TY - JOUR
T1 - HyPyRameter
T2 - A Python Toolbox to Calculate Spectral Parameters from Hyperspectral Reflectance Data
AU - Phillips, Michael S.
AU - Tai Udovicic, Christian
AU - Moersch, Jeffrey E.
AU - Basu, Udit
AU - Hamilton, Christopher W.
N1 - Publisher Copyright:
© 2024. The Author(s). Published by the American Astronomical Society.
PY - 2024/11/1
Y1 - 2024/11/1
N2 - Hyperspectral image cubes are information rich, typically containing hundreds of wavelengths and millions of spatial pixels. To condense this information into a more interpretable form, it is common to parameterize certain aspects of the spectra that are known to represent compositions of interest. Parameterizations of spectral features are called spectral parameters. Spectral parameters can be combined thematically into red, green, and blue (RGB) images, called browse products, to visualize compositional variation across a surface. Here, we present the Hyperspectral Parameter (HyPyRameter) toolbox: an open-source library, written in Python, to calculate spectral parameters for hyperspectral reflectance data. With the HyPyRameter toolbox, a user can calculate spectral parameters from point spectra or hyperspectral image cubes. Users can take advantage of the native parameters built into the HyPyRameter library, or easily customize the library of parameter formulas with built-in functions to suit the needs of a specific investigation. HyPyRameter can be run with Jupyter notebooks provided on the GitHub repo (https://github.com/Michael-S-Phillips/HyPyRameter). HyPyRameter is a flexible tool, installable via Anaconda (https://anaconda.org/michael-s-phillips/hypyrameter), with potential for wide-ranging applications to diverse fields including, but not limited to, planetary science, geology, agriculture, and mineral resource exploration.
AB - Hyperspectral image cubes are information rich, typically containing hundreds of wavelengths and millions of spatial pixels. To condense this information into a more interpretable form, it is common to parameterize certain aspects of the spectra that are known to represent compositions of interest. Parameterizations of spectral features are called spectral parameters. Spectral parameters can be combined thematically into red, green, and blue (RGB) images, called browse products, to visualize compositional variation across a surface. Here, we present the Hyperspectral Parameter (HyPyRameter) toolbox: an open-source library, written in Python, to calculate spectral parameters for hyperspectral reflectance data. With the HyPyRameter toolbox, a user can calculate spectral parameters from point spectra or hyperspectral image cubes. Users can take advantage of the native parameters built into the HyPyRameter library, or easily customize the library of parameter formulas with built-in functions to suit the needs of a specific investigation. HyPyRameter can be run with Jupyter notebooks provided on the GitHub repo (https://github.com/Michael-S-Phillips/HyPyRameter). HyPyRameter is a flexible tool, installable via Anaconda (https://anaconda.org/michael-s-phillips/hypyrameter), with potential for wide-ranging applications to diverse fields including, but not limited to, planetary science, geology, agriculture, and mineral resource exploration.
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U2 - 10.3847/PSJ/ad81f8
DO - 10.3847/PSJ/ad81f8
M3 - Article
AN - SCOPUS:85213322761
SN - 2632-3338
VL - 5
JO - Planetary Science Journal
JF - Planetary Science Journal
IS - 11
M1 - 258
ER -