https://github.com/geoscienceaustralia/eo-tides
Tide modelling tools for large-scale satellite earth observation analysis
https://github.com/geoscienceaustralia/eo-tides
coastal coastal-modelling earth-observation ocean-modelling oceanography remote-sensing satellite-data tides
Last synced: 8 months ago
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Tide modelling tools for large-scale satellite earth observation analysis
- Host: GitHub
- URL: https://github.com/geoscienceaustralia/eo-tides
- Owner: GeoscienceAustralia
- License: apache-2.0
- Created: 2024-09-16T06:10:09.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-21T00:26:14.000Z (9 months ago)
- Last Synced: 2025-02-22T05:24:46.775Z (8 months ago)
- Topics: coastal, coastal-modelling, earth-observation, ocean-modelling, oceanography, remote-sensing, satellite-data, tides
- Language: Python
- Homepage: https://GeoscienceAustralia.github.io/eo-tides/
- Size: 153 MB
- Stars: 25
- Watchers: 5
- Forks: 4
- Open Issues: 10
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Citation: CITATION.cff
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README
# `eo-tides`: Tide modelling tools for large-scale satellite earth observation analysis
[](https://pypi.org/project/eo-tides/)
[](https://github.com/GeoscienceAustralia/eo-tides/actions/workflows/main.yml?query=branch%3Amain)
[](https://github.com/GeoscienceAustralia/eo-tides/blob/main/pyproject.toml)
[](https://codecov.io/gh/GeoscienceAustralia/eo-tides)
[](https://img.shields.io/github/license/GeoscienceAustralia/eo-tides)
[](https://joss.theoj.org/papers/b5680c39bf831c1159c41a2eb7ec9c5e)
- ⚙️ **Github repository**:
- 📘 **Documentation**:
- 🐍 **PyPI**:
`eo-tides` provides powerful parallelized tools for integrating satellite Earth observation data with tide modelling. 🛠️🌊🛰️
`eo-tides` combines advanced tide modelling functionality from the [`pyTMD`](https://pytmd.readthedocs.io/en/latest/) package with [`pandas`](https://pandas.pydata.org/docs/index.html), [`xarray`](https://docs.xarray.dev/en/stable/) and [`odc-geo`](https://odc-geo.readthedocs.io/en/latest/), 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](https://knowledge.dea.ga.gov.au/) or [Microsoft Planetary Computer](https://planetarycomputer.microsoft.com/)) loaded via Open Data Cube's [`odc-stac`](https://odc-stac.readthedocs.io/en/latest/) or [`datacube`](https://opendatacube.readthedocs.io/en/latest/) packages, supporting coastal and ocean earth observation analysis for any time period or location globally.
## 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](https://gesla.org/))
## Supported tide models
`eo-tides` supports [all ocean tide models supported by `pyTMD`](https://pytmd.readthedocs.io/en/latest/getting_started/Getting-Started.html#model-database). These include:
- [Empirical Ocean Tide model](https://doi.org/10.5194/essd-13-3869-2021) (EOT20)
- [Finite Element Solution tide models](https://doi.org/10.5194/os-2020-96) (FES2022, FES2014, FES2012)
- [TOPEX/POSEIDON global tide models](https://www.tpxo.net/global) (TPXO10, TPXO9, TPXO8)
- [Global Ocean Tide models](https://doi.org/10.1002/2016RG000546) (GOT5.6, GOT5.5, GOT4.10, GOT4.8, GOT4.7)
- [Hamburg direct data Assimilation Methods for Tides models](https://doi.org/10.1002/2013JC009766) (HAMTIDE11)
- [Technical University of Denmark tide models](https://doi.org/10.11583/DTU.23828874) (DTU23)
For instructions on how to set up these models for use in `eo-tides`, refer to [Setting up tide models](setup.md).
## Installing and setting up `eo-tides`
To get started with `eo-tides`, follow the [Installation](https://geoscienceaustralia.github.io/eo-tides/install/) and [Setting up tide models](https://geoscienceaustralia.github.io/eo-tides/setup/) guides.
## Jupyter Notebooks code examples
Interactive Jupyter Notebook usage examples and more complex coastal EO case studies can be found in the [`docs/notebooks/`](https://github.com/GeoscienceAustralia/eo-tides/tree/main/docs/notebooks) directory, or [rendered in the documentation here](https://geoscienceaustralia.github.io/eo-tides/notebooks/Model_tides/).
## 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](https://pytmd.readthedocs.io/en/latest/) 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
```
## Acknowledgements
For a full list of acknowledgements, refer to [Citations and Credits](https://geoscienceaustralia.github.io/eo-tides/credits/).
This repository was initialised using the [`cookiecutter-uv`](https://github.com/fpgmaas/cookiecutter-uv) package.