Home > Research > Publications & Outputs > Tree Risk Evaluation Environment for Failure an...

Electronic data

  • pre-print February 2019

    Rights statement: This is the author’s version of a work that was accepted for publication in Computers, Environment and Urban Systems. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers, Environment and Urban Systems, 75, 2019 DOI: 10.1016/j.compenvurbsys.2019.02.001

    Accepted author manuscript, 34.9 MB, PDF document

    Available under license: CC BY-NC-ND: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License

Links

Text available via DOI:

View graph of relations

Tree Risk Evaluation Environment for Failure and Limb Loss (TREEFALL): An Integrated Model for Quantifying the Risk of Tree Failure from Local to Regional Scales

Research output: Contribution to journalJournal articlepeer-review

Published
<mark>Journal publication date</mark>1/05/2019
<mark>Journal</mark>Computers, Environment and Urban Systems
Volume75
Number of pages12
Pages (from-to)217-228
Publication StatusPublished
Early online date28/02/19
<mark>Original language</mark>English

Abstract

Trees provide a multitude of ecosystem services but are vulnerable to failure and limb loss under high winds. This is a natural process which initiates regeneration in forests but tree failures close to critical infrastructure networks lead to disruption to services and financial loss. Hence, network operators tend to apply the precautionary principle and remove all trees close to such infrastructure which leads to unnecessary loss of healthy trees, therefore, a more focussed approach is required. We introduce TREEFALL: an objective and scalable framework to assess tree failure risk. It uses novel approaches to quantify tree geometry, downscale wind parameters, simulate shielding by neighbouring trees and calculate wind-induced failure risk based on meteorological data for previous storms, scenarios or forecasts. Consequently, TREEFALL can identify individual trees which pose the greatest threat to infrastructure networks which can be targeted for field survey and management interventions where necessary. The model has broad potential for application to many different types of infrastructure networks and across the forest and environmental sciences.

Bibliographic note

This is the author’s version of a work that was accepted for publication in Computers, Environment and Urban Systems. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers, Environment and Urban Systems, 75, 2019 DOI: 10.1016/j.compenvurbsys.2019.02.001