A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Building patterns and fuel features drive wildfire severity in wildland-urban interfaces in Southern Europe
Highlights Burn severity decreases in WUIs proportionally to nearby building aggregation. The combination of radar and multispectral variables is useful to predict burn severity. Variables related to the amount of living vegetation are the most important to predict burn severity. Burn severity is more predictable outside WUIs than inside them. Knowledge of burn severity drivers serves to improve landscape planning in WUIs.
Abstract Fire danger analysis is crucial for landscape planning, which is particularly relevant in vulnerable areas such as the wildland-urban interface (WUI). The aim of our work is to investigate the capacity of fuel characteristics to predict burn severity in different WUI typologies classified according to nearby building density criteria. To achieve this goal, we selected 23 wildfires across Southern Europe, in which we differentiated non WUI areas, isolated, scattered, dense and very dense WUIs. Moreover, we spatialized burn severity and different fuel metrics using multispectral and radar satellite imagery. This information was used to analyze burn severity, and to identify its drivers in the different WUI typologies through analysis of variance, correlation analysis and machine learning models. Our results indicate that burn severity is lower in WUIs of clustered buildings than in non-WUI areas, which were also the most homogeneous in terms of vegetation cover. Moreover, we found that vegetation biophysical properties related to the amount of living fuel (fraction of vegetation cover and fraction of absorbed photosynthetically active radiation) showed the highest influence on burn severity in all WUI typologies. We also found that burn severity is less predictable in dense and very dense WUIs than in the rest, which can be attributed to their greater landscape complexity, presence of artificial structures and efficiency of extinction efforts. Our results serve to guide landscape management strategies, and impulse next-generation fire danger models, which should be based not only on synoptic fire weather indices but also on landscape-scale susceptibility to severe fires.
Building patterns and fuel features drive wildfire severity in wildland-urban interfaces in Southern Europe
Highlights Burn severity decreases in WUIs proportionally to nearby building aggregation. The combination of radar and multispectral variables is useful to predict burn severity. Variables related to the amount of living vegetation are the most important to predict burn severity. Burn severity is more predictable outside WUIs than inside them. Knowledge of burn severity drivers serves to improve landscape planning in WUIs.
Abstract Fire danger analysis is crucial for landscape planning, which is particularly relevant in vulnerable areas such as the wildland-urban interface (WUI). The aim of our work is to investigate the capacity of fuel characteristics to predict burn severity in different WUI typologies classified according to nearby building density criteria. To achieve this goal, we selected 23 wildfires across Southern Europe, in which we differentiated non WUI areas, isolated, scattered, dense and very dense WUIs. Moreover, we spatialized burn severity and different fuel metrics using multispectral and radar satellite imagery. This information was used to analyze burn severity, and to identify its drivers in the different WUI typologies through analysis of variance, correlation analysis and machine learning models. Our results indicate that burn severity is lower in WUIs of clustered buildings than in non-WUI areas, which were also the most homogeneous in terms of vegetation cover. Moreover, we found that vegetation biophysical properties related to the amount of living fuel (fraction of vegetation cover and fraction of absorbed photosynthetically active radiation) showed the highest influence on burn severity in all WUI typologies. We also found that burn severity is less predictable in dense and very dense WUIs than in the rest, which can be attributed to their greater landscape complexity, presence of artificial structures and efficiency of extinction efforts. Our results serve to guide landscape management strategies, and impulse next-generation fire danger models, which should be based not only on synoptic fire weather indices but also on landscape-scale susceptibility to severe fires.
Building patterns and fuel features drive wildfire severity in wildland-urban interfaces in Southern Europe
Fernández-García, Víctor (author) / Beltrán-Marcos, David (author) / Calvo, Leonor (author)
2022-11-20
Article (Journal)
Electronic Resource
English
Assessing Wildfire Hazard in the Wildland–Urban Interfaces (WUIs) of Central Portugal
| DOAJ | 2023
| American Chemical Society | 2021
New methodology for mapping wildfire risk in the wildland-urban interface.
| BASE | 2020
The Ashland wildland/urban interface: wildfire management inventory, analysis, and opportunities
| BASE | 2002