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Awesome Hyperspectral

Awesome Hyperspectral Awesome

A curated collection of awesome projects, papers, and tools for hyperspectral imagery

Some more awesome GIS/Machine Learning/Hyperspectral lists to take a look at:

Contents

Software

Software, libraries, and code related to building awesome stuff with hyperspectral imagery!

Software

Standalone applications or plugins for applications.

  • QGIS - A free and open source geographic information system capable of processing hyperspectral imagery.
  • EnMAP-Box - Python plugin for QGIS designed to process and visualize hyperspectral remote sensing data.
  • AVHYAS - A free & open source QGIS plugin for advanced hyperspectral image analysis
  • Google Earth Engine - Cloud computing platform for geospatial data processing and analysis (can also process hyperspectral data!).
  • Planetary Computer - Multi-petabyte catalog of geospatial data combined with cloud processing tools in Python and R.

Libraries

Libraries for software development in various programming languages.

Python

  • rasterio - GDAL-based Python library capable of reading hyperspectral data cubes.
  • Xarray - Xarray makes working with labelled multi-dimensional arrays in Python simple, efficient, and fun!
  • Xarray-spatial - Omplements common raster analysis functions using Numba and provides an easy-to-install, easy-to-extend codebase for raster analysis.
  • Spectral Python (SPY) - Pure Python module for processing hyperspectral image data.
  • PySptools - Tools for hyperspectral imaging
  • rastervision - An open-source library for geospatial machine learning projects. Many deep learning models are capable of using hyperspectral imagery.
  • torchgeo - An open-source library for training machine learning models using PyTorch on geospatial data.
  • EarthPy - A Python package that makes it easier to plot and work with spatial raster and vector data using open source tools.
  • spyndex - Allows use of awesome-spectral-indices formulae in Python.

R

  • hsdar - Manage, analyse, and simulate hyperspectral data.

Papers

Spectral Indices

  • Optical Remote Sensing Indexes of Soil Moisture: Evaluation and Improvement Based on Aircraft Experiment Observations (2021), Sun et al. [PDF]
  • Red edge spectral measurements from sugar maple leaves (1993), Vogelmann, Jim & Rock, Barrett & Moss, D.M.. [PDF]
  • Comparative analysis of hyperspectral vegetation indices for remote estimation of leaf chlorophyll content and plant status (2019), Velichkova, Kalinka & Krezhova, Dora. [PDF]

Machine Learning

  • A survey: Deep learning for hyperspectral image classification with few labeled samples (2021), Jia et al. [PDF]
  • Machine learning based hyperspectral image analysis: A survey (2019), Gewali et al. [PDF]
  • Hyperspectral Image Classification using Machine Learning Approaches (2020), Dasi et al. [HTML]
  • Hyperspectral Image Classification and Dimensionality Reduction: An Orthogonal Subspace Projection Approach (1994), Harsanyi et al. [PDF]
  • Dimensionality reduction of hyperspectral images of vegetation and crops based on self-organized maps (2019), Hidalgo et al. [HTML]

Data Sources

Imagery

  • AVIRIS - Airbone Visible/Infrared Imaging Spectrometer by NASA, in servce since the early 2000s
  • PRISMA - Medium-resolution (30m) hyperspectral satellite launched in 2019 by the Italian Space Agency
  • EnMAP - Medium-resolution (30m) hyperspectral satellite launched in 2022 by the Earth Observation Center of the German Aerospace Center
  • Wyvern - Canadian space company developing high-resolution hyperspectral satellites with deployable optics.
  • Pixxel - Space data company building a constellation of hyperspectral satellites.
  • Orbital Sidekick - Persistent monitoring service with constellation of hyperspectral satellites
  • Planet - Mature space data company developing a constellation of 30m GSD hyperspectral satellites

Hyperspectral Signatures

  • USGS Spectral Library - Thousands of materials compiled into an easy to search & download library.
  • Urban Surfaces Spectral Library - Library of spectral signatures focused on urban materials. Developed by the University of Reading's London Urban Meteorological Observitory.
  • ECOSTRESS Spectral Library - Library containing over 3400 natural and man made material spectra, and includes data from three other spectral libraries (Johns Hopkins, JPL, and USGS).

Resources

Additional sources for information related to hyperspectral data processing

  • Wyvern Knowledge Base - The go-to guide for all things hyperspectral! Now with sample data!
  • L3Harris Documentation - L3Harris' software is paid and closed source, however their documentation provides an excellent source of indices and tutorials for processing hyperspectral imagery.

Contribute

Contributions welcome! Read the contribution guidelines first.