Satellite Data Analysis: Processing SAR and Multispectral Imagery

Satellite imagery is more than just beautiful pictures; it is a rich source of quantitative geospatial data waiting to be unlocked. To make informed decisions in environmental monitoring, agriculture, or urban planning, you must know how to process both optical and radar datasets. This course guides you from a passive viewer of satellite maps to an active analyst capable of manipulating raw spatial data. What you'll learn: - Understand the fundamental physics behind Synthetic Aperture Radar (SAR) and multispectral sensors. - Process raw optical bands to calculate vegetation indices and monitor land cover changes. - Perform SAR data preprocessing, including backscatter calibration, speckle filtering, and terrain correction. - Apply modern Python libraries like rasterio and rioxarray to programmatically manipulate spatial rasters. - Work with Cloud-Optimized GeoTIFFs (COGs) for efficient, modern data access. - Analyze real-world environmental changes through structured, text-based guided walkthroughs. You will begin with core concepts of remote sensing and electromagnetic radiation before moving on to practical, step-by-step processing workflows. Each module reinforces your understanding through written explanations, conceptual exercises, and code-based analysis. This course is designed for beginners in GIS, environmental science, or data analytics, and requires no prior experience with satellite processing. Start your journey into satellite data analysis and unlock the power of Earth observation data today.