Fire danger assessment in Iran based on geospatial information

• A fire ignition and propagation probability model was developed for Iran.
• The fire ignition probability map shows higher probability for detected fires (mean p = 0.65) than for areas without detected fires (mean p = 0.4). The logistic regression correctly classified 72.7% of fire occurrence.
• Fire propagation probability was found significantly associated to burned area (p = 0.69, p < 0.001). Most of burned areas have been located in the higher values of fire propagation probability map.

Fire danger assessment is a vital issue to alleviate the impacts of wildland fires. In this study, a fire danger assessment system is proposed, which extensively uses geographical databases to characterize the spatial variations of fire danger conditions in Iran. This assessment requires three steps: (i) generation of the required input variables, (ii) methods to integrate those variables for creating synthetic indices and (iii) validation of those indices versus fire occurrence data. This fire danger model is based on previous works but adapted to Iranian conditions. It includes an estimation of the fire ignition potential (both considering human and climatic factors) and fire propagation potential. The former was generated from a logistic regression approach based on a wide range of input variables. The fire propagation probability was estimated from the Flammap fire behavior model. A first stage for validation of our fire danger system was based on comparing the estimated danger values to actual fire occurrence, based on satellite detected active fires and burned areas. The logistic regression model for fire ignition probability estimated 72.7% of true ignitions. Detected hotspots occurred more frequently in areas with higher fire ignition probability (average value: 0.65) than non hotspots (average value: 0.4). Propagation probability showed higher values for areas with higher proportion of burned area (r = 0.68, p < 0.001).