Course Overview

This crash course provides a practical introduction to GIS and remote sensing techniques applied to wildfire analysis. Participants will learn how to access, preprocess, and visualize satellite data, map burned areas, and create simple fire progression and recovery indicators using open-source tools such as QGIS. The course focuses on geospatial methods rather than fire modeling, making it suitable for researchers and professionals seeking applied analytical skills within the X-Fire community.

Course Structure

The course is structured over 3 days (2 hours per day = 6 hours total), combining short lectures with hands-on exercises using QGIS and real wildfire datasets.

DAY 1 — Core GIS Foundations for Wildfire Applications (2 hours)

Focus on GIS principles, spatial data types, Geoprocessing, and building geospatial workflows.

  • 1.1 Intro to GIS for Wildfire Applications: Contribution to wildfire work (mapping, exposure, decision support) and GIS workflow.
  • 1.2 Spatial Data Types & Structure: Vector vs Raster, Resolution, Projections, and Coordinate systems.
  • 1.3 GIS Data for Wildfire Analysis: Vector: Fire perimeters, hotspots, road networks, settlements. & Raster: Land cover, DEM, population grid, fuel types.
  • 1.4 Essential GIS Geoprocessing Tools: Clip, Intersect, Buffer, Resample, and hands-on practical tasks (e.g., calculating area of land cover categories within perimeter).

DAY 2 — Burned Area Mapping + GIS Analytical Layers (2 hours)

  • 2.1 Burned Area Workflow: Extracting fire footprint using NBR/dNBR rasters, classifying burned vs unburned, and cleaning polygons.
  • 2.2 Terrain Analysis: Understanding the role of topography (Slope, Aspect, Elevation) and deriving attributes in QGIS.
  • 2.3 Integrating GIS Layers - Exposure Analysis: Overlay analysis, Zonal statistics, and calculating exposure (e.g., % forest burned, proximity to infrastructure).

DAY 3 — GIS-Based Risk, Mapping, and Decision Support (2 hours)

  • 3.1 Wildfire Impact & Risk Mapping Using GIS: Weighted overlay, normalize variables, and creating composite risk layers.
  • 3.2 Case Study Integration: Building a full GIS pipeline from data loading to analysis and visualization.
  • 3.3 Map Production & Reporting: Layout creation, legends, exporting maps, and styling best practices.

Who can attend?

Everyone participating to X-Fire 2026 can apply to attend the crash course. There will be a maximum of 20 seats available.

If interest exceeds capacity, selection will follow these criteria:

  1. Background relevance (GIS, remote sensing, environmental sciences, forestry, geography, civil protection).
  2. Priority to Early Career Researchers with limited skills in GIS.
  3. Motivation statement submitted at registration.
  4. Gender, regional, and institutional balance (COST inclusiveness principles).

Requirements

  • Bring a personal laptop.
  • Install QGIS (latest Long Term Release) before the course.
  • Download the training datasets (to be shared beforehand).
  • Optional: Sign up for Google Earth Engine (for data access demonstration).