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• ⚙️Github repository:https://github.com/GeoscienceAustralia/eo-tides/
• 📘Documentation:https://GeoscienceAustralia.github.io/eo-tides/
• 🐍PyPI:https://pypi.org/project/eo-tides/

eo-tides provides powerful parallelized tools for integrating satellite Earth observation data with tide modelling. 🛠️🌊🛰️

eo-tides combines advanced tide modelling functionality from thepyTMD package withpandas,xarray andodc-geo, providing a suite of flexible tools for efficient analysis of coastal and ocean Earth observation data – from regional, continental, to global scale.

These tools can be applied to petabytes of freely available satellite data (e.g. fromDigital Earth Australia orMicrosoft Planetary Computer) loaded via Open Data Cube'sodc-stac ordatacube packages, supporting coastal and ocean earth observation analysis for any time period or location globally.

• 🌊 Model tide heights and phases (e.g. high, low, ebb, flow) from multiple global ocean tide models in parallel, and return apandas.DataFrame for further analysis
• 🛰️ "Tag" satellite data with tide heights based on the exact moment of image acquisition
• 🌐 Model tides for every individual satellite pixel through time, producing three-dimensional "tide height"xarray-format datacubes that can be integrated with satellite data
• 📈 Calculate statistics describing local tide dynamics, as well as biases caused by interactions between tidal processes and satellite orbits
• 🛠️ Validate modelled tides using measured sea levels from coastal tide gauges (e.g.GESLA Global Extreme Sea Level Analysis)

eo-tides supportsall ocean tide models supported bypyTMD. These include:

• Empirical Ocean Tide model (EOT20)
• Finite Element Solution tide models (FES2022, FES2014, FES2012)
• TOPEX/POSEIDON global tide models (TPXO10, TPXO9, TPXO8)
• Global Ocean Tide models (GOT5.6, GOT5.5, GOT4.10, GOT4.8, GOT4.7)
• Hamburg direct data Assimilation Methods for Tides models (HAMTIDE11)
• Technical University of Denmark tide models (DTU23)

For instructions on how to set up these models for use ineo-tides, refer toSetting up tide models.

To get started witheo-tides, follow theInstallation andSetting up tide models guides.

Interactive Jupyter Notebook usage examples and more complex coastal EO case studies can be found in thedocs/notebooks/ directory, orrendered in the documentation here.

To citeeo-tides in your work, please use the following citation:

Bishop-Taylor, R., Sagar, S., Phillips, C., & Newey, V. (2024). eo-tides: Tide modelling tools for large-scale satellite earth observation analysis. https://github.com/GeoscienceAustralia/eo-tides

In addition, please consider also citing the underlyingpyTMD Python package which powers the tide modelling functionality behindeo-tides:

Sutterley, T. C., Alley, K., Brunt, K., Howard, S., Padman, L., Siegfried, M. (2017) pyTMD: Python-based tidal prediction software. 10.5281/zenodo.5555395

For a full list of acknowledgements, refer toCitations and Credits.This repository was initialised using thecookiecutter-uv package.