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                <gco:CharacterString>The `eo-tides` package provides powerful parallelized tools for integrating satellite Earth observation (EO) data with ocean tide modelling. The package provides a flexible Python-based toolkit for modelling and attributing tide heights to a time-series of satellite images based on the spatial extent and acquisition time of each satellite observation. 

`eo-tides` leverages advanced tide modelling functionality from the `pyTMD` tide prediction software, combining this fundamental tide modelling capability with EO spatial analysis tools from `odc-geo`. This allows tides to be modelled in parallel automatically using over 50 supported tide models, and returned in standardised `pandas` and `xarray` data formats for further analysis.

Tools from `eo-tides` are designed to be applied directly to petabytes of freely available satellite data loaded from the cloud using Open Data Cube's `odc-stac` or `datacube` packages (e.g. using Digital Earth Australia or Microsoft Planetary Computer's SpatioTemporal Asset Catalogues). Additional functionality enables evaluating potential satellite-tide biases, and validating modelled tides using external tide gauge data — both important considerations for assessing the reliability and accuracy of coastal EO workflows. In combination, these open source tools support the efficient, scalable and robust analysis of coastal EO data for any time period or location globally.
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