LiDAR insights on stand structure and topography in mountain forest wind extreme events: The Vaia case study

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F24%3A100124" target="_blank" >RIV/60460709:41330/24:100124 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S0168192324003800?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0168192324003800?via%3Dihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.agrformet.2024.110267" target="_blank" >10.1016/j.agrformet.2024.110267</a>

Jazyk výsledku

angličtina

Název v původním jazyce

LiDAR insights on stand structure and topography in mountain forest wind extreme events: The Vaia case study

Popis výsledku v původním jazyce

With climate change intensifying, forests globally are becoming more susceptible to extreme weather events, such as windstorms, which account for a significant share of Europe's economic losses. The Vaia windstorm of late autumn 2018, striking Italy's North-East alpine ecosystem, highlighted this vulnerability, toppling over 8.5 million cubic meters of timber and sparking debates on forest management's role in mitigating such disasters. This study aims to evaluate the impact of structural and topographical characteristics on the damage caused by Vaia, using Airborne Light Detection And Ranging (LiDAR) data collected before the storm, in four heavily affected forest areas in the Italian Alps (Carezza in the Province of Bolzano-Bozen, Predazzo, Manghen, and Primiero in the Province of Trento). We analyzed structural metrics like forest height heterogeneity (HH), forest mean height, and density, alongside topographical features such as aspect, slope, and altitude, to discern their influence on the storm's severity. Our results revealed that the most significant difference between affected and unaffected areas is forest mean height that was found higher in areas hit by the storm. Forest density played a lesser but important role, with denser areas experiencing more severe damage, though this was only significant in certain areas. Contrary to common assumptions, our analysis revealed that forest height heterogeneity (HH) did not have a significant effect on damage levels. The findings, consistent with previous research, revealed a significant association between specific aspects, particularly the South-East orientation, which aligned with the predominant wind direction during the Vaia storm, and an increased likelihood of damage. Both structural and topographical factors interact in complex ways to influence the outcome of such extreme events. The study emphasizes the dominant impact of the Vaia windstorm, noting that while managing forest height and density may help, the diverse topography complicates these efforts. Our study explicitly tested the effectiveness of using Airborne LiDAR data to explore forest structural and topographical factors that influenced Vaia storm damage. The achieved results demonstrate that LiDAR serves as a useful tool to field data, offering valuable insights for broader applications in this domain.

Název v anglickém jazyce

LiDAR insights on stand structure and topography in mountain forest wind extreme events: The Vaia case study

Popis výsledku anglicky

With climate change intensifying, forests globally are becoming more susceptible to extreme weather events, such as windstorms, which account for a significant share of Europe's economic losses. The Vaia windstorm of late autumn 2018, striking Italy's North-East alpine ecosystem, highlighted this vulnerability, toppling over 8.5 million cubic meters of timber and sparking debates on forest management's role in mitigating such disasters. This study aims to evaluate the impact of structural and topographical characteristics on the damage caused by Vaia, using Airborne Light Detection And Ranging (LiDAR) data collected before the storm, in four heavily affected forest areas in the Italian Alps (Carezza in the Province of Bolzano-Bozen, Predazzo, Manghen, and Primiero in the Province of Trento). We analyzed structural metrics like forest height heterogeneity (HH), forest mean height, and density, alongside topographical features such as aspect, slope, and altitude, to discern their influence on the storm's severity. Our results revealed that the most significant difference between affected and unaffected areas is forest mean height that was found higher in areas hit by the storm. Forest density played a lesser but important role, with denser areas experiencing more severe damage, though this was only significant in certain areas. Contrary to common assumptions, our analysis revealed that forest height heterogeneity (HH) did not have a significant effect on damage levels. The findings, consistent with previous research, revealed a significant association between specific aspects, particularly the South-East orientation, which aligned with the predominant wind direction during the Vaia storm, and an increased likelihood of damage. Both structural and topographical factors interact in complex ways to influence the outcome of such extreme events. The study emphasizes the dominant impact of the Vaia windstorm, noting that while managing forest height and density may help, the diverse topography complicates these efforts. Our study explicitly tested the effectiveness of using Airborne LiDAR data to explore forest structural and topographical factors that influenced Vaia storm damage. The achieved results demonstrate that LiDAR serves as a useful tool to field data, offering valuable insights for broader applications in this domain.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10511 - Environmental sciences (social aspects to be 5.7)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

AGRICULTURAL AND FOREST METEOROLOGY

ISSN

0168-1923

e-ISSN

0168-1923

Svazek periodika

359

Číslo periodika v rámci svazku

110267

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

14

Strana od-do

1-14

Kód UT WoS článku

001348446700001

EID výsledku v databázi Scopus

2-s2.0-85207636027