NH7
Convener: Nikos Koutsias | Co-conveners: Joana ParenteECSECS, Marj Tonini, Mário Pereira, Francesca Di Giuseppe, Mark Parrington, Claudia VitoloECSECS
Displays
| Attendance Tue, 05 May, 14:00–18:00 (CEST)

Wildfires have long been considered as a dynamic ecological factor and an effective agricultural and landscape management tool, but more recently they are increasingly seen as a hazard, which has motivated governments to develop spatio-temporal datasets and to produce risk and prognostic maps. A key factor in this respect is to study the spatial and temporal distribution of wildfires and understand its relationships with the surrounding socio-economic, environmental and climatological factors.
In recent years, innovative algorithms and methodologies have been developed for the analysis of spatially distributed natural hazards and ongoing phenomena such as wildfires. Considering the fast growing availability of high quality digital geo-referenced databases, it is important to develop and promote methods and new tools capable of easily take them into account, especially for large scale analysis. Convert the available datasets into meaningful and valuable information is the new challenge.
This session will bring together wildfire hazard scientists and researchers of various geo-disciplines, economists, managers and people responsible for territorial and urban defense and planning policies. The goal is to improve the understanding of the fire regime and discuss new technologies, methods and strategies to mitigate the disastrous effects of wildfires.
In this context, this session will examine empirical studies, new and innovative technologies, theories, models and strategies for wildfire research, especially to identify and characterize the patterns of spatial and temporal variability of wildfires.

Research topics include, but are not limited to:
• pre- and post-fire assessment: fire incidence mapping and variability, fire severity and damage, including fire-planning and risk management
• development of methodology, based on expert knowledge or data driven, for the recognition, modelling and prediction of structured patterns in wildfires
• fire spread models, ranging from case studies to long-term climatological assessments
• long-term trend patterns: relation between wildfires and global changes (e.g., climate, land use/land cover, socioeconomic)
• fire impacts on the environment, in particular on the atmosphere, human health and natural/anthropogenic environment
• post-fire vegetation recovery and vegetation phenology

Both Oral and Poster presentations are very much encouraged, as we plan to have both lively oral and poster sessions.