This study provides a new comparative analysis of four hybrid artificial intelligence models
for the spatially explicit prediction of wildfire probabilities. Each model consists of an …

Turkey has a high forest fire potential along the Aegean and Mediterranean coasts, related
to climate and extremely sensitive forests. In Turkey over 10,000-ha forest area has been …

This research investigates the efficiency of combining the Analytical Network Process (ANP)
and fuzzy logic for developing a fire risk map. Major factors influencing the occurrence of …

Wildfire susceptibility maps display the spatial probability of an area to burn in the future,
based solely on the intrinsic local proprieties of a site. Current studies in this field often rely …

This article aims to provide a more practical forest fire spread model for predicting and
managing forest fires in Heilongjiang Province, China. Heilongjiang is dominated by …

Turkey is exposed to forest fires damaging thousands of hectares of forest every year. Earlier
studies indicate that Turkey would be one of the most affected Mediterranean countries due …

Forest fires are among the most major causes of global ecosystem degradation. The
integration of spatial information from various sources using statistical analyses in the GIS …

Wildfire susceptibility is a measure of land propensity for the occurrence of wildfires based
on terrain's intrinsic characteristics. In the present study, two stochastic approaches (ie …

Considerable economic losses and ecological damage can be caused by forest fires, and
compared to suppression, prevention is a much smarter strategy. Accordingly, this study …

The optimization of forest management in roadsides is a necessary task in terms of wildfire
prevention in order to mitigate their effects. Forest fire risk assessment identifies high-risk …