Introduction to the Python Hyperspectral Analysis Tool (PyHAT)
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Abstract
Spectroscopic data are rich in information and are commonly used in planetary research. Many mission teams, research labs, and individual research scientists derive thematic products from multi- and hyperspectral data sets and apply spectroscopic analysis techniques to derive new understanding. The PyHAT is a powerful and versatile, free, and open-source Python library designed to support exploratory spectral data analysis, the derivation of mission generated thematic products, and the application of statistical learning methods to spectral data. We present a general overview of the software architecture and identify the classes of users we seek to support. Four case studies demonstrate the use for both orbital and in-situ (landed) hyperspectral data.
| Publication type | Book chapter |
|---|---|
| Publication Subtype | Book Chapter |
| Title | Introduction to the Python Hyperspectral Analysis Tool (PyHAT) |
| Chapter | 4 |
| DOI | 10.1016/B978-0-12-818721-0.00012-4 |
| Year Published | 2022 |
| Language | English |
| Publisher | Elsevier |
| Contributing office(s) | Astrogeology Science Center, Western Geographic Science Center |
| Description | 36 p. |
| Larger Work Type | Book |
| Larger Work Subtype | Monograph |
| Larger Work Title | Machine Learning for Planetary Science |
| First page | 55 |
| Last page | 90 |
| Google Analytic Metrics | Metrics page |