CoastSat: a Google Earth Engine-enabled Python toolkit to extract shorelines from publicly available satellite imagery
Vos, K.; Splinter, K.D.; Harley, M.D.; Simmons, J.A.; Turner, I.L. (2019). CoastSat: a Google Earth Engine-enabled Python toolkit to extract shorelines from publicly available satellite imagery. Environ. Model. Softw. 122: 104528. https://dx.doi.org/10.1016/j.envsoft.2019.104528
In: Environmental Modelling & Software. Elsevier: Oxford. ISSN 1364-8152; e-ISSN 1873-6726, more
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| Keyword |
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| Author keywords |
Google Earth Engine; Shoreline mapping; Landsat; Sentinel-2; Sub-pixel resolution |
| Authors | | Top |
- Vos, K.
- Splinter, K.D.
- Harley, M.D.
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- Simmons, J.A.
- Turner, I.L.
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| Abstract |
CoastSat is an open-source software toolkit written in Python that enables the user to obtain time-series of shoreline position at any sandy coastline worldwide from 30+ years (and growing) of publicly available satellite imagery. The toolkit exploits the capabilities of Google Earth Engine to efficiently retrieve Landsat and Sentinel-2 images cropped to any user-defined region of interest. The resulting images are pre-processed to remove cloudy pixels and enhance spatial resolution, before applying a robust and generic shoreline detection algorithm. This novel shoreline detection technique combines a supervised image classification and a sub-pixel resolution border segmentation to map the position of the shoreline with an accuracy of ~10 m. The purpose of CoastSat is to provide coastal managers, engineers and scientists a user-friendly and practical toolkit to monitor and explore their coastlines. The software is freely-available on GitHub (https://github.com/kvos/CoastSat) and is accompanied by guided examples (Jupyter Notebook) plus step-by-step README documentation. |
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