Computing WO from S2 ARD

Yukienip commented 3 months ago

Proposed changes

New notebook to demonstrate applying WO classifier to S2 imagery. Provides options for x-y input and custom bounding box. Chosen area for demonstration is affected by cloud masking error, and solutions are explored in the following notebook (Name TBC, currently Incorporating_Fmask_ARD)

Closes issues (optional)

Closes Issue #000

Checklist

(Replace [ ] with [x] to check off)

[ x] Notebook created using the DEA-notebooks template
[ x] Remove any unused Python packages from Load packages
[x ] Remove any unused/empty code cells
[x ] Remove any guidance cells (e.g. General advice)
[x ] Ensure that all code cells follow the PEP8 standard for code. The jupyterlab_code_formatter tool can be used to format code cells to a consistent style: select each code cell, then click Edit and then one of the Apply X Formatter options (YAPF or Black are recommended).
[ x] Include relevant tags in the final notebook cell (refer to the DEA Tags Index, and re-use tags if possible)
[ x] Clear all outputs, run notebook from start to finish, and save the notebook in the state where all cells have been sequentially evaluated
[sandbox only ] Test notebook on both the NCI and DEA Sandbox (flag if not working as part of PR and ask for help to solve if needed)
[ x] If applicable, update the Notebook currently compatible with the NCI|DEA Sandbox environment only line below the notebook title to reflect the environments the notebook is compatible with
[x ] Check for any spelling mistakes using the DEA Sandbox's built-in spellchecker (double click on markdown cells then right-click on pink highlighted words). For example:

sandbox_spellchecker

review-notebook-app[bot] commented 3 months ago

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BexDunn commented 2 months ago

Hey @Yukienip do you have more files in here than the ones you have updated? you may want to look at doing this one from a fresh branch and pulling your updates on a fresh checkout of develop?

GeoscienceAustralia / dea-notebooks