Wildfires pose a great threat to the wildland-urban interface (WUI), the zone of contact between wildland vegetation and the human-settled environment. In these areas, high fuel loads often coexist with high value assets, which are more exposed to ignition than equivalent structures in an urban context. At the WUI, wildfires can quickly exhaust the resources normally available to urban firefighters, and the value of assets do not allow the use of large-scale, resource-saving techniques common in wildland fires management. Mapping the WUI represents a first important step in wildfire risk management due to the primary importance of prevention in a setting that is difficult to defend in the face of emergencies. In addition, as the WUI is not only a possible target for wildfires, it is often a source of them, prevention of fire in these areas is a critical part of risk management. Several methods are currently available to detect and map the WUI, differing according to the scale and the scope of the analysis. Pioneering methods mainly used aggregated data (e.g. census data, large scale vegetation maps) while recent techniques are increasingly using high precision remote sensing data to identify single structures and local changes in topography and vegetation. In the context of the UE Interreg project Italia-Slovenija CROSSIT SAFER, a new methodology will be described to analyse and map wildfire risk at the WUI relying on state-of-the-art data and technologies. Specifically, high precision LiDAR data and segmentation processes are used to characterise wildland fuel precisely and efficiently.

New methodology for mapping wildfire risk in the wildland-urban interface.

Flavio Taccaliti
;
Emanuele Lingua
2020

Abstract

Wildfires pose a great threat to the wildland-urban interface (WUI), the zone of contact between wildland vegetation and the human-settled environment. In these areas, high fuel loads often coexist with high value assets, which are more exposed to ignition than equivalent structures in an urban context. At the WUI, wildfires can quickly exhaust the resources normally available to urban firefighters, and the value of assets do not allow the use of large-scale, resource-saving techniques common in wildland fires management. Mapping the WUI represents a first important step in wildfire risk management due to the primary importance of prevention in a setting that is difficult to defend in the face of emergencies. In addition, as the WUI is not only a possible target for wildfires, it is often a source of them, prevention of fire in these areas is a critical part of risk management. Several methods are currently available to detect and map the WUI, differing according to the scale and the scope of the analysis. Pioneering methods mainly used aggregated data (e.g. census data, large scale vegetation maps) while recent techniques are increasingly using high precision remote sensing data to identify single structures and local changes in topography and vegetation. In the context of the UE Interreg project Italia-Slovenija CROSSIT SAFER, a new methodology will be described to analyse and map wildfire risk at the WUI relying on state-of-the-art data and technologies. Specifically, high precision LiDAR data and segmentation processes are used to characterise wildland fuel precisely and efficiently.
2020
EGUsphere
EGU2020: Sharing Geoscience Online
File in questo prodotto:
File Dimensione Formato  
Taccaliti_EGU_2020_abstract.pdf

accesso aperto

Descrizione: Abstract EGU 2020 Taccaliti et al.
Tipologia: Published (publisher's version)
Licenza: Creative commons
Dimensione 291.34 kB
Formato Adobe PDF
291.34 kB Adobe PDF Visualizza/Apri
EGU2020-10583_presentation.pdf

accesso aperto

Tipologia: Published (publisher's version)
Licenza: Creative commons
Dimensione 14.51 MB
Formato Adobe PDF
14.51 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3339178
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
  • OpenAlex ND
social impact