Artificial intelligence (AI) holds significant promise for advancing natural disaster
management through the use of predictive models that analyze extensive datasets, identify …

Forest fires significantly disrupt global ecosystems. Many forecasting techniques predict fire
activity and allocate prevention resources, but various factors are missing from the …

Wildfire susceptibility maps play a crucial role in preemptively identifying regions at risk of
future fires and informing decisions related to wildfire management, thereby aiding in …

Soil temperature is a key parameter in many disciplines, and its research has important
practical significance. In recent years, the prediction of soil temperature by deep learning …

Forest fires pose a serious risk to ecosystems in the Mediterranean region; thus, 2021 fires
in the Mediterranean region of Türkiye emphasize the requirement for accurate and …

Adaptation to an increasingly dry regional climate requires spatially explicit information
about current and future risks. Existing drought risk studies often rely on expert-weighted …

Wildfire risk increases following non-fire disturbance events, but this relationship is not
always linear or cumulative, and previous studies are not consistent in differentiating …

Global karst vegetation is crucial for carbon sequestration and biodiversity conservation.
However, research on the carbon sink capacity of vegetation and its potential driving …

Since 2018, severe droughts have affected a significant part of central Europe, causing
premature leaf senescence in European beech (Fagus sylvatica L.). The correlation …

Blue water (BW) and green water (GW) are crucial components of the hydrological cycle, but
their accurate simulation and interpretation remain challenging in data-scarce basins. We …