Remote Sensing for Marine Litter and Plastic Pollution Monitoring Course

Course Introduction

Marine litter and plastic pollution have become critical environmental challenges of the 21st century, threatening marine ecosystems, coastal livelihoods, fisheries, tourism, and human health. With global plastic production continuing to rise, monitoring and management have become urgent priorities for sustainability and ocean governance.

Traditional monitoring approaches, while useful, are often limited in scope and time. They cannot fully capture the scale, movement, and accumulation of plastic debris across large marine and coastal environments. Remote sensing technologies provide transformative capabilities for filling this gap through large-scale, continuous, and data-driven observation.

This course introduces participants to cutting-edge applications of remote sensing for tracking marine litter and plastic pollution. It covers both satellite-based and drone-based monitoring approaches, offering insights into detecting floating plastics, mapping hotspots, and modeling transport pathways.

Participants will learn how to access, process, and analyze Earth observation data for marine pollution assessment. They will explore advanced tools, including multispectral and hyperspectral imagery, machine learning algorithms, and oceanographic data integration to improve detection accuracy.

Through practical exercises and case studies, learners will apply remote sensing techniques to real-world scenarios, building capacity to support decision-making in marine conservation, policy, and pollution management strategies.

By the end of the course, participants will have the knowledge and skills to employ remote sensing as a powerful tool in combating plastic pollution and safeguarding marine environments for future generations.

Who Should Attend

• Marine and coastal resource managers
• Environmental scientists and oceanographers
• Remote sensing and GIS professionals
• Climate change and sustainability practitioners
• NGOs and international organizations in marine conservation
• Government agencies responsible for coastal and marine policy
• Researchers and academics in ocean studies
• Professionals working in fisheries and blue economy sectors

Duration

5 days

Course Objectives

• Equip participants with knowledge of remote sensing technologies for detecting, tracking, and monitoring marine litter.
• Develop practical skills in using satellite and drone imagery for mapping plastic pollution hotspots in marine environments.
• Train learners to process multispectral and hyperspectral data to improve accuracy in identifying marine plastic waste.
• Build capacity to integrate oceanographic and remote sensing data for modeling litter transport pathways.
• Strengthen analytical skills for applying machine learning in marine plastic pollution detection and classification.
• Provide knowledge on assessing ecological, social, and economic impacts of marine litter using geospatial tools.
• Develop strategies for using remote sensing data to inform policy, marine governance, and international agreements.
• Enhance capacity to evaluate effectiveness of plastic reduction and cleanup interventions through spatial analysis.
• Introduce emerging technologies such as AI, drones, and cloud platforms for marine litter monitoring and research.
• Foster understanding of the role of remote sensing in advancing global commitments to ocean sustainability and SDGs.

Comprehensive Course Outline

Module 1: Introduction to Marine Litter and Plastic Pollution

• Global overview of marine litter challenges
• Sources, pathways, and impacts of plastic pollution
• Importance of monitoring for policy and management
• Role of Earth observation in marine pollution research

Module 2: Fundamentals of Remote Sensing in Marine Environments

• Principles of remote sensing for ocean monitoring
• Satellite sensors and platforms for marine observation
• Drone applications for coastal and nearshore pollution mapping
• Data sources, formats, and limitations

Module 3: Detecting Marine Plastics with Remote Sensing

• Spectral characteristics of plastics in multispectral imagery
• Hyperspectral data for advanced detection accuracy
• Algorithms for floating plastic identification
• Case studies of detection success in different regions

Module 4: Mapping Marine Litter Hotspots

• Spatial distribution analysis of marine litter
• GIS-based mapping of accumulation zones
• Linking pollution hotspots to human activity and currents
• Temporal monitoring of seasonal and long-term trends

Module 5: Modeling Plastic Transport Pathways

• Oceanographic data integration with remote sensing
• Modeling wind, currents, and waves in debris transport
• Predictive modeling of plastic accumulation zones
• Tools for early warning of pollution risks

Module 6: Emerging Technologies for Marine Litter Monitoring

• AI and machine learning in marine plastic detection
• Drone swarms and autonomous ocean vehicles
• Cloud-based platforms for real-time analysis
• Future innovations in Earth observation for pollution

Module 7: Assessing Impacts of Marine Litter

• Ecological impacts on marine biodiversity
• Socioeconomic costs for fisheries and tourism
• Human health implications of plastic pollution
• GIS-based frameworks for impact assessment

Module 8: Remote Sensing for Policy and Governance

• Data-driven marine litter action planning
• International agreements and marine pollution commitments
• Integrating remote sensing data into national policies
• Decision-support systems for marine governance

Module 9: Monitoring Cleanup and Mitigation Efforts

• Evaluating effectiveness of cleanup operations
• Tracking progress toward plastic reduction targets
• Spatial analysis of interventions and outcomes
• Remote sensing for adaptive management strategies

Module 10: Future Directions and Best Practices

• Global best practices in marine litter monitoring
• Innovations in blue economy and pollution control
• Remote sensing contributions to SDGs 14 and 13
• Collaborative approaches for scaling monitoring solutions

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: training@upskilldevelopment.com Tel: +254 721 331 808

Training Venue

The training will be held at our Upskill 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 Upskill 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: training@upskilldevelopment.com, +254 721 331 808

Terms of Payment

Unless otherwise agreed between the two parties payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better