This is a development repository for the NEON Data Skills portal. Here the NEON Data Skills team develops and builds new content. Content is transferred to the NEONScience/NEON-Data-Skills repository to be published.

This directory will contain all the code related to the Remote Sensing Python lessons originally created for Data Institute 2017.

*images/Remote-Sensing-Python/...: each series/lesson will have a subdirectory with the same naming/file path as in the _posts directory. This allows for organized and automated creation of files and embedding the images in the files.

• code/Remote-Sensing-Python/...: this directory (same file paths inside) will contain any code that should be downloadable with the lesson via the "Download code" button at the bottom of each tutorial page.

The Day 1 Lesson (Jupyter Notebooks) were designed in the following order:

1. intro_neon_aop_hyperspectral_python.ipynb
2. hdf5_hyperspectral_functions.ipynb
3. plot_spectral_signatures.ipynb
4. calculate_ndvi_extract_spectra_with_masks.ipynb

Data, once uploaded should be stored under the Remote-Sensing-Python folder, or the paths to access data will need to be modified in the notebook scripts. I am still updating and adding functions to the neon_aop.py module that is loaded at the start of lessons 2-4, but all functions required to run the notebooks should already be uploaded.