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eo-tides: Tide modelling tools for large-scale satellite Earth observation analysis

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Note: This package is a work in progress, and not currently ready for operational use.

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

eo-tides combines advanced tide modelling functionality from the pyTMD package with pandas, xarray and odc-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. from Digital Earth Australia or Microsoft Planetary Computer) loaded via Open Data Cube's odc-stac or datacube packages, supporting coastal and ocean earth observation analysis for any time period or location globally.

eo-tides abstract showing satellite data, tide data array and tide animation

Highlights

  • 🌊 Model tide heights and phases (e.g. high, low, ebb, flow) from multiple global ocean tide models in parallel, and return a pandas.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)

Supported tide models

eo-tides supports all ocean tide models supported by pyTMD. These include:

For instructions on how to set up these models for use in eo-tides, refer to Setting up tide models.

Citing eo-tides

To cite eo-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 underlying pyTMD Python package which powers the tide modelling functionality behind eo-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

Next steps

To get started, first follow the guide to installing eo-tides, and then set up one or multiple global ocean tide models.