Synergy of GIS and Remote Sensing Data in Forest Fire Danger Modeling

摘要: Forest fires constitute an important problem for the environment degradation. In this paper, we propose a Dynamic Fire Risk Index (DFRI) that takes into account different static and dynamic factors of risk fire occurrence. Variables like insolation hours, vegetation cover, altitude, slope, proximity to main roads, statistics have been used develop Static (SFRI) using logistic regression model. Using satellite data derive water stress forest, new index is defined weighting with actual value indicators. This methodology has previously tested some in Canary Islands (Spain), and, case, prove its usefulness both NOAA-AVHRR Terra-MODIS sensors data. As test sites, two took place September 2005 on La Palma Island August 2007 Tenerife (Canary Islands, Spain) considered order validate suitability these tools regional scale application, area where multiple microclimates are present mainly due steep orography trade winds.