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A Proximity-Based Approach for the Identification of Fallen Species of Street Trees during Strong Wind Events in Lisbon

Author

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  • Flávio Henrique Mendes

    (Department of Forest Sciences (LCF), Luiz de Queiroz College of Agriculture (ESALQ), University of São Paulo (USP), Av. Pádua Dias, 11, Piracicaba 13418-900, SP, Brazil)

  • Felipe Coelho de Souza Petean

    (School of Visual Arts (FAV), Campus Samambaia, Federal University of Goiás (UFG), Av. Esperança s/n, Goiânia 74690-900, GO, Brazil)

  • Ezequiel Luís Tavares Correia

    (Centre of Geographical Studies (CEG), Institute of Geography and Spatial Planning (IGOT), University of Lisbon, R. Branca Edmée Marques, 1600-276 Lisbon, Portugal)

  • António Manuel Saraiva Lopes

    (Centre of Geographical Studies (CEG), Institute of Geography and Spatial Planning (IGOT), University of Lisbon, R. Branca Edmée Marques, 1600-276 Lisbon, Portugal)

Abstract

The benefits of urban trees are very well known, but they can fall and cause damage, putting people’s lives at risk. There are few studies on the vulnerability of species to falling. In Lisbon (Portugal), fallen trees have been recorded since 1990 without, however, the identification of the species, knowledge of which is fundamental for improving their management. This study aimed to identify the tree species most vulnerable to falling in Lisbon through a proximity-based approach of known species, since the city has 47,713 inventoried trees, of which only 26,595 (55.7%) were identified. Four criteria were designed to presume the species: (i) the tree must be within 15 m from the street median axis; (ii) at least three individuals within 30 m from the occurrence must belong to the same species; (iii) the surrounding species must be representative in the street (>50%); and (iv) visual identification of avenue medians. Through this approach, considering 3767 fallen trees, it was possible to identify 736 cases, representing 19.5% of all occurrences throughout the studied time and representing 43 different species. Species like Morus nigra L., Tipuana tipu (Benth.) Kuntze, Liriodendron tulipifera L., Prunus cerasifera Ehrh., and Koelreuteria paniculata Laxm. were most vulnerable. Additionally, in 57.7% of cases (425 fallen trees), the wind speed 12-h before the occurrence was greater than 7 m s −1 . This research will provide important data for urban planners seeking to maximize the ecosystem services of urban trees.

Suggested Citation

  • Flávio Henrique Mendes & Felipe Coelho de Souza Petean & Ezequiel Luís Tavares Correia & António Manuel Saraiva Lopes, 2024. "A Proximity-Based Approach for the Identification of Fallen Species of Street Trees during Strong Wind Events in Lisbon," Land, MDPI, vol. 13(5), pages 1-11, May.
  • Handle: RePEc:gam:jlands:v:13:y:2024:i:5:p:708-:d:1396896
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    References listed on IDEAS

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    1. Cláudia Reis & António Lopes, 2019. "Evaluating the Cooling Potential of Urban Green Spaces to Tackle Urban Climate Change in Lisbon," Sustainability, MDPI, vol. 11(9), pages 1-17, April.
    2. Guangyang Hou & Suren Chen, 2020. "Probabilistic modeling of disrupted infrastructures due to fallen trees subjected to extreme winds in urban community," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 102(3), pages 1323-1350, July.
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