ILIAD Hackathon, Aquaculture

Purpose

This repository contains various notebooks created during the 2024 ILIAD Hackathon. Our case focused on extraction of chlorophyll measurements from (a) ferryboxes, and (b) satellite imagery. See the notebooks in the folders ./ferrybox and ./satellites for details.

The notebooks also conveniently illustrate the tools available to work with remote THREDDS Data Servers through OPeNDAP using xarray, how to use MovingPandas to deal with trajectories, how to use PySTAC-Client to deal with STAC catalogues, and how to use Satpy to deal with diverse satellite data products with little pain.

Prerequisites

We do need an uncomfortably large collection of Python packages. Using Miniforge, you can get started as follows:

conda create --name iliad-hackathon python=3.12
conda activate iliad-hackathon
mamba install numpy ipython jupyterlab xarray pandas
mamba install tqdm
mamba install geopandas movingpandas holoviews geoviews 
mamba install satpy pystac pystac-client

This should pull in everything you need. Since Miniforge is pulling from conda-forge (where versions move fast), we chose not provide an environment.yml file. If you don't use Miniforge, you need to specifcy the conda-forge channel (i.e., conda install --channel conda-forge package1 packag2).

Usage, Ferrybox

In the ./ferrybox folder, you will find the following notebooks.

Notebook	Description
01_trajectories_with_data.ipynb	Load ferrybox data from the NIVA Thredds server, select some trajectories, load them into a Moving Pandas, and then visualize chlorophyll measurements along the trajectory.
02_heatmap_1D_singletrip.ipynb	Load ferrybox data from a single trip, extracts relevant data into a target grid of latitudes (along the Oslofjord), and then plots the spatial variation of chlorophyll with latitude.
03_heatmap_2D_manytrips.ipynb	As above, but loads multiple ferrybox trips and creates a timespace heatmap of how chlorophyll changes with latitude.

The first notebook generates a HTML file (./ferrybox/01_trajectories_with_data_sample.html) that contains only the interactive visualization of the trajectories. The HTML file looks like this:

The timespace heatmap from the third notebook (03_heatmap_2D_manytrips.ipynb) looks like this:

Usage, Satellite Data

In the ./satellites/ directory, you will find the following notebooks.

Notebook	Description
01_search_stac_on_cdse.ipynb	Explores the STAC endpoint of the Copernicus Dataspace (CDS) that allows you to query available satellite products for a given area of interest and time.
02_download_from_cdse.ipynb	Downloads the compressed Sentinel-3 OCLI Level 2 data from the Copernicus Data Space. Data is downloaded in the SAFE format.
03_unzip.sh	Unzip the archives you just downloaded.
04_inspect_product_coordinates.ipynb	Loads the coordinates coordinates of the downloaded product to find out whether we have a regular or irregular grid.
05_with_satpy_to_geotiff.ipynb	Uses Satpy to loads, reproject, plot, and export a GeoTiff of the CHL_NN product.

In addition to links to the full data products, the first notebook also gives links to download quicklook previews. For the target area and time, the quicklook image looks like this. This a bit of lucky break because the entire picture is covered by clouds except Northern Norway (which we are interested in right now). Usually, it is the other way around.

Finally, by dragging the GeoTiff from by the last notebook into QGIS , you can produce the following figure.

Contact

• Volker Hoffmann (volker.hoffmann@sintef.no)

Funding

This work was supported by EU Horizon 2020 and Horizon Europe Research and Innovation Programmes under Grant Agreement No 101037643 and 101094434 (projects ILIAD and AquaINFRA).