolia and Magnolia grandiflora have the highest risk probability rating,while Cinnamomum camphora,Ginkgo biloba and Liquidambar formosana have lower risk.From the safe space pattern of the street trees,the distribution of P,s and r grades within the Outer Ring Road presents a large-gathering spatial pattern,and the central urban area presents a gradually descending law of a circle-type toward the periphery,the areas with high street tree risk are mainly in Huangpu district and Xuhui district.As far as the strength of the trees themselves is concerned,the holes,dead trees,injuries and structural defects are the four major risk points of the street trees in Shanghai,the risk points of the street trees in the central city,the outer ring and the coastal area are concentrated in the trunk,the root and the branch respectively.According to the different risk points of trees,the corresponding risk correction measures are different,and the risk mitigation measures are mainly based on the tree itself and the target of risk impact.In addition,GIS and information technology can be used for real-time monitoring and risk correction of trees at risk,which can be used as a new means of risk mitigation and help to establish corresponding management measures and serve for tree risk management in information-based cities.The purpose of this study is to predict the risk of trees for the first time.It is a direct and effective method for street tree risk assessment in a large area of a city.At the same time,strong subjectivity is also the inadequacy of this study.Therefore,the potential risk information of trees can be found by this method,and an advanced assessment of areas above the medium risk level is needed to help further reduce the risk of trees after the classification results are obtained,improving urban public safety.
Keywords/Search Tags:Street tree, VTA approach, Risk matrix, risk assessment, GIS technology, Redundancy analysis
PDF Full Text Request
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