Course overview
The GIS, Remote Sensing and Geospatial Analytics for Sustainable Development Seminar equips professionals with practical skills to collect, process, analyze, and visualize geospatial data to support sustainable development planning, environmental management, climate resilience, and evidence-based decision-making. The seminar explores Geographic Information Systems (GIS), satellite remote sensing, spatial statistics, geospatial databases, and Earth observation technologies for understanding land-use change, natural resource distribution, urban growth, environmental risks, and socioeconomic inequalities.
Participants learn to apply open-source and professional geospatial tools to map development indicators, monitor environmental change, assess climate-related risks, and produce decision-support maps and analytical reports. The training emphasizes practical applications aligned with the United Nations Sustainable Development Goals (SDGs), including sustainable cities, climate action, responsible resource management, food security, and ecosystem conservation.
Course objectives
- sustainable development. Collect, validate, manage, and integrate spatial data from field surveys, satellite imagery, and open geospatial sources. Perform advanced GIS operations, spatial analysis, and suitability modeling. Process and analyze satellite imagery using Landsat, Sentinel, and cloud-based geospatial platforms. Apply remote sensing techniques to land-use mapping, environmental monitoring, and change detection. Use geospatial indicators to assess climate risks, natural hazards, agricultural conditions, and natural resources.
- Develop a practical geospatial decision-support project and communicate findings through maps and technical reports.
- Evaluate spatial data quality, classification accuracy, analytical uncertainty, and map reliability.
- Apply geospatial analytics to relevant Sustainable Development Goals and development indicators.
- Create interactive maps, web GIS applications, and dashboards for development monitoring.
- Develop geospatial databases and automate spatial workflows using PostGIS and Python.
- Apply GIS to urban planning, infrastructure development, service accessibility, and spatial inequality analysis.
Who should attend
GIS Professionals, Remote Sensing Specialists, Geospatial Analysts, Environmental Officers, Environmental Scientists, Sustainable Development Professionals, Urban Planners, Regional Planners, Land Surveyors, Cartographers, Environmental Consultants, Climate Change Analysts, Disaster Risk Management Officers, Natural Resource Managers, Agricultural Officers, Water Resource Professionals, Forestry Officers, Conservation Professionals, Transport Planners, Infrastructure Development Professionals, Monitoring and Evaluation Officers, Development Planning Officers, NGO Professionals, Government Planning Officers, Research Scientists, Data Analysts, Spatial Data Scientists, GIS Developers, Geospatial Database Administrators, Humanitarian Response Professionals, Public Health Mapping Professionals, Development Consultants, University Researchers, GIS and Remote Sensing Students.
Course content
- Module 1: Foundations of GIS and Sustainable Development GIS concepts and spatial data types, vector and raster data, coordinate reference systems, geospatial data sources, SDGs and spatial indicators, GIS applications in development planning, spatial dec
- Module 2: Geospatial Data Collection and Management Field data collection, GPS and mobile mapping, OpenStreetMap, KoboToolbox and ODK, satellite and administrative datasets, geospatial data quality, metadata, coordinate transformation, data validation.
- Module 3: Advanced GIS Mapping and Spatial Analysis QGIS and ArcGIS Pro, geoprocessing, spatial joins, buffering, overlay analysis, proximity analysis, suitability modeling, terrain analysis, spatial interpolation, cartographic design.
- Module 4: Remote Sensing and Satellite Image Processing Satellite imagery principles, Landsat and Sentinel missions, spatial and spectral resolution, image preprocessing, atmospheric correction concepts, band combinations, spectral indices, supervised and
- Module 5: Google Earth Engine and Cloud-Based Geospatial Analytics Google Earth Engine, JavaScript and Python workflows, satellite image collections, image filtering, cloud masking, temporal composites, vegetation indices, large-scale raster analysis, aut
- Module 6: Land Use, Land Cover and Environmental Change Detection Land-use classification, training data preparation, classification accuracy assessment, confusion matrices, change detection, deforestation monitoring, urban expansion, ecosystem degradatio
- Module 7: Climate Change, Natural Hazards and Disaster Risk Mapping Climate-related geospatial indicators, flood susceptibility mapping, drought monitoring, wildfire risk, erosion assessment, terrain and hydrological analysis, exposure mapping, vulnerabil
- Module 8: Sustainable Agriculture, Water and Natural Resource Management Agricultural suitability analysis, crop monitoring, vegetation health, soil and land degradation, watershed analysis, water resource mapping, irrigation planning, biodiversity conser
- Module 9: Urban Planning, Infrastructure and Sustainable Cities Urban growth analysis, settlement mapping, transport accessibility, service coverage, infrastructure planning, population distribution, spatial inequality, site suitability, green space analy
- Module 10: Geospatial Databases, Automation and Spatial Data Science PostgreSQL and PostGIS, spatial SQL, spatial indexing, GeoServer, Python geospatial libraries, GeoPandas, Rasterio, Shapely, automated geoprocessing, spatial statistics, reproducible ana
- Module 11: Geospatial Dashboards, Web GIS and Development Indicators Interactive maps, web mapping, Leaflet, web GIS publishing, geospatial dashboards, development indicator mapping, SDG monitoring, spatial data visualization, stakeholder reporting, map a
- Module 12: Integrated Geospatial Analytics for Sustainable Development Sustainable development problem formulation, geospatial methodology design, data integration, multi-criteria spatial analysis, environmental and socioeconomic assessment, results valid
General notes
- GIS Data Acquisition and Quality Assessment, GPS and Mobile Field Data Collection, QGIS Spatial Analysis, Spatial Buffer and Overlay Analysis, Multi-Criteria Site Suitability Mapping, Sentinel-2 Satellite Image Processing, Landsat Land-Cover Classification, NDVI Vegetation Health Analysis, NDWI Water Feature Mapping, Google Earth Engine Time-Series Analysis, Land Use and Land Cover Change Detection, Deforestation and Ecosystem Monitoring, Flood Susceptibility Mapping, Drought Monitoring Using Satellite Indicators, Watershed and Terrain Analysis, Agricultural Suitability Assessment, Urban Expansion and Built-Up Area Mapping, Population and Service Accessibility Analysis, PostGIS Spatial Database Development, Python-Based Geospatial Data Processing, Interactive Web GIS Map Development, SDG Indicator Mapping, Sustainable Development Geospatial Dashboard Design, Final Integrated GIS and Remote Sensing Project.
- Tools and technologies QGIS, ArcGIS Pro, Google Earth Engine, ESA SNAP, Copernicus Data Space Ecosystem, USGS EarthExplorer, Landsat Satellite Data, Sentinel-1 and Sentinel-2 Data, PostgreSQL, PostGIS, GeoServer, GeoPandas, Rasterio, Shapely, GDAL, Python, Jupyter Notebook, Leaflet, OpenStreetMap, KoboToolbox, ODK, Google Earth, digital elevation models, satellite-derived environmental indices, spatial statistics tools.
Frequently asked questions
1. 1.Who should attend this seminar?
The seminar is suitable for GIS professionals, environmental practitioners, planners, development specialists, researchers, natural resource managers, and professionals working with spatial data.
2. 2. What will I learn during the training?
You will learn GIS mapping, satellite image processing, spatial analysis, environmental change detection, climate risk mapping, geospatial database management, and development indicator visualization.
3. 3. Which software and tools are covered?
The seminar covers QGIS, Google Earth Engine, satellite imagery from Landsat and Sentinel missions, PostGIS, Python geospatial libraries, and web GIS technologies.
4. 4. Does the seminar include practical exercises?
Yes. Participants complete hands-on mapping, satellite image analysis, environmental monitoring, spatial database development, and web mapping exercises using practical datasets.
5. 1. How is the training relevant to sustainable development?
It demonstrates how geospatial information supports environmental protection, climate resilience, sustainable agriculture, urban planning, infrastructure development, natural resource management, and SDG monitoring.
Schedule & fees
| Dates | Location | Duration | Fee (USD) |
|---|
| 05/04/2027 - 16/04/2027 |
Nairobi,kenya or Virtual |
10 Days |
$2,000 |
| 05/07/2027 - 06/07/2027 |
Kigali,Rwanda |
10 Days |
$2,000 |
| 02/08/2027 - 13/08/2027 |
Accra,Ghana |
10 Days |
$4,000 |