The program aims to empower participants with the technical autonomy to monitor land resources at scale. Upon completion, participants will be able to:

• Navigate the GEE Ecosystem: Master the Code Editor interface, asset management, and the basics of JavaScript for geospatial data manipulation.
• Handle Big Earth Data: Efficiently query, filter, and mosaic multi-petabyte datasets without downloading local files.
• Implement Machine Learning Workflows: Select, train, and deploy supervised classifiers—such as Random Forest (RF) and Support Vector Machines (SVM)—for land cover mapping.
• Optimize Feature Engineering: Generate and integrate spectral indices (e.g., NDVI, EVI) and topographic data (DEM) to improve classification accuracy.
• Execute Rigorous Validation: Perform statistical accuracy assessments using Confusion Matrices, Kappa Coefficients, and Producer/User accuracy metrics.
• Operationalize Results: Export high-resolution thematic maps and tabular statistics for use in national environmental reports and policy briefs.

The course follows a "Code-Along" pedagogical model, emphasizing tactile learning through real-time script development.

• Hands-on Lab Sessions: The core of the course. Each theoretical concept is immediately followed by a guided practical exercise in the GEE Code Editor.
• Interactive Technical Briefings: Short, high-impact presentations on the logic of machine learning and the physics of spectral bands.
• Problem-Based Learning: Participants work in small "Sprints" to debug code and solve common classification challenges, such as class imbalance or spectral overlap.
• Clinics & Peer Review: Daily "Script Clinics" where instructors provide one-on-one troubleshooting for participants' specific regional datasets.
• Visual Demonstration: Live walkthroughs of complex workflows, from data ingestion to the final export of a GeoTIFF.

•National and sub- national environmental agencies
•Scientists, researchers, and analysts
•Meteorological and hydrological department staff
•Urban planners and environmental engineers
•Academics andstudents
•Development professionals and practitioners

$1,550 (without accommodation)
$2,036 [with accommodation (6 nights)]

Fees are inclusive of course materials (soft copy), cost of instructions and course certificate. For face-to-face training, fee is inclusive of morning and afternoon snacks and lunch during the course.

Interested individuals and organizations can register online at www.adpc.net/apply.

For more information about the course, you may also contact ApibarlBunchongraksa at apibarl@adpc.net and telephone numbers +66 22980681 to 92 ext. 132.