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CODE 94658
ACADEMIC YEAR 2022/2023
CREDITS
SCIENTIFIC DISCIPLINARY SECTOR ING-INF/04
LANGUAGE English
TEACHING LOCATION
  • SAVONA
SEMESTER 1° Semester
MODULES Questo insegnamento è un modulo di:
TEACHING MATERIALS AULAWEB

AIMS AND CONTENT

LEARNING OUTCOMES

The course will provide the knowledge needed to understand the processes related with fire occurrence in the agro-forest environment. An overview of the problem of wildfires at global level will be introduced focusing on the several aspects involved in this kind of risk, including climate change. Firstly, the main aspects related with wildfire hazard will be analyzed. Techniques for assessing wildfire danger maps will be approached. In addition, the effects of meteorological variability will be described in order to predict local extremes in wildfire danger conditions. Tools and methodologies for the prediction of wildfire danger will be used and described. Finally, exposed elements and vulnerability will be introduced in order to evaluate risk and emergency scenarios through the application of simulation tools. The students will be able to make use of the knowledge acquired during the classes in order to provide support to decision makers both in prevention phase and suppression.

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. 

SYLLABUS/CONTENT

  • Introduction to the course
  • 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.

TEACHERS AND EXAM BOARD

Exam Board

ANGELA CELESTE TARAMASSO (President)

GIORGIO ROTH

PAOLO FIORUCCI (President Substitute)

LESSONS

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 course will complete the evaluation of the students.

Students with learning disorders ("disturbi specifici di apprendimento", DSA) will be allowed to use specific modalities and supports that will be determined on a case-by-case basis in agreement with the delegate of the Engineering courses in the Committee for the Inclusion of Students with Disabilities.

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

Exam schedule

Data appello Orario Luogo Degree type Note
09/01/2023 11:00 SAVONA Scritto + Orale
13/02/2023 11:00 SAVONA Scritto + Orale
20/06/2023 11:00 SAVONA Scritto + Orale