Update Python hyperspectral tutorials to use a more up-to-date version of the hyperspectral functions

[bhass-neon]

The Python tutorials (many written for the 2017 and 2018 RSDIs) use different versions of functions for reading in reflectance h5 files, plotting, and so forth. Make these consistent, and make sure they work with latest version of Python, etc.

Can start with these python_modules, made for ESIIL 2023.

Intro Hyperspectral Tutorials

• [x] NEON AOP Hyperspectral Data in HDF5 format with Python (https://github.com/NEONScience/NEON-Data-Skills/blob/main/tutorials/Python/AOP/Hyperspectral/intro-hyperspectral/intro-refl-h5) - updated March 13, 2024
• [x] Read in and visualize hyperspectral data in Python (https://github.com/NEONScience/NEON-Data-Skills/tree/main/tutorials/Python/AOP/Hyperspectral/intro-hyperspectral/hyperspectral_functions)
• [x] Calculate NDVI & Extract Spectra Using Masks in Python (https://github.com/NEONScience/NEON-Data-Skills/tree/main/tutorials/Python/AOP/Hyperspectral/intro-hyperspectral/ndvi-spectra-masks)
• [x] Plot a Spectral Signature from Reflectance Data in Python (https://github.com/NEONScience/NEON-Data-Skills/tree/main/tutorials/Python/AOP/Hyperspectral/intro-hyperspectral/plot-spectral-signature)
• [x] Create Intro Tutorial Series (https://www.neonscience.org/resources/learning-hub/tutorials/introduction-hyperspectral-remote-sensing-data-python)
• [ ] Update all lessons above to download the file in the beginning. The download_url function currently used in the scripts is not ideal for large files!

Classification Tutorials

• [ ] Unsupervised Spectral Classification in Python: Endmember Extraction (https://github.com/NEONScience/NEON-Data-Skills/tree/main/tutorials/Python/AOP/Hyperspectral/classification/endmember-extraction)
• [ ] Unsupervised Spectral Classification in Python: KMeans & PCA (https://github.com/NEONScience/NEON-Data-Skills/tree/main/tutorials/Python/AOP/Hyperspectral/classification/kmeans-pca)

Uncertainty / Validation Tutorials

• [ ] Assessing Spectrometer Accuracy using Validation Tarps with Python (https://github.com/NEONScience/NEON-Data-Skills/tree/main/tutorials/Python/AOP/Hyperspectral/uncertainty-validation)
• [ ] Hyperspectral Variation Uncertainty Analysis in Python (https://github.com/NEONScience/NEON-Data-Skills/blob/main/tutorials/Python/AOP/Hyperspectral/uncertainty-validation/hyperspectral_variation_py)

[bhass-neon]

• [x] NEON AOP Hyperspectral Data in HDF5 format with Python - updated March 13, 2024
• [x] Read in and visualize hyperspectral data in Python - updated April 15, 2024
• [x] Calculate NDVI & Extract Spectra Using Masks in Python - updated April 15, 2024
• [x] Plot a Spectral Signature from Reflectance Data in Python - updated April 15, 2024

[bhass-neon]

• [x] Unsupervised Spectral Classification in Python: Endmember Extraction (https://github.com/NEONScience/NEON-Data-Skills/tree/main/tutorials/Python/AOP/Hyperspectral/classification/endmember-extraction) < looked into this and the pysptools package used (https://pypi.org/project/pysptools/) is no longer compatible with the latest version of Python, it only works for Python 3.5/3.6. Archiving this lesson, and will look into replacing with something more up to date.