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 …

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

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

Forest fires (FF) in tropical seasonal forests impact ecosystem. Addressing FF in tropical
ecosystems has become a priority to mitigate impacts on biodiversity loss and climate …

In the hilly region of the Western Himalayas, forest fires play a crucial role in forest
destruction and biodiversity loss. Therefore, addressing the problem of forest fires is an …

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 …

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 …

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 pose significant challenges by disrupting ecological balance, impacting socio-
economic harmony, and raising global concerns. North-East India (NEI) experiences high …

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 …