A Destination Earth Platform use case.
This repository is the official content repository for the Gloabl FishTracking Service (GFTS), a Destination Earth Platform Use Case procured by ESA.
The lack of accurate modelling of fish movement, migration strategies, and site fidelity is a major challenge for policy-makers when they need to formulate effective conservation policies. By relying on the Pangeo infrastructure on the DestinatE Platform, the Use Case aims to predict the sea bass behavior and develop a Decision Support Tool (DST) for “what-if” scenario planning. As a result, the Use Case will help to obtain accurate insights into fish populations by introducing the Global Fish Tracking System (GFTS) and a Decision Support Tool into the DestinE Platform.
Documentation can be viewed at https://destination-earth.github.io/DestinE_ESA_GFTS.
- Ensure you have Python 3.11 installed.
This project is compatible with macOS and Linux distributions with Python 3.11 installed.
To build this project, ensure you have Python 3 and all the necessary Python packages (see environmemt.yml) installed on your system.
To get a local copy of the GFTS repository, you can clone it on your local computer and/or server:
git clone https://github.com/destination-earth/DestinE_ESA_GFTS.gitThe sections below explain how to install and run DestinE_ESA_GFTS jupyter notebooks locally from source. We assume you have already cloned the github repository.
Jupyter notebooks to showcase GFTS are in the docs folder and can be run after installing Python and the required packages listed in the .binder/environment.yml file.
To install Python, we recommend to install conda or miniconda and then create a new conda environment using .binder/environment.yml:
conda env create -f environment.ymlDo not forget to switch to the gfts conda environment prior to executing any Jupyter notebooks or programs from the GFTS repository.
conda activate gftsTo deactivate the gfts environment:
conda deactivateThe section below explains how to start JupyerLab and run the Jupyter notebooks.
Once all the required packages are installed, you can start JupyterLab and execute the jupyter notebooks from the docs folder:
jupyter labBefore building the GFTS docker image, you would need to install docker.
Make sure you change directory to gfts-track-reconstruction/jupyterhub/images/user before executing the command below:
docker build -t gfts:latest .docker run -p 7777:8888 -i -t gfts:latest jupyter lab --ip=0.0.0.0 --no-browserOpen your web browser and enter the following command:
http://127.0.0.1:7777/labThen you need to enter your token: it can be found at the bottom of the printout you got after running the docker run command given above.
Instructions on how to build and deploy GFTS hub are described in ./gfts-track-reconstruction/jupyterhub/README.md.
The current Jupyterhub deployment is done on OVH cloud operator.
Contributions are always welcome!
Tho contribute to DestinE Open Source SW collections please refer to Rule of Participation
DestinE open source community abide to this Code of Conduct## Deployment of GFTS Hub on the cloud
Instructions on how to build and deploy GFTS hub are described in ./gfts-track-reconstruction/jupyterhub/README.md.
The current Jupyterhub deployment is done on OVH cloud operator.
If you have any feedback, please reach out to us by filling an issue.
For support, please create a Github issue.
This project is used by the following companies:
Python, Jupyter Notebooks.
Please refer to the whole course as described in the CITATION.cff file
The content of this repository is made available under the Apache 2.0 license; for more details, see the LICENSE file.
This project is funded by the European Space Agency through the Destination Earth Use Case initiative.
The project is currently work in progress