PGA GIS Course IV: GIS for WASH Programs

Perk Group Africa Explore the world of spatial analysis and cartography with GIS

Target Audience

The course is designed for WASH specialists, M & E Experts, Public health, Program Manager, Students, Risk assessors, water engineers, and individuals who require knowledge and skills on the use of GIS in their organization for WASH programs.

Description

The focus of WASH programs is to facilitate water resources management, water quality monitoring, and promotion of good hygiene and sanitation practices in order to improve and protect health. GIS, on the other hand, is known for giving a spatial dimension to data by allowing users to view different types of data inform of layers, they are used to perform analysis and eventually publish a map.

GIS, when integrated with WASH, enables users to create models of complex environments making them easy to understand. This in turn aids in proper and informed decision making which speeds up the implementation of programs.

This training exposes participants to the use of GIS for WASH programs with respect to Data Sources, Mapping, Applications, Technology, and Timeline for implementation.

Course Outline

  • Introduction and definition of WASH and GIS concepts
  • GIS Data Management
  • Development and presentation of maps
  •  The use of GIS and Remote Sensing in monitoring WASH projects
  • Multi-Criteria analysis and its applications
  • Participatory GIS for WASH
  • Use of Mobile Phones for Data Collection
  • Statistical data analysis for WASH

Learning Objectives

By the end of the course, delegates will be able to:

  • Evaluate the spatial data requirements in Water Sanitation and Hygiene;
  • Use GIS and RS as a tool for monitoring WASH projects;
  • Assess spatial data availability and understand the importance of Spatial Data Infrastructure in WASH programs;
  • Use participatory GIS (PGIS) at the community level;
  • Collect data using Mobile data gathering tools;
  • Design and implement their own GIS projects that integrate remote sensing data, GPS-based field information in a proper geospatial framework