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https://github.com/opengeos/HyperCoast
A Python package for visualizing and analyzing hyperspectral data in coastal regions
https://github.com/opengeos/HyperCoast
coastal geospatial hyperspectral nasa python
Last synced: 3 months ago
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A Python package for visualizing and analyzing hyperspectral data in coastal regions
- Host: GitHub
- URL: https://github.com/opengeos/HyperCoast
- Owner: opengeos
- License: mit
- Created: 2024-04-08T16:01:06.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2024-05-19T04:04:21.000Z (6 months ago)
- Last Synced: 2024-05-23T00:30:18.005Z (6 months ago)
- Topics: coastal, geospatial, hyperspectral, nasa, python
- Language: Python
- Homepage: https://hypercoast.org
- Size: 2.68 MB
- Stars: 31
- Watchers: 4
- Forks: 1
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- Contributing: docs/contributing.md
- License: LICENSE
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README
# HyperCoast
[](https://colab.research.google.com/github/opengeos/HyperCoast/blob/main)
[](https://pypi.python.org/pypi/HyperCoast)
[](https://pepy.tech/project/hypercoast)
[](https://anaconda.org/conda-forge/hypercoast)
[](https://github.com/conda-forge/hypercoast-feedstock)
[](https://anaconda.org/conda-forge/hypercoast)
**A Python Package for Visualizing and Analyzing Hyperspectral Data in Coastal Environments**
- Free software: MIT License
- Documentation:
## Introduction
HyperCoast is a Python package designed to provide an accessible and comprehensive set of tools for visualizing and analyzing hyperspectral data in coastal environments. Hyperspectral data refers to the information collected by sensors that capture light across a wide range of wavelengths, beyond what the human eye can see. This data allows scientists to detect and analyze various materials and conditions on the Earth's surface with great detail. Unlike multispectral data, which captures light in a limited number of broad wavelength bands (typically 3 to 10), hyperspectral data captures light in many narrow, contiguous wavelength bands, often numbering in the hundreds. This provides much more detailed spectral information. Leveraging the capabilities of popular packages like [Leafmap](https://leafmap.org) and [PyVista](https://pyvista.org), HyperCoast streamlines the exploration and interpretation of complex hyperspectral remote sensing data from existing spaceborne and airborne missions. It is also poised to support future hyperspectral missions, such as NASA's SBG and GLIMR. It enables researchers and environmental managers to gain deeper insights into the dynamic processes occurring in aquatic environments.
HyperCoast supports the reading and visualization of hyperspectral data from various missions, including [AVIRIS](https://aviris.jpl.nasa.gov), [NEON](https://data.neonscience.org/data-products/DP3.30006.001), [PACE](https://pace.gsfc.nasa.gov), [EMIT](https://earth.jpl.nasa.gov/emit), and [DESIS](https://www.earthdata.nasa.gov/s3fs-public/imported/DESIS_TCloud_Mar0421.pdf), along with other datasets like [ECOSTRESS](https://ecostress.jpl.nasa.gov). Users can interactively explore hyperspectral data, extract spectral signatures, change band combinations and colormaps, visualize data in 3D, and perform interactive slicing and thresholding operations (see Figure 1). Additionally, by leveraging the [earthaccess](https://github.com/nsidc/earthaccess) package, HyperCoast provides tools for interactively searching NASA's hyperspectral data. This makes HyperCoast a versatile and powerful tool for working with hyperspectral data globally, with a particular focus on coastal regions.
**Figure 1.** An example of visualizing NASA EMIT hyperspectral data using HyperCoast.
## Features
- Searching for NASA hyperspectral data interactively
- Performing atmospheric correction using [Acolite](https://github.com/acolite/acolite)
- Interactive visualization and analysis of hyperspectral data, such as [AVIRIS](https://aviris.jpl.nasa.gov), [DESIS](https://www.earthdata.nasa.gov/s3fs-public/imported/DESIS_TCloud_Mar0421.pdf), [EMIT](https://earth.jpl.nasa.gov/emit), [PACE](https://pace.gsfc.nasa.gov), [NEON AOP](https://data.neonscience.org/data-products/DP3.30006.001)
- Interactive visualization of NASA [ECOSTRESS](https://ecostress.jpl.nasa.gov) data
- Interactive visualization of [PACE](https://pace.gsfc.nasa.gov) chlorophyll-a data
- Interactive extraction and visualization of spectral signatures
- Changing band combinations and colormaps interactively
- Visualizing hyperspectral data in 3D
- Visualizing ERA5 temperature data in 3D
- Interactive slicing and thresholding of hyperspectral data in 3D
- Saving spectral signatures as CSV files
## Demos
- Visualizing hyperspectral data in 3D ([notebook](https://hypercoast.org/examples/image_cube))
- Interactive slicing of hyperspectral data in 3D ([notebook](https://hypercoast.org/examples/image_slicing))
- Interactive thresholding of hyperspectral data in 3D ([notebook](https://hypercoast.org/examples/image_slicing))
- Visualizing ERA5 temperature data in 3D ([notebook](https://hypercoast.org/examples/temperature))
- Changing band combinations and colormaps interactively ([notebook](https://hypercoast.org/examples/neon))
- Visualizing NASA [AVIRIS](https://aviris.jpl.nasa.gov) hyperspectral data interactively ([notebook](https://hypercoast.org/examples/aviris))
- Visualizing [DESIS](https://www.earthdata.nasa.gov/s3fs-public/imported/DESIS_TCloud_Mar0421.pdf) hyperspectral data interactively ([notebook](https://hypercoast.org/examples/desis))
- Visualizing NASA [EMIT](https://earth.jpl.nasa.gov/emit) hyperspectral data interactively ([notebook](https://hypercoast.org/examples/emit))
- Visualizing NASA [PACE](https://pace.gsfc.nasa.gov) hyperspectral data interactively ([notebook](https://hypercoast.org/examples/pace))
- Visualizing [NEON AOP](https://data.neonscience.org/data-products/DP3.30006.001) hyperspectral data interactively ([notebook](https://hypercoast.org/examples/neon))
- Interactive visualization of [PACE](https://pace.gsfc.nasa.gov) chlorophyll-a data ([notebook](https://hypercoast.org/examples/chlorophyll_a))
## Acknowledgement
The HyperCoast project draws inspiration from the [nasa/EMIT-Data-Resources](https://github.com/nasa/EMIT-Data-Resources) repository. Credits to the original authors. We also acknowledge the NASA EMIT program support through grant no. 80NSSC24K0865.
## License
HyperCoast is released under the MIT License. However, some of the modules in HyperCoast adapt code from other open-source projects, which may have different licenses. Please refer to the license notice in each module for more information. Credits to the original authors.
- [emit.py](https://github.com/opengeos/HyperCoast/blob/main/hypercoast/emit.py): Part of the code is adapted from the [nasa/EMIT-Data-Resources](https://github.com/nasa/EMIT-Data-Resources) repository, which is released under the Apache License 2.0.
- [aviris.py](https://github.com/opengeos/HyperCoast/blob/main/hypercoast/aviris.py): Part of the code is adapted from the [jjmcnelis/aviris-ng-notebooks](https://github.com/jjmcnelis/aviris-ng-notebooks), which is released under the MIT License.