15 Topics
5 Days
45 Sessions
Programme Overview
Training Description
M&E professionals looking to integrate GIS into their project monitoring frameworks.
Project managers who want to use spatial data to track project progress and impact.
GIS analysts and researchers who want to expand their knowledge in the application of GIS in M&E.
Development professionals, NGOs, government agencies, and environmental organizations working with spatial data for decision-making and reporting.
Anyone interested in leveraging open-source GIS tools like QGIS and Google Earth Engine for spatial analysis in M&E contexts.
Session Objectives
- Master QGIS and Google Earth Engine: Gain proficiency in using open-source GIS tools for spatial data analysis and mapping. Enhance M&E Activities: Learn to integrate GIS and remote sensing data into M&E activities for better project monitoring and impact assessment. Understand Spatial Data Collection: Understand best practices in spatial data collection and how to manage geospatial data for M&E purposes. Visualize Data Effectively: Develop skills to visualize data through maps, charts, and other visual tools to communicate project outcomes clearly. Apply GIS to Project Monitoring: Understand how to use GIS for planning, monitoring, and evaluating various development projects. Conduct Spatial Analysis: Learn how to perform advanced spatial analysis and derive actionable insights to improve project results and effectiveness. Explore Open-Source Alternatives: Understand the advantages of using open-source GIS tools, ensuring cost-effective and sustainable data management in M&E projects. This training course will empower participants to utilize open-source GIS tools to enhance their M&E efforts, improve spatial data management, and derive actionable insights to track project performance and drive better decision-making.
About the Course
The Open-Source GIS for Monitoring & Evaluation (M&E) Training Course equips professionals with the essential skills to effectively apply Geographic Information Systems (GIS) in the monitoring and evaluation of projects. Leveraging powerful open-source platforms such as QGIS and Google Earth Engine, participants will learn how to collect, analyze, and visualize spatial data to enhance project monitoring, reporting, and decision-making. This training emphasizes the use of freely accessible GIS tools to make geospatial data more affordable, accessible, and impactful for M&E practitioners, offering them the flexibility to perform sophisticated spatial analysis without the need for costly proprietary software..
Curriculum & Topics
15 Topics | 45 Sessions
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Workshop 1.1:
Understanding GIS in the context of Monitoring & Evaluation.
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Workshop 1.2:
Overview of spatial data and its relevance to project monitoring and impact assessment.
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Workshop 1.3:
Introduction to open-source GIS tools: QGIS and Google Earth Engine.
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Workshop 2.1:
Setting up QGIS for M&E applications.
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Workshop 2.2:
Navigating the QGIS interface: tools, menus, and functions.
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Workshop 2.3:
Importing and visualizing spatial data in QGIS.
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Workshop 3.1:
Understanding raster and vector data.
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Workshop 3.2:
Introduction to spatial data formats: shapefiles, GeoJSON, KML, and more.
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Workshop 3.3:
Choosing the right data formats for monitoring & evaluation projects.
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Workshop 4.1:
Data Collection and Management for M&E
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Workshop 4.2:
Managing and organizing geospatial data in QGIS.
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Workshop 4.3:
Importing and integrating remote sensing data for M&E applications.
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Workshop 5.1:
Introduction to Google Earth Engine (GEE) and its capabilities for M&E.
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Workshop 5.2:
Setting up a Google Earth Engine account and interface.
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Workshop 5.3:
Importing and visualizing satellite imagery and other geospatial data in GEE.
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Workshop 6.1:
Performing basic spatial analysis: buffering, overlay, and proximity analysis.
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Workshop 6.2:
Analyzing spatial patterns and relationships in M&E projects.
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Workshop 6.3:
Data querying and filtering techniques in QGIS.
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Workshop 7.1:
Conducting advanced analysis such as interpolation, network analysis, and spatial statistics.
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Workshop 7.2:
Using spatial analysis to assess project outcomes and impact.
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Workshop 7.3:
Geospatial modeling for predicting trends in M&E projects.
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Workshop 8.1:
Analyzing satellite imagery for land cover and land use monitoring.
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Workshop 8.2:
Time-series analysis for tracking environmental changes and project impact.
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Workshop 8.3:
Leveraging GEE for large-scale spatial data analysis and visualization.
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Workshop 9.1:
Designing effective maps for project reports and presentations.
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Workshop 9.2:
Customizing map styles, symbology, and labels.
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Workshop 9.3:
Exporting and printing maps for reporting purposes.
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Workshop 10.1:
Integrating various data sources for comprehensive spatial analysis.
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Workshop 10.2:
Combining field data, remote sensing, and survey results.
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Workshop 10.3:
Enhancing M&E insights through data integration.
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Workshop 11.1:
Creating interactive maps and visualizations for M&E reporting.
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Workshop 11.2:
Visualizing trends and patterns in project progress.
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Workshop 11.3:
Sharing maps and spatial data outputs with stakeholders.
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Workshop 12.1:
Real-time monitoring using spatial data to track project activities.
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Workshop 12.2:
Assessing project performance through spatial analysis.
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Workshop 12.3:
Using geospatial data to evaluate project sustainability.
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Workshop 13.1:
Ensuring data quality and accuracy in GIS-based M&E systems.
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Workshop 13.2:
Techniques for validating and cleaning spatial data.
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Workshop 13.3:
Identifying and addressing data gaps in M&E systems.
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Workshop 14.1:
Evaluating the effectiveness of projects using GIS tools.
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Workshop 14.2:
Conducting impact analysis through spatial data analysis.
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Workshop 14.3:
Reporting M&E results based on GIS insights.
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Workshop 15.1:
Best practices in using GIS for Monitoring and Evaluation.
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Workshop 15.2:
Future trends in GIS and remote sensing for development projects.
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Workshop 15.3:
Exploring new technologies like machine learning and AI in geospatial data analysis for M&E.
