Wildfires threaten and kill people, destroy urban and rural property, degrade air quality,
ravage forest ecosystems, and contribute to global warming. Wildfire management decision …

Due to the harm forest fires cause to the environment and the economy as they occur more
frequently around the world, early fire prediction and detection are necessary. To anticipate …

In recent years, the number of wildfires has increased all over the world. Therefore, mapping
wildfire susceptibility is crucial for prevention, early detection, and supporting wildfire …

The recurrent forest fires have been a serious management concern in southern Western
Ghats, India. This study investigates the applicability of various geospatial data, machine …

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 …

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 …

Floods, one of the most common natural hazards globally, are challenging to anticipate and
estimate accurately. This study aims to demonstrate the predictive ability of four ensemble …

Forest fires are among the major natural disasters that destroy the balance of forest
ecosystems. The construction of a forest fire prediction model to investigate the driving …

This study aims to examine three machine learning (ML) techniques, namely random forest
(RF), LightGBM, and CatBoost for flooding susceptibility maps (FSMs) in the Vietnamese Vu …

In the last decades, natural fire regimes have experienced significant alterations in terms of
intensity, frequency and severity in fire prone regions of the world. Modelling forest fire …