Structure-level fuel load assessment in the wildland–urban interface: a fusion of airborne laser scanning and spectral remote-sensing methodologies
Nicholas S. Skowronski A , Scott Haag B , Jim Trimble C , Kenneth L. Clark D , Michael R. Gallagher D and Richard G. Lathrop C E
+ Author Affiliations
- Author Affiliations
A USDA Forest Service, Northern Research Station, 180 Canfield Street, Morgantown, WV 26505, USA.
B The Patrick Center for Environmental Research, Academy of Natural Sciences of Drexel University, 1900 Benjamin Franklin Parkway, Philadelphia, PA 19103, USA.
C Center for Remote Sensing and Spatial Analysis, Rutgers University, 14 College Farm Road, New Brunswick, NJ 08901, USA.
D USDA Forest Service, Northern Research Station, 501 Four Mile Road, New Lisbon, NJ 08064, USA.
E Corresponding author. Email: lathrop@crssa.rutgers.edu
International Journal of Wildland Fire 25(5) 547-557 https://doi.org/10.1071/WF14078
Submitted: 7 May 2014 Accepted: 16 July 2015 Published: 10 September 2015
Abstract
Large-scale fuel assessments are useful for developing policy aimed at mitigating wildfires in the wildland–urban interface (WUI), while finer-scale characterisation is necessary for maximising the effectiveness of fuel reduction treatments and directing suppression activities. We developed and tested an objective, consistent approach for characterising hazardous fuels in the WUI at the scale of individual structures by integrating aerial photography, airborne laser scanning and cadastral datasets into a hazard assessment framework. This methodology is appropriate for informing zoning policy questions, targeting presuppression planning and fuel reduction treatments, and assisting in prioritising structure defence during suppression operations. Our results show increased variability in fuel loads with decreasing analysis unit area, indicating that fine-scale differences exist that may be omitted owing to spatial averaging when using a coarser, grid-based approach. Analyses using a local parcel database indicate that approximately 75% of the structures in this study have ownership of less than 50% of the 30 m buffer around their building, illustrating the complexity of multiple ownerships when attempting to manage fuels in the WUI. Our results suggest that our remote-sensing approach could augment, and potentially improve, ground-based survey approaches in the WUI.
Additional keywords: Light detection and ranging (LiDAR), risk assessment, wildfire hazard.
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