Module 1: Introduction to Google Earth Engine (GEE)

• What is Google Earth Engine? Cloud computing for geospatial analysis
• Key Features and Advantages of GEE: Scale, data catalog, API
• The GEE Data Catalog: Overview of available datasets (satellite imagery, climate data, etc.)
• Setting Up Your GEE Account and Workspace: Accessing the Code Editor
• Understanding the GEE JavaScript API Structure
• Practical session: Navigating the GEE Code Editor, exploring the data catalog, and running your first simple script

Module 2: GEE User Interface and Data Exploration

• The GEE Code Editor Layout: Script editor, console, inspector, tasks
• Searching and Loading Image Collections: Landsat, Sentinel, MODIS
• Visualizing Image Data: Display parameters, true color, false color composites
• Working with Feature Collections: Loading vector data (shapefiles, Fusion Tables)
• Basic Map Operations: Centering, zooming, and adding layers
• Practical session: Loading and visualizing different satellite image collections and feature collections, adjusting visualization parameters.

Module 3: Working with Satellite Imagery in GEE

• Understanding Image Bands and Metadata: Reflectance values, acquisition dates
• Filtering Image Collections: By date, region, and cloud cover
• Reducing Image Collections: Mosaicking, median, mean, and other reducers
• Applying Functions to Images: Map and ee.Image.expression()
• Introduction to the ee.Image object and its properties
• Practical session: Filtering a Sentinel-2 image collection by date and location, then creating a cloud-free mosaic.

Module 4: Basic Image Processing and Visualization

• Band Math and Indices: NDVI, NDWI, EVI calculation
• Clipping Images to a Region of Interest: Using clip()
• Reprojection and Resampling Images: Aligning spatial resolutions
• Masking Pixels: Removing clouds, water bodies, or other unwanted features
• Exporting Images to Google Drive or Asset: Saving your results
• Practical session: Calculating NDVI for an area of interest, applying a mask to remove water, and exporting the resulting NDVI image.

Module 5: Time Series Analysis with GEE

• Creating Time Series Charts: Visualizing changes over time for a single pixel or region
• Calculating Temporal Statistics: Mean, min, max over time
• Detecting Change over Time: Difference images, change detection algorithms (e.g., CCDC, LandTrendr overview)
• Smoothing Time Series Data: Reducing noise for better trend identification
• Applications of Time Series Analysis: Deforestation monitoring, crop health assessment
• Practical session: Generating and analyzing NDVI time series charts for specific agricultural fields or forest areas.

Module 6: Vector Data Processing and Analysis

• Loading and Manipulating ee.FeatureCollection objects
• Filtering Feature Collections: By property, geometry, or intersection
• Geometric Operations: Buffering, union, intersection
• Zonal Statistics: Extracting pixel values under vector polygons (e.g., mean NDVI per administrative unit)
• Joining Data: Combining image and vector properties
• Practical session: Calculating mean NDVI for a set of administrative boundaries or protected areas using zonal statistics.

Module 7: Cloud Computing Concepts and GEE Scalability

• Understanding the Client-Server Model in GEE
• Lazy Evaluation: How GEE optimizes computations
• Distributed Computing and Parallel Processing: GEE's backend infrastructure
• Memory Management and Avoiding Common Errors: Debugging tips
• Scaling Your Analysis: Efficient scripting for large datasets
• Practical session: Modifying existing scripts to optimize performance and reduce computational load, debugging common errors.

Module 8: Introduction to Machine Learning in GEE

• Overview of Supervised vs. Unsupervised Classification
• Preparing Training Data: Collecting samples for classification
• Common Classifiers in GEE: Random Forest, Support Vector Machine (SVM)
• Performing Image Classification: Land cover mapping example
• Accuracy Assessment: Basic metrics (confusion matrix, overall accuracy)
• Practical session: Performing a simple land cover classification using a small training dataset and evaluating its accuracy.

Module 9: Exporting Results and Advanced Applications

• Exporting Images as GeoTIFFs: For use in other GIS software
• Exporting Feature Collections as Shapefiles/CSV: For vector data
• Exporting Charts and Tables: For data visualization and reporting
• GEE Assets: Managing and sharing your custom datasets
• Introduction to GEE for specific applications: Disaster response, water resources, urban growth
• Practical session: Exporting classified land cover maps and associated data tables to Google Drive.

Module 10: Building Interactive Applications with GEE

• Introduction to the GEE ui Module: Creating interactive widgets
• Building Simple User Interfaces: Buttons, sliders, text boxes
• Integrating UI Elements with GEE Scripts: Dynamic analysis
• Sharing GEE Applications: Public access and collaboration
• Case Studies of GEE Applications: Real-world examples of interactive tools
• Practical session: Building a simple interactive GEE application that allows users to select a date range and visualize NDVI for a selected area.

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