Using Google Earth Engine For Large-scale M&e Projects Training Course in Kenya
Introduction:
Google Earth Engine (GEE) is a powerful platform for analyzing large-scale geospatial datasets, ideal for Monitoring and Evaluation (M&E) professionals. This course empowers participants to leverage GEE's cloud-based tools to monitor environmental changes, evaluate project impacts, and measure progress across a range of sectors, including agriculture, disaster management, climate change, and sustainable development. With access to an extensive archive of satellite imagery and geospatial data, participants will learn how to utilize GEE for data processing, analysis, and reporting—providing actionable insights for decision-making in M&E projects.
Target Audience:
This course is designed for professionals involved in Monitoring and Evaluation (M&E), project management, environmental monitoring, and data analysis. Ideal for:
- M&E Specialists
- GIS and Remote Sensing Professionals
- Environmental Analysts
- Government Agencies and NGOs working on large-scale projects
- Researchers and Academics interested in geospatial data analysis
- Development practitioners working in sectors such as agriculture, climate change, and disaster management
Course Objectives:
By the end of the Using Google Earth Engine for Large-Scale M&E Projects course, participants will be able to:
- Understand the Fundamentals of Google Earth Engine (GEE): Gain a solid understanding of GEE's capabilities, tools, and applications for geospatial analysis.
- Perform Data Preprocessing and Analysis: Learn how to access, clean, and process large satellite imagery datasets for M&E purposes.
- Conduct Spatial Analysis for M&E Projects: Utilize GEE for performing land-use classification, change detection, and environmental monitoring over large areas.
- Integrate Remote Sensing Data with GIS Tools: Use GEE alongside GIS platforms for better decision-making and project evaluation.
- Assess the Impact of Development Projects: Leverage satellite data to monitor, measure, and report the effectiveness of large-scale projects in sectors such as agriculture, infrastructure, and health.
- Visualize and Report Results: Develop visualizations and reports that effectively communicate findings to stakeholders and project teams.
- Implement Machine Learning in GEE for M&E: Learn how to apply machine learning algorithms for automating feature extraction, classification, and regression models.
- Monitor and Evaluate Environmental and Social Changes: Understand how to use satellite data to track environmental changes such as deforestation, water quality, and urban development.
- Use GEE for Climate Change Monitoring: Apply GEE to assess climate variability, land degradation, and other critical aspects of sustainable development.
This comprehensive training ensures participants will be proficient in using Google Earth Engine for impactful, data-driven decision-making in large-scale M&E projects, enhancing the ability to track progress and evaluate project outcomes effectively.
Duration
10 Days
Course content
Module 1: Introduction to Google Earth Engine (GEE)
- Overview of Google Earth Engine’s capabilities and features.
- Understanding the cloud-based platform and its benefits for large-scale geospatial analysis.
- Setting up a Google Earth Engine account and basic navigation.
Module 2: Introduction to Satellite Remote Sensing
- Fundamentals of remote sensing and satellite imagery.
- Understanding the types of remote sensing data used in M&E projects.
- Overview of key satellite missions and datasets (Landsat, Sentinel, MODIS).
Module 3: Data Collection and Access in GEE
- Accessing satellite data and geospatial datasets in Google Earth Engine.
- Data import/export options in GEE.
- Using GEE's data catalog to find relevant datasets for M&E.
Module 4: Data Preprocessing and Cleaning in GEE
- Techniques for cleaning raw satellite data (cloud masking, geometric corrections).
- Handling missing data and noise reduction methods.
- Standardizing data for analysis and interpretation.
Module 5: Spatial Analysis for M&E Projects
- Performing land cover classification and change detection using GEE.
- Techniques for analyzing environmental changes such as deforestation and urban expansion.
- Application of geospatial algorithms in project monitoring.
Module 6: Time-Series Analysis for M&E Projects
- Understanding time-series analysis using satellite imagery.
- Techniques for detecting trends and anomalies in geospatial data.
- Analyzing temporal patterns in land use, vegetation, and other environmental factors.
Module 7: Integration of GEE with GIS Tools for Advanced Analysis
- Exporting data from GEE to GIS platforms (ArcGIS, QGIS).
- Integrating GEE outputs with GIS tools for more detailed spatial analysis.
- Creating layered visualizations in GIS for decision support.
Module 8: Visualizing Geospatial Data in Google Earth Engine
- Techniques for visualizing satellite data (maps, charts, and graphs).
- Creating custom visualizations to represent environmental or project data.
- Exporting and sharing visual outputs for reporting.
Module 9: Project Impact Assessment with Remote Sensing
- Using GEE to assess the environmental impact of development projects.
- Measuring changes in land cover, water bodies, and vegetation due to interventions.
- Assessing the success of conservation, reforestation, or infrastructure projects using satellite data.
Module 10: Monitoring Agricultural and Rural Development Projects
- Leveraging GEE to monitor agricultural activities, crop health, and land use changes.
- Using remote sensing to evaluate irrigation and water resource management in agriculture.
- Analyzing rural development initiatives such as roads, schools, and infrastructure using geospatial data.
Module 11: Climate Change Monitoring and Impact Evaluation
- Using GEE for climate change monitoring (temperature, precipitation, sea-level rise).
- Analyzing the effects of climate change on vulnerable regions using satellite data.
- Techniques for assessing the effectiveness of climate adaptation and mitigation projects.
Module 12: Machine Learning in Google Earth Engine for M&E
- Introduction to machine learning techniques available in GEE.
- Supervised and unsupervised classification for land cover detection.
- Using GEE for automated feature extraction and pattern recognition in large datasets.
Module 13: Advanced Data Analysis and Modeling in GEE
- Advanced spatial analysis techniques in GEE (e.g., regression, clustering).
- Modeling and predicting land use changes, deforestation rates, and other M&E metrics.
- Using GEE for environmental modeling in urban planning and disaster risk reduction.
Module 14: Reporting and Communicating Results in M&E Projects
- Best practices for reporting M&E results using Google Earth Engine data.
- Creating dynamic, user-friendly reports with visual maps and charts.
- Presenting findings to stakeholders through interactive dashboards and online platforms.
Module 15: Case Studies and Real-World Applications
- In-depth case studies showcasing the use of Google Earth Engine in large-scale M&E projects.
- Practical exercises on using GEE for monitoring, evaluation, and impact assessment.
- Discussing lessons learned and opportunities for using GEE in various sectors like agriculture, disaster management, and climate change.
These modules offer a comprehensive framework for using Google Earth Engine in large-scale Monitoring & Evaluation projects. The course content ensures a hands-on approach to learning geospatial data analysis, from data preprocessing to advanced modeling and reporting techniques. It equips professionals with the necessary skills to make informed, data-driven decisions for effective project evaluation and environmental monitoring.
Training Approach
This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.
Tailor-Made Course
This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449
Training Venue
The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.
Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant
Certification
Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.
Airport Pickup and Accommodation
Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449
Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 7 working days before commencement of the training.
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| 04/08/2025 - 15/08/2025 | $3000 | Nairobi |
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| 11/08/2025 - 22/08/2025 | $3500 | Mombasa |
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| 18/08/2025 - 29/08/2025 | $3000 | Nairobi |
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| 01/09/2025 - 12/09/2025 | $3000 | Nairobi |
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| 08/09/2025 - 19/09/2025 | $4500 | Dar es Salaam |
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| 15/09/2025 - 26/09/2025 | $3000 | Nairobi |
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| 06/10/2025 - 17/10/2025 | $3000 | Nairobi |
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| 13/10/2025 - 24/10/2025 | $4500 | Kigali |
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| 20/10/2025 - 31/10/2025 | $3000 | Nairobi |
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| 03/11/2025 - 14/11/2025 | $3000 | Nairobi |
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| 10/11/2025 - 21/11/2025 | $3500 | Mombasa |
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| 17/11/2025 - 28/11/2025 | $3000 | Nairobi |
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| 01/12/2025 - 12/12/2025 | $3000 | Nairobi |
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| 08/12/2025 - 19/12/2025 | $3000 | Nairobi |
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| 05/01/2026 - 16/01/2026 | $3000 | Nairobi |
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| 12/01/2026 - 23/01/2026 | $3000 | Nairobi |
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| 19/01/2026 - 30/01/2026 | $3000 | Nairobi |
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| 02/02/2026 - 13/02/2026 | $3000 | Nairobi |
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| 09/02/2026 - 20/02/2026 | $3000 | Nairobi |
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| 16/02/2026 - 27/02/2026 | $3000 | Nairobi |
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| 02/03/2026 - 13/03/2026 | $3000 | Nairobi |
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| 09/03/2026 - 20/03/2026 | $4500 | Kigali |
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| 16/03/2026 - 27/03/2026 | $3000 | Nairobi |
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| 06/04/2026 - 17/04/2026 | $3000 | Nairobi |
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| 13/04/2026 - 24/04/2026 | $3500 | Mombasa |
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| 13/04/2026 - 24/04/2026 | $3000 | Nairobi |
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| 04/05/2026 - 15/05/2026 | $3000 | Nairobi |
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| 11/05/2026 - 22/05/2026 | $5500 | Dubai |
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| 18/05/2026 - 29/05/2026 | $3000 | Nairobi |
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