Land use planning and wildfire risk mitigation: an analysis of wildfire-burned subdivisions using high-resolution remote sensing imagery and GIS data

Abstract

This paper evaluates risk factors that influence the probability that a house will burn from wildfire. A logistic regression is used to analyse data processed from pre-fire and post-fire IKONOS images and other geo-referenced data. The dependent variable is the probability that a given house will burn. A total of 12 independent variables are evaluated: vegetation density; area of defensible space; adjacency of a parcel to public lands; proximity of a house to fire station; road width; road type; parcel size; subdivision morphology; assessed value; elevation; slope and aspect. Model results generally support dominant land use planning and design strategies for wildfire risk reduction including vegetation treatments, site selection with respect to topography, and improving access to fire stations.

Keywords:

• wildfire
• vulnerability
• IKONOS
• logistic regression
• Wildland-Urban Interface
• the western United States

Acknowledgements

The authors would like to acknowledge and thank Willem Van Vliet, Fahriye Sancar, Konrad Steffen and Mark Mclean for their inputs. Konrad Steffen also provided funding support to purchase IKONOS images used for this research. The authors would also like to thank the three anonymous reviewers for their comments.

Notes

1. “It includes homes, schools, workplaces, parks/recreation areas, greenways, business areas and transportation systems. It extends overhead in the form of electric transmission lines, underground in the form of waste disposal sites and subway trains, and across the country in the form of highways. It includes land-use planning and policies that impact our communities in urban, rural and suburban areas” (NEIHS 2006).

2. UTM Zone 13 NAD 1983.

3. State Plane, Colorado Central FIPS 0502 feet, NAD 1983.

4. UTM Zone 13 NAD 1983.