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

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.     

Delivering Arsenic-free Drinking Water-Made Practically Possible: Continuous Scale Electrochemical Arsenic Remediation Process Furnished,based on Experimental Studies and ANN Simulation

Environment, Development and Sustainability - Arsenic (As) in groundwater has become a worldwide concern due to its high toxicity as it is classified as a potent carcinogen, when exposed to...