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This book discusses vulnerability to natural hazards, method of evaluating vulnerability to natural hazards, and finally evaluation of risk factors that influence the probability that a house will burn from wildfire. A logistic regression is used to analyze 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…mehr

Produktbeschreibung
This book discusses vulnerability to natural hazards, method of evaluating vulnerability to natural hazards, and finally evaluation of risk factors that influence the probability that a house will burn from wildfire. A logistic regression is used to analyze 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 measures and strategies for wildfire risk reduction including vegetation treatments, site selection with respect to topography, and improving access to fire stations.
Autorenporträt
Uddhab Bhandary, PhD, received his doctoral degree in Design & Planning from the University of Colorado in 2007. He has been teaching courses as a lecturer and conducting research in environmental planning. He espouses quantitative research including GIS and remote sensing. Dr. Bhandary has an international teaching, research and field experiences.