Application of artificial intelligence for tree risk assessment optimization in Itanhaém – São Paulo, Brazil

Maria, Tamara Ribeiro Botelho de Carvalho; Biondi, Daniela; Behling, Alexandre; Reis, Allan Rodrigo Nunho dos; Zamproni, Kendra; Ho, Tatiane Lima

doi:10.1016/j.ufug.2023.127844

Cited by 2 publications

(2 citation statements)

References 28 publications

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“…However, affected by the complex urban environment, street trees also have potential safety hazards such as falling branches, broken trunks, and tree lodging, which will pose serious threats to municipal facilities [14], urban traffic [15,16], and the personal safety of citizens [17][18][19]. The potential of tree failure is based on the presence and severity of the defects, and the tree failure assessment of street trees can detect potential safety hazards in advance [20][21][22] and help to take targeted maintenance measures to eliminate or reduce safety hazards ahead of time [23][24][25], which is of great significance to the precision management of urban greening. Therefore, the importance of street tree failure assessment cannot be overstated.…”

Section: Introductionmentioning

confidence: 99%

Tree Failure Assessment of London Plane (Platanus × acerifolia (Aiton) Willd.) Street Trees in Nanjing City

Wang,

Wu,

Sun

et al. 2023

Forests

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The London plane (Platanus × acerifolia (Aiton) Willd.) street tree is a symbolic tree species in Nanjing City, which is known as the “city card”. However, accidents such as street trees falling over cars, affecting traffic, and hurting people have seriously affected the daily lives of citizens. Thus, it is of vital significance to accurately assess the potential for tree failure in London plane street trees in Nanjing City. This study comprehensively considers the growth condition of London plane street trees and their impact on traffic, establishes a scientific street tree failure assessment scheme that contains eight characteristics, creates a tree failure assessment database by thoroughly collecting data on trees, and develops a tree failure assessment model based on factor analysis and k-means clustering. The assessment results show that street trees that pose a high or medium potential for failure are present in proportions of 4.47% and 34.85%, respectively, and are mostly found in Gulou District, Xuanwu District, and Qinhuai District. The average tree failure score of London plane street trees on Changjiang Road in Xuanwu District is the highest, while the road with the lowest tree failure score is Mufu East Road in Gulou District. The results will provide a scientific basis for the maintenance of London plane street trees in Nanjing City and have reference significance for other street tree failure assessment studies.

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Section: Introductionmentioning

confidence: 99%

Tree Failure Assessment of London Plane (Platanus × acerifolia (Aiton) Willd.) Street Trees in Nanjing City

Wang,

Wu,

Sun

et al. 2023

Forests

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“…Despite the fact that systematic risk assessment is an effective and economical method of determining tree risk at the outset, data acquisition for assessment metrics remains predominantly subjective [34], and further research is needed. Therefore, (i) adding evaluation tools for objectivity, (ii) combining modern technologies such as computer vision for accurate data collection, and (iii) using machine learning to determine metric weights and develop a professional tree risk assessment website or application that makes the initial risk assessment a simple, quick, and reusable assessment method are all prospective research directions for determining tree risk [39].…”

Section: Introductionmentioning

confidence: 99%

Spatial Analysis of Risk Exposure of Urban Trees: A Case Study from Bologna (Italy)

Caggiu,

Fiorani,

Corradini

et al. 2023

Urban Science

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In Europe, more than two-thirds of the population live in urban areas. The management of urban green areas and trees is becoming increasingly relevant involving different players and stakeholders, as well for keeping a focus on the Sustainable Development Goals. Society and policy makers are often unaware of the disservices that neglecting these areas can cause. Appropriate monitoring interventions can protect both citizens and trees themselves. The aim of the study was to assess the risk potential in urban trees in Bologna suburbs (Italy). For each tree in the city of Bologna, three target variables identifying the number and categories of streets, buildings, and walking and cycle paths near the tree were considered and used as covariates. A multiple regression model assessing the relationship between a dependent synthetic spatial variable (digital number, DN), proxy of the likelihood of tree failure, and the three independent covariates was estimated. Both the number of streets and walking and cycle paths in the area surrounding a tree are shown to be significantly associated with the DN value. The use of open data can assist in monitoring and maintaining urban green areas. The tool supports a virtuous circle between stakeholders in urban systems through sustainability and efficiency.

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Application of artificial intelligence for tree risk assessment optimization in Itanhaém – São Paulo, Brazil

Cited by 2 publications

References 28 publications

Tree Failure Assessment of London Plane (Platanus × acerifolia (Aiton) Willd.) Street Trees in Nanjing City

Tree Failure Assessment of London Plane (Platanus × acerifolia (Aiton) Willd.) Street Trees in Nanjing City

Spatial Analysis of Risk Exposure of Urban Trees: A Case Study from Bologna (Italy)

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