Satellite Imagery, Remote Sensing & Machine Learning
About this course
Transform raw satellite data into actionable environmental insights with this 8-course program bridging traditional remote sensing with cutting-edge machine learning. Start by learning fundamentals: understanding how satellites measure Earth, calculating vegetation indices, & working with LiDAR 3D point clouds. Progress to advanced techniques of spatial statistics, SAR processing for disaster response, & climate data analysis. Dive into machine learning with hands-on training in CNNs for land cover classification, transfer learning, & model interpretability using Grad-CAM. Master Google Earth Engine for large-scale environmental monitoring without complex infrastructure. Through practical projects, analyze forest health, detect flood extent, evaluate air quality, & track vegetation trends. Each course emphasizes real-world application, from creating elevation models to generating climate reports for ESG initiatives. Learn to handle diverse data types—multispectral, SAR, LiDAR, & climate datasets—while building confidence in analysis & communication. Whether monitoring deforestation, assessing disasters, or tracking climate indicators, gain skills essential for environmental consulting & sustainability reporting. Perfect for GIS professionals, environmental analysts, & data scientists entering Earth observation. By completion, you'll confidently process satellite imagery, apply machine learning to environmental challenges, & deliver insights supporting critical decisions.
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What you'll learn
- understanding satellite data measurement
- calculating vegetation indices
- working with LiDAR 3D point clouds
- applying spatial statistics
- performing SAR processing for disaster response
- conducting climate data analysis
- using machine learning for land cover classification
- applying transfer learning
- interpreting models with Grad-CAM
- mastering Google Earth Engine for environmental monitoring
Course objectives
- transform raw satellite data into actionable insights
- analyze various types of environmental data
- develop confidence in environmental analysis and communication
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