Flux-footprints

FluxFootprints is a fast, fully‑featured Python implementation of the Kljun et al. (2015) flux‑footprint parameterisation for eddy‑covariance research. It provides vectorised and xarray‑enabled utilities to compute per‑timestamp footprints, aggregate footprint climatologies, extract source‑area contours, and visualise results—scaling seamlessly from single towers to multi‑year datasets.

Table of Contents

1. Installation
2. Documentation
3. Quick‑start Example
4. Key Features
5. Input Requirements
6. Citing & Referencing
7. Contributing
8. Development Road‑map
9. License

Installation

# Stable release (PyPI)
pip install fluxfootprints

# Development version (GitHub)
pip install git+https://github.com/YourOrg/fluxfootprint.git

Minimum Python 3.10 Core dependencies: numpy, pandas, xarray, scipy, matplotlib. Optional: dask, rioxarray, pyproj for advanced geospatial export.

Documentation

Full API docs, tutorials, and example notebooks are hosted at Read the Docs:

https://fluxfootprints.readthedocs.io/en/latest/

To build locally:

pip install -r docs/requirements.txt
sphinx-build -M html docs/ docs/_build

Key Features

Input Requirements

Any additional columns are ignored unless you plug in custom routines.

Citing & Referencing

If you use Flux-Footprints in a publication, please cite the original parameterisation:

Kljun, N., Calanca, P., Rotach, M.W., & Schmid, H.P. (2015). A simple two‑dimensional parameterisation for flux footprint prediction (FFP). Geoscientific Model Development, 8(11), 3695–3713. https://doi.org/10.5194/gmd-8-3695-2015

You may also cite the software directly (see CITATION.cff).

Contributing

1. Fork → 2. Create branch → 3. Commit changes
2. Run tests (pytest) & linters (pre‑commit run --all-files)
3. Open a pull‑request

All contributions—bug reports, suggestions, or code—are welcome!

Development Road‑map

• Build out tests
• Build out documentation
• Footprint uncertainty quantification via Monte‑Carlo resampling
• OpenET API and Comparison
• Footprint aggregation across different time periods
• QGIS plug‑in for in‑map footprint visualisation

License

This project is licensed under the MIT License – see the LICENSE file for details.

Happy footprinting!