Work

Improve the estimation of forest wind vulnerability through remote sensed data: a new methodology

Year: 2025

Type: article

Abstract: Windstorms are the primary cause of damage to European forests. Although different mechanistic and probabilistic models have been developed to estimate the vulnerability of forests to wind, their practical application remains limited. This study presents a new, semi-automated methodology for deriving tree and forest characteristics over large areas through the analysis of Canopy Height Model (CHM) data. By integrating the semi-mechanistic model ForestGALES, the developed algorithm uses these data to calculate spatially explicit maps of Critical Wind Speed (CWS). The presented methodology is applied to a real case study to calculate the CWS of forests in the Italian Eastern Alps. Results show that adding detailed and spatially distributed forest cover information improves the CWS calculations, thereby enhancing the reliability of models to assess forest wind vulnerability. Forest practitioners can take advantage of this new methodology to enhance the resistance and resilience of their forests through specific management techniques.

Source: Environmental Modelling & Software

DOI: 10.1016/j.envsoft.2025.106825

Authors: Tommaso Baggio, Maximiliano Costa, Niccolò Marchi, Tommaso Locatelli, Emanuele Lingua

Institutions: University of Padua, ETH Zurich, Institute of Terrestrial Ecosystems, Forest Research

Language: English

Topic: Tree Root and Stability Studies

Subfield: Mechanical Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Life on land, Climate action

Open Access status: hybrid

Estimated APC paid: $3,500