Author: ORNL DAAC Date: August 14, 2022 Contact for the ORNL DAAC: uso@daac.ornl.gov
Keywords: ORNL DAAC, AVIRIS-NG, ABoVE, Python
This tutorial demonstrates methods to read and perform a Principal Components Analysis on a file of Surface Reflectance data from the AVIRIS-NG instrument. The AVIRIS-NG (Airborne Visible/Infrared Imaging Spectrometer-Next Generation) instrument provides continuous radiance measurements of surface reflectance. This approximates one step in a study of Wetland Vegetation Classification conducted by NASA's Arctic-Boreal Vulnerability Experiment (ABoVE) Science team. The study incorporated data from NASA airborne instruments, including the AVIRIS-NG instrument. The ABoVE study included applications associating spectral characteristics with land cover classification focused on water and wetland vegetation communities over the Peace-Athabasca Delta (PAD), Canada.
In this tutorial, we'll use python methods to:
- Read and explore a flight path of AVIRIS-NG Spectral Reflectance (L2) data
- Create Spectral Profiles of the AVIRIS-NG data
- Export georeferenced multiband geoTIFF files
- Run a Principal Components Analysis (PCA) on an AVIRIS-NG Spectral Reflectance file
Jupyter Notebook: ESA2022_ABoVE_AVIRIS-NG_Notebook.ipynb
More tutorials related to ORNL DAAC data and web services can be found at the ORNL DAAC Learning page.