AIMS AND CONTENT

LEARNING OUTCOMES

The module aims to provide students with basic concepts of assessment and management of wildfire risk. The module will impart the necessary knowledge to understand the processes and ground and meteorological conditions related to the occurrence of fires in agro-forestry environments, with particular attention to the temporal dynamics of local fire danger extremes. The purpose of the course is to provide an overview of the global issue of wildfires, focusing on the various aspects involved in this type of risk, including the effects of climate change. At the end of the course, the student will be able to use and interpret the most common systems for quantifying wildfire danger; interpret susceptibility, hazard, and wildfire risk maps; and identify data sources and techniques necessary for constructing these maps. Additionally, the student will be familiar with the main fire propagation models and their role in firefighting actions and scenario generation.

AIMS AND LEARNING OUTCOMES

Aims of the course is to transfer knowledge on the main processes related with the occurrence and the behavior of forest fires considering all the aspects involved, including cause of ignition, vegetation, topography, meteorology and climate, coping capacity. Tools and methods for wildfire risk assessment will be presented both considering static and dynamic mapping. The students at the end of the course will be able to:

• understand the phenomena: causes, regimes, impacts
• create wildfire risk maps
• predict fire danger
• suggest prevention activities
• simulate the potential behavior of wildfires
• support decisions in firefighting activities
• evaluate the potential impacts of wildfires
• analyze wildfire risk scenarios

TEACHING METHODS

Theoretical aspects will be presented through frontal lectures. Practical aspects of data analysis and wildfire risk mapping will be approached through laboratory activities. Python language and Jupyter environment will be adopted. The students are encouraged to work in small groups, with particular attention to the final project that will be evaluated during the exam. It is suggested to attend all the classes and the exercises in laboratory. Field trips and seminars will be organized. 

Students with valid certifications for Specific Learning Disorders (SLDs), disabilities or other educational needs are invited to contact the teacher and the School's contact person for disability at the beginning of teaching to agree on possible teaching arrangements that, while respecting the teaching objectives, take into account individual learning patterns. Contacts of the teacher and the School's disability contact person can be found at the following link: Comitato di Ateneo per l’inclusione delle studentesse e degli studenti con disabilità o con DSA | UniGe | Università di Genova

SYLLABUS/CONTENT

• Introduction to the module
• Overview of wildfire regimes and impacts
• The phases of wildfire risk management: prevention & preparedness, response, restoration & recovery
• Static wildfire risk assessment: susceptibility, hazard, vulnerability and risk
• Fire spread simulators: physical and empirical approaches
• Dynamic wildfire danger assessment and early warning systems

RECOMMENDED READING/BIBLIOGRAPHY

Teaching materials will be provided to the students during the lessons, including slides, scientific papers, reports, etc.

LESSONS

LESSONS START

https://corsi.unige.it/en/corsi/10553/studenti-orario

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

The exam consists in an oral session where it is strongly suggested to present the results of the project assigned during the laboratory activities. Theoretical questions concerning the whole set of topics presented during the Wildfire Risk Assesment and Management module will complete the evaluation of the students.

ASSESSMENT METHODS

The oral exam will assess the following capacities:

• understanding the main drivers of wildfire
• producing wildfire risk maps
• knowledge on different approaches to predict fire danger
• suggesting effective prevention activities
• evaluating the potential impacts of wildfires
• analyzing wildfire risk scenarios
• implementing in Python environment routines for risk mapping and data analysis

FURTHER INFORMATION

Please, ask directly the professor for other information not included in the teaching schedule.