8 docs tagged with "Easy"

AVIRIS / AVIRIS-NG

It's easy to get started in geospatial & hyperspectral processing due to the abundance of free and open source tools available! This is a short list on some of the most common tools available, however the geospatial community is filled with excellent packages and tools for you to explore.

Before we dive head first into hyperspectral imagery, it's best to understand some of the fundamentals of geospatial processing. Wyvern's satellites produce raster imagery, which can then be used by geospatial analysts & tools like QGIS and Python to extract value from the data.

Hyperspectral imaging is a relatively new technology to be commercialized. It is a type of imaging that has

Hyperspectral imagery is similar to most other forms of geospatial imagery, commonly called rasters. The main difference between images generated by satellites like Landsat & Sentinel, and hyperspectral imagery is the number of bands within an image. The below table shows common sources of imagery and their bands. You can see our satellites will have a ton more bands than common multi-spectral satellites. Take note, this also means larger file sizes!

Every material and compound reflects light differently based on it's chemical composition. Many organizations have collected, cataloged, and published these reflectance spectra for use in analysis and detection.

Background

We leverage the SpatioTemporal Asset Catalog (STAC) format to make our geospatial data more accessible, interoperable, and easier to discover.