Training on AI-Powered Satellite Image Classification & Land Cover Mapping
Learn AI-powered satellite image classification and land cover mapping using machine learning, remote sensing, GIS, and geospatial analytics.
Next intake
20 Jul 2026 · Nakuru
Duration
10 days
Live instruction
Delivery
Physical + Virtual
Cohort based
Level
Advanced
Working professionals
Certification
NITA reimbursable
For Kenyan cohorts
Language
English
All materials
About this programme
Artificial Intelligence (AI) is revolutionizing satellite image analysis by enabling faster, more accurate, and automated classification of land cover and land use patterns. This course equips participants with practical skills in applying AI and machine learning techniques to satellite imagery for environmental monitoring, land cover mapping, urban planning, agriculture, forestry, disaster management, and natural resource assessment.
Through hands-on exercises, real-world datasets, and practical case studies, participants will learn how to process satellite imagery, develop AI-based classification models, generate land cover maps, assess classification accuracy, and utilize geospatial intelligence for data-driven decision-making. The course combines remote sensing, GIS, and AI technologies to support modern geospatial analysis and digital transformation initiatives.
Duration
10 Days
Who Should Attend:
- GIS Analysts and Specialists
- Remote Sensing Professionals
- Environmental Officers
- Urban and Regional Planners
- Forestry and Natural Resource Managers
- Agricultural Specialists
- Researchers and Academics
- Data Scientists
- Government Geospatial Officers
- Development Practitioners
What you'll walk away with
By the end of the training, participants will be able to:
- Understand the fundamentals of AI, remote sensing, and satellite image classification.
- Process and prepare satellite imagery for analysis.
- Apply machine learning and AI techniques for land cover classification.
- Develop and validate land use and land cover mapping models.
- Utilize geospatial analytics for environmental and resource management.
- Assess classification accuracy and model performance.
- Implement AI-powered workflows for large-scale geospatial projects.
What we cover, module by module
Module 1: Introduction to AI, Remote Sensing & Land Cover Mapping
- Fundamentals of AI and machine learning
- Introduction to remote sensing
- Satellite imagery and sensors
- Land use and land cover concepts
- Applications across sectors
- Case Study: AI applications in environmental and agricultural monitoring.
- Practical Exercise: Explore and interpret satellite imagery datasets.
Module 2: Satellite Data Acquisition & Preprocessing
- Sources of satellite imagery
- Image correction and enhancement
- Data cleaning and preprocessing
- Spectral bands and indices
- Preparing datasets for AI analysis
- Case Study: Preparing satellite imagery for land cover classification projects.
- Practical Exercise: Preprocess and organize satellite imagery datasets.
Module 3: GIS & Remote Sensing Integration
- GIS fundamentals for image analysis
- Spatial data management
- Coordinate systems and projections
- Geospatial data integration
- Image visualization techniques
- Case Study: Integrating GIS and remote sensing for spatial planning.
- Practical Exercise: Create geospatial datasets for AI-based mapping.
Module 4: Machine Learning for Image Classification
- Supervised and unsupervised learning
- Training datasets and feature selection
- Classification algorithms
- Model development workflows
- AI tools for geospatial analysis
- Case Study: Applying machine learning to classify land cover categories.
- Practical Exercise: Develop a basic image classification model.
Module 5: Advanced AI Techniques for Land Cover Mapping
- Deep learning concepts
- Convolutional Neural Networks (CNNs)
- Object-based image analysis
- Automated feature extraction
- Large-scale classification approaches
- Case Study: Deep learning applications in satellite image interpretation.
- Practical Exercise: Build an AI-driven land cover classification workflow.
Module 6: Land Use & Land Cover Classification
- Classification schemes and standards
- Vegetation and land cover indices
- Agricultural land classification
- Urban and infrastructure mapping
- Environmental monitoring applications
- Case Study: Mapping agricultural and urban land use changes.
- Practical Exercise: Generate a land cover classification map.
Module 7: Accuracy Assessment & Validation
- Classification accuracy assessment
- Error matrices and validation techniques
- Ground truth data collection
- Model improvement strategies
- Quality assurance procedures
- Case Study: Evaluating classification performance in environmental projects.
- Practical Exercise: Conduct accuracy assessment for a classification model.
Module 8: Change Detection & Monitoring
- Temporal image analysis
- Land cover change detection
- Environmental monitoring techniques
- Deforestation and degradation assessment
- Disaster and risk monitoring
- Case Study: Monitoring land cover changes using AI and satellite imagery.
- Practical Exercise: Analyze land cover changes over multiple time periods.
Module 9: Cloud-Based Geospatial AI Platforms
- Cloud computing for geospatial analysis
- AI-powered mapping platforms
- Big geospatial data processing
- Collaborative geospatial workflows
- Automation and scalability
- Case Study: Large-scale land cover mapping using cloud-based technologies.
- Practical Exercise: Develop a cloud-based geospatial analysis workflow.
Module 10: AI-Powered Mapping Project & Action Planning
- Project planning and implementation
- Workflow optimization
- Geospatial reporting and visualization
- Stakeholder communication
- Future trends in AI and remote sensing
- Case Study: Successful implementation of AI-powered land cover mapping projects.
- Practical Exercise: Develop and present an AI-Powered Satellite Image Classification & Land Cover Mapping Project Plan.
Where the change lands
Individual Impact
- Apply AI techniques to satellite image analysis.
- Improve remote sensing and GIS analytical skills.
- Generate accurate land cover and land use maps.
- Enhance expertise in modern geospatial technologies.
Organizational Impact
- Faster and more accurate land cover mapping.
- Improved environmental and resource monitoring.
- Enhanced decision-making through geospatial intelligence.
- Increased efficiency in large-scale mapping and analysis projects.
Dates and locations
Upcoming intakes
Every intake is limited to a small cohort. Booking closes when a date fills or three weeks before the start, whichever comes first.
| City | Starts | Ends | Delivery | Book |
|---|---|---|---|---|
NakuruNext | 20 Jul 2026 | 31 Jul 2026 | In-Person | Book |
Kigali | 20 Jul 2026 | 31 Jul 2026 | In-Person | Book |
Accra | 20 Jul 2026 | 31 Jul 2026 | In-Person | Book |
Kisumu | 27 Jul 2026 | 07 Aug 2026 | In-Person | Book |
Johannesburg | 27 Jul 2026 | 07 Aug 2026 | In-Person | Book |
Dakar | 27 Jul 2026 | 07 Aug 2026 | In-Person | Book |
- NakuruNext
20 Jul → 31 Jul·In-Person
Book this intake - Kigali
20 Jul → 31 Jul·In-Person
Book this intake - Accra
20 Jul → 31 Jul·In-Person
Book this intake - Kisumu
27 Jul → 07 Aug·In-Person
Book this intake - Johannesburg
27 Jul → 07 Aug·In-Person
Book this intake - Dakar
27 Jul → 07 Aug·In-Person
Book this intake
Common questions.
Still not sure? Send us a note and a facilitator will get back to you within a business day.
You may also like.
Programmes in the same discipline that participants often pair with this course.
Hybrid10 daysLearn AI and computer vision for urban growth monitoring and informal settlement mapping using satellite imagery, GIS, deep learning, and spatial analytics.
Hybrid10 daysLearn AI-powered disaster damage assessment using satellite imagery, machine learning, GIS, and remote sensing for rapid response and recovery planning.
Hybrid10 daysLearn AI-powered water body and flood extent mapping using SAR data, machine learning, GIS, and remote sensing for disaster management and water resources.
Course finder
Find the right course for you
Prefer to talk it through? Send us an enquiry and a facilitator will scope a fit within a business day.
For corporate teams
Training 10+ professionals?
We deliver Training on AI-Powered Satellite Image Classification & Land Cover Mapping in-house at your offices, at a venue we arrange, or fully virtual. Customise the curriculum against your KPIs, and get a bespoke price for the cohort size you need.