Format: Live instructor-led online training via Zoom / Microsoft Teams

Time Series Satellite Data Analytics Training Course

Time Series Satellite Data Analytics Training Course is a comprehensive professional development program designed to equip participants with advanced knowledge and practical skills in analyzing, interpreting, and utilizing multi-temporal satellite datasets for environmental monitoring, climate change assessment, agriculture, disaster management, urban development, natural resource management, and sustainable development planning. As Earth Observation missions continuously generate massive volumes of satellite imagery and geospatial information, organizations increasingly require professionals capable of extracting meaningful trends, patterns, anomalies, and predictive insights from long-term satellite data records. This course provides participants with the expertise necessary to transform time series satellite data into actionable geospatial intelligence that supports evidence-based planning and decision-making.

The course focuses on the principles of time series analysis, satellite data acquisition, temporal image processing, trend detection, change monitoring, statistical analysis, machine learning applications, and geospatial modeling. Participants will learn how to process and analyze large volumes of multi-temporal satellite imagery from platforms such as Landsat, Sentinel, MODIS, and other Earth Observation systems. Through practical exercises and real-world projects, learners will gain hands-on experience in data preprocessing, temporal analysis, anomaly detection, forecasting, visualization, and interpretation of long-term environmental and socio-economic changes.

Participants will explore advanced applications including vegetation dynamics monitoring, climate variability assessment, drought and flood monitoring, land use and land cover change analysis, agricultural productivity forecasting, urban growth monitoring, ecosystem health assessment, water resource management, and disaster resilience planning. The course also covers cloud computing platforms, Google Earth Engine workflows, artificial intelligence, deep learning, big geospatial data analytics, and predictive modeling techniques. These competencies enable organizations to improve monitoring systems, strengthen forecasting capabilities, optimize resource management, and support sustainable development goals.

Upon completion of the training, participants will be capable of designing and implementing time series satellite analytics projects, developing monitoring and forecasting systems, generating geospatial intelligence products, and supporting strategic decision-making through advanced Earth Observation technologies. The acquired skills will strengthen institutional capacity in geospatial analytics, climate resilience, environmental management, and evidence-based policy development. The course combines instructor-led presentations, practical laboratory exercises, collaborative group work, web-based tutorials, and applied case studies to ensure comprehensive learning and practical implementation.

Course Objectives

1.     Understand the principles and methodologies of time series satellite data analytics.

2.     Acquire, preprocess, and manage multi-temporal satellite datasets effectively.

3.     Apply temporal analysis techniques to detect trends and patterns.

4.     Conduct land use and land cover change monitoring using satellite imagery.

5.     Analyze environmental and climate-related changes using Earth Observation data.

6.     Apply machine learning and artificial intelligence in time series analysis.

7.     Utilize cloud-based geospatial platforms for large-scale data processing.

8.     Develop predictive models and forecasting systems using satellite datasets.

9.     Support evidence-based planning and policy formulation through geospatial intelligence.

10.  Strengthen institutional capacity in Earth Observation and geospatial analytics.

Organizational Benefits

1.     Improve environmental monitoring and natural resource management capabilities.

2.     Enhance climate change adaptation and resilience planning.

3.     Strengthen disaster preparedness and risk reduction systems.

4.     Improve agricultural monitoring and food security initiatives.

5.     Support sustainable urban planning and infrastructure development.

6.     Enhance forecasting and early warning systems.

7.     Improve monitoring, evaluation, and reporting frameworks.

8.     Strengthen evidence-based decision-making processes.

9.     Increase efficiency through automated geospatial analytics.

10.  Build sustainable institutional capacity in satellite data analytics and Earth Observation technologies.

Target Participants
GIS Specialists, Remote Sensing Analysts, Environmental Officers, Climate Change Specialists, Agricultural Officers, Natural Resource Managers, Urban Planners, Engineers, Disaster Management Professionals, Researchers, Data Scientists, Monitoring and Evaluation Specialists, Government Officials, Development Practitioners, Water Resource Managers, ICT Professionals, Policy Analysts, and professionals involved in geospatial information management and Earth Observation initiatives.

Course Outline

Module 1: Introduction to Time Series Satellite Data Analytics

·       Fundamentals of time series analysis

·       Overview of Earth Observation systems

·       Multi-temporal satellite data concepts

·       Applications of time series analytics

·       Sources of satellite datasets

·       Emerging trends in geospatial analytics

General Case Study: Establishing a national environmental monitoring framework using time series satellite data.

Module 2: Satellite Data Acquisition and Management

·       Landsat, Sentinel, MODIS, and commercial satellite platforms

·       Data acquisition strategies

·       Metadata and documentation standards

·       Geospatial database development

·       Data storage and management systems

·       Data quality assessment procedures

General Case Study: Building a multi-temporal satellite imagery repository for long-term monitoring projects.

Module 3: Data Preprocessing and Correction Techniques

·       Radiometric correction methodologies

·       Atmospheric correction procedures

·       Geometric correction techniques

·       Image registration and alignment

·       Noise reduction methods

·       Quality control and validation

General Case Study: Preparing long-term satellite datasets for vegetation trend analysis.

Module 4: Temporal Analysis and Trend Detection

·       Time series decomposition techniques

·       Seasonal trend analysis

·       Temporal pattern identification

·       Anomaly detection methodologies

·       Statistical trend analysis

·       Temporal visualization techniques

General Case Study: Identifying long-term environmental changes through temporal satellite analysis.

Module 5: Land Use and Land Cover Change Analytics

·       Land cover classification methodologies

·       Change detection techniques

·       Urban growth analysis

·       Deforestation monitoring systems

·       Land degradation assessment

·       Landscape dynamics analysis

General Case Study: Monitoring urban expansion using historical satellite imagery.

Module 6: Vegetation and Agricultural Monitoring

·       Vegetation index analysis

·       Crop growth monitoring systems

·       Agricultural productivity assessment

·       Precision agriculture applications

·       Drought stress detection

·       Food security monitoring frameworks

General Case Study: Forecasting crop performance using satellite time series datasets.

Module 7: Climate Change and Environmental Monitoring

·       Climate variability assessment

·       Ecosystem monitoring systems

·       Carbon stock analysis

·       Biodiversity monitoring applications

·       Environmental impact assessment

·       Sustainable development indicators

General Case Study: Monitoring climate-induced environmental changes using Earth Observation data.

Module 8: Water Resources and Hydrological Applications

·       Surface water monitoring techniques

·       Watershed management applications

·       Flood monitoring systems

·       Drought assessment methodologies

·       Water quality monitoring

·       Hydrological trend analysis

General Case Study: Evaluating long-term water resource changes through satellite analytics.

Module 9: Disaster Risk Reduction and Resilience

·       Hazard monitoring frameworks

·       Disaster impact assessment

·       Early warning systems development

·       Emergency response support applications

·       Post-disaster recovery monitoring

·       Resilience planning methodologies

General Case Study: Developing flood early warning systems using time series satellite data.

Module 10: Machine Learning and Artificial Intelligence Applications

·       Machine learning fundamentals

·       Deep learning techniques for temporal analysis

·       Predictive modeling methodologies

·       Automated classification systems

·       Anomaly detection using AI

·       Big geospatial data analytics

General Case Study: Applying AI algorithms to automate environmental monitoring and forecasting.

Module 11: Cloud Computing and Geospatial Platforms

·       Google Earth Engine applications

·       Cloud-based geospatial analytics

·       Large-scale data processing workflows

·       Geospatial web services

·       Data sharing and collaboration systems

·       Enterprise analytics solutions

General Case Study: Processing multi-year satellite datasets using cloud computing platforms.

Module 12: Decision Support Systems and Future Trends

·       Integration with GIS and decision support systems

·       Geospatial dashboards and reporting tools

·       Policy and planning applications

·       Digital twin technologies

·       Real-time Earth Observation systems

·       Future developments in time series satellite analytics

General Case Study: Designing a national geospatial decision support platform using time series satellite data.

General Information

1.     Customized Training: All our courses can be tailored to meet the specific needs of participants.

2.     Language Proficiency: Participants should have a good command of the English language.

3.     Comprehensive Learning: Our training includes well-structured presentations, practical exercises, web-based tutorials, and collaborative group work. Our facilitators are seasoned experts with over a decade of experience.

4.     Certification: Upon successful completion of training, participants will receive a certificate from Foscore Development Center (FDC-K).

5.     Training Locations: Training sessions are conducted at Foscore Development Center (FDC-K) centers. We also offer options for in-house and online training, customized to the client's schedule.

6.     Flexible Duration: Course durations are adaptable, and content can be adjusted to fit the required number of days.

7.     Onsite Training Inclusions: The course fee for onsite training covers facilitation, training materials, two coffee breaks, a buffet lunch, and a Certificate of Successful Completion. Participants are responsible for their travel expenses, airport transfers, visa applications, dinners, health/accident insurance, and personal expenses.

8.     Additional Services: Accommodation, pickup services, freight booking, and visa processing arrangements are available upon request at discounted rates.

9.     Equipment: Tablets and laptops can be provided to participants at an additional cost.

10.  Post-Training Support: We offer one year of free consultation and coaching after the course.

11.  Group Discounts: Register as a group of more than two and enjoy a discount ranging from 10% to 50%.

12.  Payment Terms: Payment should be made before the commencement of the training or as mutually agreed upon, to the Foscore Development Center account. This ensures better preparation for your training.

13.  Contact Us: For any inquiries, please reach out to us at training@fdc-k.org or call us at +254712260031.

14.  Website: Visit our website at www.fdc-k.org for more information.