The AIS Explorer template provides a graphical exploratory interface for automatic identification system (AIS) data.
For any given MMSI, the AIS Explorer shows the vessel's location over selected dates. You can represent location using latitude and longitude, or through H3. You can adjust the H3 resolution to show more or less detail.
To deploy this template on Tinybird, click the following button:
Then clone or fork this repository and deploy the data project to Tinybird.
- Use noaa_uploader.sh to append as many of the zipped CSV files as you need to Tinybird for sample data.
- Run app.py to have a local app to explore some of the shipping data. The default values should work.
To work on this project in your local environment, follow these steps:
- Clone this repository.
- Create a Python virtual env using
python -m venv .venv && source ./.venv/bin/activate. - Install the Python dependencies by running
pip install -r requirements.txt. - Open or create a Tinybird Workspace.
- Open the Tinybird Auth Token page and copy the User Admin Token.
- Run
tb authin the repo directory and paste the token. - Run
tb pushto establish the backend processing structure and serve the data APIs. - Use
noaa_uploader.shto append as many of the zipped CSV files as you need to Tinybird for sample data. Jan-May is about 1b rows. You might needjqinstalled:sudo apt-get update && sudo apt-get install jq -y --no-install-recommendsorbrew install jqfor macOS. - Run
app.pyto have a local app to explore some of the shipping data. The default values should work.
You can also stream in live AIS data following the same format.
AIS Explorer uses Dash and Plotly for the map, Pandas for the frontend data processing, and Tinybird for the backend.
The dataset comes from NOAA. It contains a few billion vessel observation samples from 2020.
Warning
NOAA provides this data for free, so don't abuse their download server.
Created by @Chaffelson, @juliavallina, @sdairs, and @rbarbadillo.