Urban forestry strategic fire protection via a susceptibility model

We present an adaptive system for automatic assessment of both physical and anthropic fire impact factors on peri-urban forestries. The aim is to provide an integrated methodology exploiting a complex data structure. This structure is built upon a multi resolution grid gathering historical land exploitation and meteorological data, records of human habits along with suitably segmented and interpreted high resolution X-SAR images, and several other information sources. The contribution of the model and its novelty relies manly on the definition of a learning schema lifting different factors and aspects of fire causes, including physical, social and behavioral ones, to the design of a fire susceptibility map of a specific urban forestry. The outcome is an integrated geospatial database providing an infrastructure that merges cartography, heterogeneous data and complex analysis. It establishes a digital environment where users and tools are interactively connected in an efficient and flexible way. © 2012 Taylor & Francis Group.