Add new sunglint masking notebook for Sentinel-2 water applications

This PR adds a new How_to_guide notebook that demonstrates how to mask out sunglint from Sentinel-2 imagery using DEA sun and satellite view angle metadata. Based on the method in this Medium article: https://towardsdatascience.com/how-to-implement-sunglint-detection-for-sentinel-2-images-in-python-using-metadata-info-155e683d50

This is likely to be useful for any Sentinel-2 applications that focus on large waterbodies, e.g. oceans or lakes.

Before:

After:

[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
[ ] 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)
[ ] 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

GeoscienceAustralia / dea-notebooks