Mastering Geospatial Analysis in QGIS & Google Earth Engine for Environmental Applications

Categories: Python, QGIS
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About Course

Mastering Geospatial Analysis in QGIS & Google Earth Engine for Environmental Applications is an advanced, hands-on training program designed for environmental scientists, geologists, and GIS professionals. This course bridges the gap between desktop map-making and cloud-based environmental problem-solving. Participants will master advanced workflows in QGIS and leverage the massive computational power of Google Earth Engine to monitor environmental changes, model disaster risks, and analyze topographical features. Utilizing open-source Earth observation data (Sentinel, Landsat), students will learn to conduct rigorous spatial analyses, process heavy time-series datasets in the cloud, and finalize professional cartographic deliverables in QGIS.

 

🗓️ Classes Begin: 15.6.2026

🔗 Register Now: https://eomyanmar.org/registration-form/

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What Will You Learn?

  • Cloud Computing & Desktop GIS: Seamlessly integrate Google Earth Engine with QGIS to process massive datasets without local hardware limitations.
  • Terrain & Hydrological Modeling: Process Digital Elevation Models (DEMs) to delineate watersheds and extract cross-sectional topographic profiles.
  • River Morphology Analysis: Quantify long-term fluvial dynamics, mapping historical channel migration, erosion, and accretion rates.
  • Air Quality Monitoring: Track and visualize atmospheric pollutants and emission trends using Sentinel-5P satellite data.
  • Machine Learning for LULC: Train and validate Random Forest and SVM algorithms to automate Land Use/Land Cover classification.
  • Environmental Change Detection: Perform multi-temporal analysis using historical satellite imagery to identify, quantify, and map landscape transitions, urban expansion, and deforestation over time.

Course Content

Module 1: Foundations of Environmental GIS & Cloud Computing

Module 2: Terrain Analysis & Hydrological Modeling

Module 3: River Morphology Change Detection

Module 4: Air Quality Monitoring using Satellite Remote Sensing

Module 5: Machine Learning-Based Land Use and Land Cover Mapping and Change Detection

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Our mission is to deliver advanced research, training, and consulting in remote sensing and GIS for sustainable development and environmental monitoring.