This intensive training course is designed to provide participants with a comprehensive understanding of how remote sensing technologies are utilized to monitor, analyze, and assess climate change impacts. Participants will gain in-depth knowledge of various satellite sensors, data acquisition techniques, and advanced processing methods crucial for extracting climate-relevant information from remotely sensed data. The course emphasizes practical application, enabling attendees to confidently use remote sensing data for climate research, policy development, and adaptation strategies.
The curriculum covers a wide array of topics, beginning with the fundamental principles of remote sensing and its specific applications to climate change. It progresses through detailed discussions on different satellite missions, data pre-processing, and the use of remote sensing for monitoring atmospheric, oceanic, terrestrial, and cryospheric climate variables. Advanced modules will delve into time-series analysis, integration with climate models, and the application of machine learning for climate studies, ensuring participants are equipped with cutting-edge skills for effective climate change monitoring.
Who should attend the training
- Climate Scientists and Researchers
- Environmental Managers and Policy Makers
- GIS Specialists and Remote Sensing Analysts
- Meteorologists and Oceanographers
- Urban Planners and Resource Managers
- Postgraduate Students in Earth Sciences
Objectives of the training
- Understand the fundamental principles of remote sensing and its relevance to climate change.
- Identify and utilize various satellite missions and sensors for climate monitoring.
- Master techniques for acquiring, pre-processing, and analyzing remote sensing data.
- Apply remote sensing methods to monitor atmospheric, oceanic, terrestrial, and cryospheric climate variables.
- Gain proficiency in time-series analysis of remote sensing data for trend detection.
- Learn to integrate remote sensing data with climate models for enhanced understanding.
- Explore advanced applications of machine learning in climate change remote sensing.
Personal benefits
- Enhanced expertise in a critical and rapidly evolving scientific field.
- Development of highly sought-after skills in remote sensing data analysis.
- Ability to contribute meaningfully to climate change research and solutions.
- Increased proficiency with industry-standard geospatial software and tools.
- Improved career prospects in environmental agencies, research institutions, and NGOs.
Organizational benefits
- Enhanced capacity for monitoring and assessing climate change impacts.
- Improved data-driven decision-making for climate adaptation and mitigation.
- More efficient and accurate environmental reporting and compliance.
- Better understanding of climate-related risks and vulnerabilities.
- Increased ability to develop and implement effective climate policies.
Training methodology
- Interactive lectures and theoretical discussions
- Extensive hands-on practical sessions and computer labs
- Case studies and real-world applications
- Group exercises and collaborative problem-solving
- Demonstrations of advanced remote sensing software and platforms
Trainer Experience
Our trainers are leading experts in remote sensing and climate science, with extensive academic and practical experience in monitoring climate change using satellite data. They possess deep knowledge of various remote sensing platforms, data processing workflows, and advanced analytical techniques. Our instructors are actively involved in climate research projects and have a proven track record of delivering high-quality, engaging training that bridges the gap between theory and practical application. They are committed to fostering a dynamic learning environment and sharing their real-world insights.
Quality Statement
We are dedicated to providing an unparalleled training experience in remote sensing for climate change monitoring. Our curriculum is meticulously designed, regularly updated with the latest scientific advancements and technological innovations, and delivered by world-class instructors. We are committed to equipping participants with the most relevant and actionable skills, ensuring they leave with the confidence and capability to make significant contributions to climate science and policy.
Tailor-made courses
We offer customized training programs to address the specific needs and objectives of your organization. Our team can work closely with you to adapt the course content, duration, and delivery format, ensuring a highly relevant and impactful learning experience that directly addresses your unique climate monitoring challenges.
Course Duration: 10 days
Training fee: USD 2500
Module 1: Fundamentals of Remote Sensing for Climate Change
- Introduction to climate change and its key indicators
- Basic principles of remote sensing: energy sources, atmospheric interactions
- Passive vs. active remote sensing systems
- Spectral signatures of Earth's features relevant to climate
- Overview of remote sensing applications in climate science
- Practical session: Exploring various remote sensing images and identifying spectral characteristics
Module 2: Electromagnetic Radiation and Sensor Systems
- Understanding the electromagnetic spectrum
- Radiometric, spatial, spectral, and temporal resolutions
- Types of sensors: optical, thermal, microwave
- Principles of image formation and data acquisition
- Sensor characteristics and their suitability for climate variables
- Practical session: Analyzing sensor specifications and their impact on data quality
Module 3: Satellite Missions for Climate Monitoring
- Overview of key Earth Observation satellites (e.g., Landsat, Sentinel, MODIS, NOAA, ICESat)
- Missions specifically designed for climate (e.g., GRACE, SMAP, GPM)
- Data availability, archives, and access portals
- International initiatives for climate monitoring from space
- Future satellite missions and their potential for climate science
- Practical session: Accessing and downloading climate-relevant data from satellite archives
Module 4: Remote Sensing Data Acquisition and Pre-processing
- Data formats for remote sensing (e.g., GeoTIFF, HDF, NetCDF)
- Radiometric calibration and atmospheric correction techniques
- Geometric correction and image registration
- Image enhancement and filtering methods
- Handling missing data and cloud cover
- Practical session: Performing radiometric and atmospheric corrections on satellite imagery
Module 5: Atmospheric Remote Sensing for Climate Variables
- Monitoring atmospheric temperature and humidity profiles
- Remote sensing of aerosols and clouds
- Measuring atmospheric composition (e.g., CO2, CH4, O3)
- Satellite-derived precipitation products
- Understanding atmospheric dynamics from space
- Practical session: Analyzing satellite data for atmospheric temperature and cloud cover
Module 6: Oceanic Remote Sensing for Climate Variables
- Sea surface temperature (SST) monitoring
- Ocean color and chlorophyll-a concentration
- Sea level rise monitoring using altimetry
- Ocean currents and eddies detection
- Sea ice extent and concentration
- Practical session: Extracting and visualizing sea surface temperature anomalies
Module 7: Terrestrial Remote Sensing for Climate Variables
- Land cover and land use change detection
- Vegetation indices (e.g., NDVI, EVI) for ecosystem health
- Drought monitoring and vegetation stress assessment
- Forest cover change and deforestation monitoring
- Soil moisture content estimation
- Practical session: Calculating and analyzing vegetation indices over time
Module 8: Cryospheric Remote Sensing for Climate Change
- Monitoring glacier and ice sheet dynamics
- Snow cover extent and depth mapping
- Permafrost degradation assessment
- Sea ice thickness and volume estimation
- Polar region climate change indicators
- Practical session: Mapping snow cover extent using satellite imagery
Module 9: Remote Sensing of the Carbon Cycle and Greenhouse Gases
- Estimating terrestrial carbon stocks and fluxes
- Monitoring changes in biomass and forest carbon
- Satellite-based measurements of CO2 and CH4 concentrations
- Urban greenhouse gas emissions mapping
- Role of remote sensing in carbon accounting and reporting
- Practical session: Visualizing global CO2 concentration data from satellite observations
Module 10: Remote Sensing for Extreme Weather Events and Disasters
- Monitoring floods and inundation mapping
- Wildfire detection and burn severity mapping
- Hurricane and cyclone tracking and intensity estimation
- Drought impact assessment and early warning systems
- Landslide and erosion monitoring
- Practical session: Delineating flood extent from post-disaster satellite imagery
Module 11: Geospatial Data Analysis and Interpretation for Climate Studies
- Spatial statistics for climate data analysis
- Change detection techniques (e.g., image differencing, PCA)
- Classification and segmentation of remote sensing images
- Regression analysis for climate variable estimation
- Uncertainty and error propagation in remote sensing products
- Practical session: Performing change detection analysis on land cover data
Module 12: Advanced Remote Sensing Platforms and Data Sources
- High-resolution commercial satellite imagery
- Drone-based remote sensing for localized climate studies
- Lidar data for 3D climate modeling (e.g., forest structure, urban heat islands)
- Synthetic Aperture Radar (SAR) for all-weather monitoring
- Integrating multi-sensor data for comprehensive analysis
- Practical session: Working with Lidar data for terrain analysis
Module 13: Time-Series Analysis of Remote Sensing Data
- Principles of time-series analysis for climate trends
- Detecting anomalies and breakpoints in long-term datasets
- Seasonal and inter-annual variability analysis
- Forecasting climate variables using historical remote sensing data
- Software and tools for time-series analysis (e.g., Google Earth Engine, R, Python)
- Practical session: Conducting time-series analysis on vegetation index data to identify trends
Module 14: Integration of Remote Sensing Data with Climate Models
- Understanding climate models and their components
- Assimilating remote sensing observations into climate models
- Validating model outputs with satellite data
- Downscaling climate model projections using remote sensing
- Bridging the gap between observations and simulations
- Practical session: Comparing satellite-derived data with climate model outputs
Module 15: Validation and Accuracy Assessment of Remote Sensing Products
- Importance of ground truth data for validation
- Statistical methods for accuracy assessment (e.g., confusion matrix, RMSE)
- Cross-validation and inter-comparison of satellite products
- Uncertainty quantification in remote sensing-derived climate variables
- Best practices for reporting accuracy and limitations
- Practical session: Performing an accuracy assessment of a land cover classification map
Module 16: Policy, Reporting, and Applications of Remote Sensing in Climate Action
- Role of remote sensing in national and international climate reporting (e.g., UNFCCC)
- Supporting climate adaptation and mitigation strategies
- Remote sensing for climate services and early warning systems
- Informing policy decisions with geospatial evidence
- Case studies of remote sensing applications in climate action
- Practical session: Developing a brief policy brief based on remote sensing findings
Module 17: Machine Learning and Artificial Intelligence in Remote Sensing for Climate
- Introduction to machine learning concepts for geospatial data
- Supervised and unsupervised classification for climate variables
- Deep learning for image segmentation and feature extraction
- Predictive modeling of climate impacts using AI
- Cloud-based AI platforms for large-scale remote sensing analysis
- Practical session: Applying a machine learning algorithm for land cover classification
Module 18: Future Directions in Remote Sensing for Climate Change Monitoring
- New sensor technologies and satellite constellations
- Advances in data processing and cloud computing for climate data
- Integration of remote sensing with other data sources (e.g., IoT, social media)
- Citizen science and crowdsourcing for climate monitoring
- Ethical considerations and challenges in future remote sensing applications
- Practical session: Discussing and brainstorming future remote sensing applications for climate challenges
Requirements:
· Participants should be reasonably proficient in English.
· Applicants must live up to Armstrong Global Institute admission criteria.
Terms and Conditions
1. Discounts: Organizations sponsoring Four Participants will have the 5th attend Free
2. What is catered for by the Course Fees: Fees cater for all requirements for the training – Learning materials, Lunches, Teas, Snacks and Certification. All participants will additionally cater for their travel and accommodation expenses, visa application, insurance, and other personal expenses.
3. Certificate Awarded: Participants are awarded Certificates of Participation at the end of the training.
4. The program content shown here is for guidance purposes only. Our continuous course improvement process may lead to changes in topics and course structure.
5. Approval of Course: Our Programs are NITA Approved. Participating organizations can therefore claim reimbursement on fees paid in accordance with NITA Rules.
Booking for Training
Simply send an email to the Training Officer on training@armstrongglobalinstitute.com and we will send you a registration form. We advise you to book early to avoid missing a seat to this training.
Or call us on +254720272325 / +254725012095 / +254724452588
Payment Options
We provide 3 payment options, choose one for your convenience, and kindly make payments at least 5 days before the Training start date to reserve your seat:
1. Groups of 5 People and Above – Cheque Payments to: Armstrong Global Training & Development Center Limited should be paid in advance, 5 days to the training.
2. Invoice: We can send a bill directly to you or your company.
3. Deposit directly into Bank Account (Account details provided upon request)
Cancellation Policy
1. Payment for all courses includes a registration fee, which is non-refundable, and equals 15% of the total sum of the course fee.
2. Participants may cancel attendance 14 days or more prior to the training commencement date.
3. No refunds will be made 14 days or less before the training commencement date. However, participants who are unable to attend may opt to attend a similar training course at a later date or send a substitute participant provided the participation criteria have been met.
Tailor Made Courses
This training course can also be customized for your institution upon request for a minimum of 5 participants. You can have it conducted at our Training Centre or at a convenient location. For further inquiries, please contact us on Tel: +254720272325 / +254725012095 / +254724452588 or Email training@armstrongglobalinstitute.com
Accommodation and Airport Transfer
Accommodation and Airport Transfer is arranged upon request and at extra cost. For reservations contact the Training Officer on Email: training@armstrongglobalinstitute.com or on Tel: +254720272325 / +254725012095 / +254724452588
