Incorporating airborne LiDAR into reliable and scalable garden wildfire hazard assessments at the wildland–urban interface

Background The creation of defensible space, an area around the house where fuel is managed according to specific guidelines, can reduce ignition and fire spread, mitigating wildfire threat to communities. Remote sensing approaches can facilitate assessments of defensible spaces. Aims To develop a protocol to evaluate which defensible space hazards can be accurately assessed using Light Detection and Ranging (LiDAR). Methods We used high and low point density airborne LiDAR to measure hazards in 31 gardens in southeast Tasmania (Australia) based on alignment with defensible space guidelines. We compared the resulting ‘garden hazard scores’ with those generated from field observations to identify garden characteristics that can be estimated using LiDAR, as well as the best analysis resolution to do so. Key results We found a good association between field data and LiDAR measures of vegetation cover and spatial arrangement, but not plant flammability, inferred using Normalised Difference Vegetation Index (NDVI), or flammable objects. Low-density LiDAR consistently underestimated cover metrics compared with High-density LiDAR. Nonetheless, garden hazard scores calculated using either high- or low-density LiDAR yielded results similar to those obtained using only field observations. Implications LiDAR can be used to conduct semi-automatic, large-scale measurements of some, albeit not all, critical garden hazards.

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Publication Details

Journal
International Journal of Wildland Fire
Published
2026-01-06
DOI
https://doi.org/10.1071/wf25218
Primary Topic
Fire effects on ecosystems
Type
article
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article

Incorporating airborne LiDAR into reliable and scalable garden wildfire hazard assessments at the wildland–urban interface

Scott M. Foyster, David M. J. S. Bowman, Stefania Ondei, Grant Williamson
International Journal of Wildland Fire
Fire effects on ecosystems
article

Incorporating airborne LiDAR into reliable and scalable garden wildfire hazard assessments at the wildland–urban interface

Scott M. Foyster, David M. J. S. Bowman, Stefania Ondei, Grant Williamson
article en

Abstract

Background The creation of defensible space, an area around the house where fuel is managed according to specific guidelines, can reduce ignition and fire spread, mitigating wildfire threat to communities. Remote sensing approaches can facilitate assessments of defensible spaces. Aims To develop a protocol to evaluate which defensible space hazards can be accurately assessed using Light Detection and Ranging (LiDAR). Methods We used high and low point density airborne LiDAR to measure hazards in 31 gardens in southeast Tasmania (Australia) based on alignment with defensible space guidelines. We compared the resulting ‘garden hazard scores’ with those generated from field observations to identify garden characteristics that can be estimated using LiDAR, as well as the best analysis resolution to do so. Key results We found a good association between field data and LiDAR measures of vegetation cover and spatial arrangement, but not plant flammability, inferred using Normalised Difference Vegetation Index (NDVI), or flammable objects. Low-density LiDAR consistently underestimated cover metrics compared with High-density LiDAR. Nonetheless, garden hazard scores calculated using either high- or low-density LiDAR yielded results similar to those obtained using only field observations. Implications LiDAR can be used to conduct semi-automatic, large-scale measurements of some, albeit not all, critical garden hazards.

International Journal of Wildland FireVol. 35(3)
University of Tasmania (AU), RMIT University (AU)
Sustainable cities and communities
Openalex Percentile: Top 97%
Fire effects on ecosystems
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Incorporating airborne LiDAR into reliable and scalable garden wildfire hazard assessments at the wildland–urban interface — Scott M. Foyster, David M. J. S. Bowman, et al. · International Journal of Wildland Fire (2026) | TGRS Research Map | TGRS