Spatial and Temporal Monitoring of Wildfire Hazard Under a Climate Change Environment: Prevention, Mitigation and Management

Wildfire is a natural phenomenon that may become a disaster if it crosses the boundaries of natural and anthropogenic ecosystems. During the last 20 years (2001 – 2021), 119 million ha of tree cover have been consumed by fires on a global scale, accounting for almost 37% of total tree cover loss. Fire history may highlight the interlinkages of ecological and socio-economic dimensions. Indicatively, in the USA, the mean annual number of wildfire ignitions are 70,000, burning approximately 2.8 million ha, whereas the annual suppression cost reached about $ 4.4 billion in 2021 (the highest since 1985). The interrelation between climate change and wildfires has been proven and highlighted by the large volume of research conducted on this issue. Future projections predict that, under a climate change environment, the fire season (especially in Southern Europe) will be prolonged, with higher duration and severity of droughts, leading to higher fire severity and burned area, as was the case of 2021 fires in Greece. The increasing fire intensity and the number of ignitions create a vicious circle, reinforcing the climate change effect. This argument can be supported by the highest carbon emissions released during 2022 from the EU and United Kingdom for the last 15 years, as well as, by the highest number of August fire ignitions in the Amazon in the last decade.

The purpose of this special issue is to highlight recent research related to the spatial and temporal monitoring of wildfire hazards, linked with the climate change dimensions of wildfire hazard dynamics. This synergy can potentially allow spatially determining and developing of the most appropriate preventative measures in the most vulnerable regions. Within this context, interdisciplinary approaches are highly welcome. The contribution of geospatial technologies (GIS; remote sensing; google earth engine), big data analytics (using artificial intelligence algorithms, R, Python and other programming languages), wildfires and climate change modelling (e.g., wildfire simulations, weather research and forecasting modelling) could reveal the historical and future patterns of wildfire hazard. Based on these outcomes, the most suitable preventative measures may be proposed to mitigate the future wildfire intensity and the corresponding climate change effect on wildfire hazards.
This Research Topic welcomes manuscripts that showcase unique empirical strategies and novel data sources, novel theoretical and philosophical contributions and/or integrate findings and theories across multiple disciplines.

The recommendations may include the following subjects, but they are not limited to these topics only:
- Integration of geospatial technologies (GIS; remote sensing; google earth engine) to historical and future wildfire hazard estimation.
- Big data analytics (artificial intelligence algorithms; geostatistics; R; Python and other programming languages) for historical and future wildfire hazard estimation.
- Wildfires simulation and modelling (burn and fire ignitions probability; fire exposure; fire effects).
- Climate change modelling (fire weather indices; weather research and forecasting modelling; drought indices; climatological multi-hazard estimation).
- Prevention, mitigation and management processes.

Keywords: wildfires, climate change, spatial and temporal patterns of hazard and ignitions, geospatial technologies, artificial intelligence, wildfire hazard projection, Prevention mitigation and management processes, big data

Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.