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Advanced GIS

Syllabus

Introduction to Spatial Analysis (3 hours lecture)

  • Common spatial analysis techniques
  • Introduction to spatial analysis tools in QGIS/WebGIS

Advanced Spatial Analysis Techniques (3 hours lecture, 3 hours exercises)

  • Spatial statistics and analyses
  • Practical exercises in QGIS

GIS Toolboxes and Plugins (1 hour lecture, 3 hours exercises)

  • Overview of GIS toolboxes and plugins
  • Processing Toolbox in QGIS
  • Practical exercises with GIS toolboxes and plugins

Building GIS Models I (3 hours exercises)

  • Introduction to model building in GIS
  • Model Designer in QGIS
  • Creating basic models

Building GIS Models II (4 hours exercises)

  • Advanced model building techniques
  • Introduction to Python scripting for GIS
  • Integrating scripts in models
  • Practical model building exercises

Precision Farming with GIS (1 hour lecture, 1 hour exercises)

  • Introduction to precision farming concepts
  • Role of GIS in precision farming

Computing Management Zones (1 hour lecture, 2 hours exercises)

  • Methods for computing management zones
  • Practical exercises in computing management zones using FieldCalc/QGIS

Using Apps to Display and Analyze Sensor Data (3 hours lecture, 2 hour exercises)

  • Collecting and integrating sensor data in GIS
  • Case studies using apps for data display and analysis
  • Practical exercises with SensLog Dashboard/FIE

Case Studies and Practical Applications (10 hours lab sessions)

  • Detailed case studies in precision farming
  • Project planning and implementation
  • Real-world applications and success stories
  • Student-led case study presentations

The homework will include: 20 hrs literature analysis, GIS terminology, and individual study.

Objectives and Competences

Course objectives:

  • To advance students' knowledge in spatial analysis and GIS toolboxes.
  • To provide skills in building GIS models for complex spatial problems.
  • To explore real-world applications of GIS, with a focus on precision farming.
  • To integrate digital tools and apps for data collection, display, and analysis in GIS projects.

Competences:

  • Proficiency in advanced spatial analysis techniques.
  • Ability to use and customize GIS toolboxes.
  • Skills in building and implementing GIS models.
  • Practical experience in applying GIS to precision farming and analyzing sensor data.

Intended Learning Outcomes

Students that will successfully attend the course will be able to:

  • Conduct advanced spatial analysis using GIS.
  • Utilize and customize various GIS toolboxes for specific tasks.
  • Build and apply GIS models to solve spatial problems.
  • Implement digital tools and apps in precision farming projects.
  • Analyze and interpret sensor data for agricultural applications.