Lectures
The physics of EO, sensor types (Active vs. Passive), and the Four Resolutions.
Comparing platform capabilities: resolution, swath, cost, and revisit time.
📚 Required Readings
Electromagnetic spectrum, sensors, and satellite platforms.
📖 RS eBook - Chapter 2Contiguous spectral bands, spectral libraries, and applications.
📖 RS eBook - Chapter 4📝 Key Concepts for the Exam
The size of the area on the ground represented by a single pixel (e.g., 30m for Landsat, 10m for Sentinel-2).
The number and width of spectral bands. Multispectral (3-15 broad bands) vs. Hyperspectral (100s of narrow bands).
Revisit time—how often a satellite records the same location (e.g., 16 days for Landsat, 5 days for Sentinel-2 constellation).
The "Bit Depth"—how sensitive the sensor is to small differences in electromagnetic energy (e.g., 8-bit = 256 levels, 12-bit = 4096 levels).
Detects natural energy (sunlight) reflected or emitted from the Earth. Cannot see through clouds or at night.
Provides its own source of energy (like a flash). SAR (Capella, ICEYE) can see through clouds and at night.
- Satellite: Massive coverage (large swath), lower cost per km², but limited by orbital physics and clouds.
- Drone (UAV): Ultra-high resolution (cm-level), deployable under cloud cover, but limited swath and high operational cost.
- The Trade-off: "The closer you are, the better the resolution, but the smaller the footprint."
- NDVI = (NIR - Red) / (NIR + Red): Vegetation health.
- NDWI = (Green - NIR) / (Green + NIR): Water body detection.
- NDBI = (SWIR - NIR) / (SWIR + NIR): Urban/built-up mapping.
- NBR = (NIR - SWIR2) / (NIR + SWIR2): Burn severity.
Assessment
Focus on resolution trade-offs and sensor selection for disaster scenarios.
Assessed