CS-5202-SLB
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 the participants with theoretical understanding of advanced remote sensing and Land Cover detection. The participants will then learn how to conduct building damage assessment and population exposure analysis for tropical cyclones. Towards the end of the session the participants will be introduced to online GIS applications and will develop a case study.
Learning Objectives
At the end of this course participants should be able to:
- Recall the basic concepts of Geographic Information System and Remote Sensing
- Calculate vegetation index from satellite image and perform land cover change detection
- Develop a population exposure analysis for tropical cyclones wind hazard
- Assess building damage from tropical cyclone using very high-resolution satellite images
- 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.