Global lightning-ignited wildfires prediction and climate change projections based on explainable machine learning models.

ABSTRACT: Wildfires pose a significant natural disaster risk to populations and contribute to accelerated climate change. As wildfires are also affected by climate change, extreme wildfires are becoming increasingly frequent. Although they occur less frequently globally than those sparked by human activities, lightning-ignited wildfires play a substantial role in carbon emissions and account for the majority of burned areas in certain regions. While existing computational models, especially those based on machine learning, aim to predict lightning-ignited wildfires, they are typically tailored to specific regions with unique characteristics, limiting their global applicability. In this study, we present machine learning models designed to characterize and predict lightning-ignited wildfires on a glo

SUBMITTER: Shmuel A 

PROVIDER: S-EPMC11885559 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature