📄️ Geospatial basics
Geospatial fundamentals for earth observation: the difference between vector and raster data, their common file formats, and how the two are combined when working with Wyvern hyperspectral imagery.
📄️ Hyperspectral basics
An introduction to hyperspectral imaging: the electromagnetic spectrum, how panchromatic, multispectral, and hyperspectral earth observation imagery differ, and what Wyvern's Dragonette satellites measure.
📄️ Hyperspectral image formats
Hyperspectral image formats explained: the data cube, and the raster formats you'll meet with hyperspectral imagery, including GeoTIFF and Cloud-Optimized GeoTIFF, ENVI, and HDF5 and NetCDF.
📄️ Processing levels
Earth observation processing levels (L0–L4) explained, plus the details of Wyvern's two delivered products: L1B top-of-atmosphere radiance and L2A surface reflectance, with their projections, units, data types, and NoData values.
📄️ Understanding the STAC format
Understand the SpatioTemporal Asset Catalog (STAC): items, catalogs, and collections, how Wyvern's Open Data catalog is organized with them, and tools like PySTAC and pystac-client for accessing it.
📄️ Hyperspectral signatures
How spectral signatures identify materials in hyperspectral imagery, why mixed pixels complicate that, and the main methods for handling them: endmember extraction, spectral unmixing, and spectral matching.
📄️ Common tools
The geospatial and hyperspectral software we use with Wyvern imagery (QGIS, ArcGIS, ENVI, Python, R, and GDAL), what each is good for, and what it costs.
📄️ Atmospheric correction
The difference between L1B top-of-atmosphere radiance and L2A surface reflectance for Wyvern data, what Wyvern's L2A product corrects, and the tools to use if you are correcting L1B yourself.