https://giscience.github.io/gis-training-resource-center/content/intro.html

5.6. Exercises for Module 5

These exercises touch on all the content of module 5.

Exercise	Description	Focus Group	Estimated time
Exercise 1: Health site distribution in the Saint Louis region	The aim of this exercise is to become familiar with different types of spatial analysis and geoprocessing tools and understand the process of discovering relationships and connections between features in spatial data. The goal is to determine which health sites in the Saint Louis region in Senegal are prone to flooding. We will make use of Buffers, Classification, Selecting by location, and selecting using an expression.	Data analysis	3 hours
Exercise 2: Disaster impact in different regions of Senegal	Become familiar with different types of non-spatial analysis and geoprocessing tools. Understand the process of discovering relationships and connections between features in spatial data.	Data analysis	3 hours
Exercise 3: Trigger & Intervention Map for Forecast-based-Action	This exercise is based on the monitoring and triggering process used by the Somalia Red Crescent Society (SRCS) in the framework of a drought Early Action Protocol (EAP). In this exercise, you will build a simplified version of the monitoring and trigger mechanism for the FEWSNET projection pillar.	Data analysis, Early Action Protocol, Monitoring & Triggering	6 hours
Exercise 4: Security Peshawar		Data analysis	3 hours
Exercise 5: Aggregate and Assess G2P Money Transfers in Pakistan	The exercise teaches how to aggregate data on administrative levels and subsequently join the aggregated data with a polygon dataset.	Data analysis and creating reports	60 minutes
Exercise 6: Calculate vulnerability index Part 1	We want to create an overview of different vulnerability indicators. Using a Covid-19 risk indicators dataset, we take % permanent wall type, % permanent roof type and poverty incidence. Using Uganda population statistics, we calculate the % of under fives and % of elderly. By combining the data, we are now able to visualise the areas in Uganda that are most vulnerable.	Data analysis (spatial joins)	45 - 60 minutes
Exercise 8: Estimating Exposed Population – Aina’s Manual Approach	This exercise teaches how to buffer cyclone track and use zonal statistics to estimate the population in the cyclone buffer	Data analysis	2 hours
Exercise 9: Public Health Part 2	The aim of this exercise is to aggregate data on district-level, calculate zonal statistics and use the field calculator to calculate the incidence rate of measles in a fictious scenario.	Public health workers	3 hours