Semester Course: 3rd 
Credits: 6 ECTS
Lecturers: Dr. Felipe Bravo

Course webpage:

  1. Objectives:
    Students will be able to design, manage and apply techniques on
    (i) Geographical Information Systems,
    (ii) Spatial Statistics
    (iii) Spatial pattern analysis. Besides that, students will be able to critically select, read and assess scientific literature related with the course.
  2. Programme topics:
    1. FOUNDATIONS:Introduction to spatial data analysis, GIS principles and QGIS foundations, Introduction to R software, Visualizing and exploring data (with R),·Classes for Spatial Data in R, Principles of LiDAR and Airborne Laser Scanning (ALS)
    2. DATA GATHERING: Importing data in R and QGIS, Georeferencing maps with QGIS, ALS-based Forest inventory: Area Based (ABA), Enhanced Area based (EABA) approaches and Individual tree detection methods (ITD), TLS-based Forest inventory
    3. DATA ANALYSIS: QGIS forestry related tools:  Digitizing and updating forest stands, ALS-based forest management planning: cell based vs segment based forest planning, Modelling: stand level models with ALS data, Basic Knowledge in Spatial Statistics and Spatial Point Patterns, Geostatistics , Spatial Regression Models
    4. CASE STUDIES: Tree size and species mingling, Monitoring changes: Systematic sampling of forest stands, Forest stands maps
  3. Assessment:
    Course requirements include active participation (10%), the presentation of a class summary (10%), a class project (30%) and a final exam (50%)