Learn the Fundamentals
Dive into core concepts: radiance vs reflectance, STAC, atmospheric correction, and use cases.
Explore →Spectral Index Library
Browse standardized indices with formulas, wavelength constraints, and usage guidance.
Explore →Data Product Guide
Find out more about image specifications, products, and releases
Explore →Tutorials and Code
Step-by-step workflows for working with Wyvern data in GIS and common programming languages
Explore →Open Data
Explore over 100 freely available high-resolution hyperspectral images
Explore →Spectral Index Library
Search and compare relevant indices across applications that are directly applicable to Wyvern's satellites and sensors. Indices currently cover chlorophyll, stress, water, algae, and more.
Browse Index Library →(NIR - Red) / (NIR + Red)Vegetation vigor & chlorophyll proxy. High correlation with biomass under many conditions.
Preview standardized formatting & metadata for each index.
Code & Technical Resources
Use our Python helpers to load hyperspectral cubes, compute indices, perform reflectance conversion, run dimensionality reduction, and visualize spectra interactively.
- L1B to L1C Conversion
- Relative Spectral Response curves
- Image ingestion and processing
- Index computation and visualization
Tutorials & Notebooks
Hands-on tutorials and guides covering everying you need to know to work with Wyvern data, across all common GIS platforms and programming languages.
Loading Wyvern Data
How to visualize and load imagery using Python and common GIS libraries
Open →Visualizing Spectra
Use QGIS and EnMAP Box to select and visualize hyperspectral curves
Open →ENVI Wyvern Manual
Explore a wide variety of algorithms and applications using ENVI to analyze Wyvern data
Open →Loading Data in ArcGIS
Learn how to load Wyvern images into ArcGIS, and adjust visualization settings for optimal viewing.
Open →Contribute Indices and Examples
Help expand the spectral index library, improve tutorials, or add dataset adapters. We welcome all contributions!
Join the Community
Share discoveries, propose new indices, and collaborate on open and accessible hyperspectral imaging from space.