Coat of Arms of Vanuatu

Advanced training on Earth Observation (EO) and Geospatial Information Technology (GIT) Applications for Climate Resilience

Course Content

The course will start with recalling the basics concepts of GIS and Remote Sensing learned from the first training session. The following sessions will also provide them with theoretical understanding of advanced remote sensing and Land Use/Land Cover (LULC) mapping. The participants will then utilise time series satellite imagery to understand change in the landcover. Additionally, the participants will develop a rapid response mapping and post-disaster damage assessment based on the Tropical Cyclone Harold. Towards the end of the session the participants will be introduced to web mapping tools.

Learning Objectives

At the end of this course participants should be able to:

  • Recall the basic concepts of Geographic Information System and Remote Sensing 
  • Apply digital image processing techniques for Land Use Land Cover (LULC) mapping from satellite images 
  • Assess the landcover change using time-series satellite images (time series change detection – visual interpretation or band analysis?) 
  • Develop a Population Exposure Analysis for Tropical Cyclones
  • Utilise satellite imagery for post-disaster damage assessment
  • Develop web-based products to convey clear and concise decision support information  
  • Design priority case studies in GIT applications for Climate Resilience 

Chapter 1: Review of Introductory Training

During the Introductory training held in November 2019, we had the chance to learn basic concepts and functions in QGIS. This module will serve as refresher through games and role-play.

Chapter 2: Land Cover Change Detection using Remote Sensing Index (NDVI)

Land cover classification is the process of assigning land cover classes to a pixel of remote sensing image. You will be familiarized with a technique for land cover change detection through NDVI, using EO Browser and QGIS.

Chapter 3: Rapid Response Mapping in Emergency Situations

In this chapter we are going to perform Population Exposure Analysis in case Tropical Cyclone Harold using some geoprocessing functionalities of QGIS.

Chapter 4: Post Disaster Damage Assessment Trough Visual Interpretation of Satellite Images

Quantitative estimation of building damages is extremely important after a disastrous event. In this exercise you are going to use a Very High-Resolution Satellite images to compare and detect the damages.

Chapter 5: Web Mapping as Decision Support Information

Web Mapping is a service through which the consumers can choose what they want to show on the map. This exercise will give you a foundation for using QGIS plugin and uploading the result to a website that make your web map accessible by other users.