CoastSat: A Google Earth Engine-enabled Python toolkit to extract shorelines from publicly available satellite imagery. (December 2019) - Vos, Kilian; Splinter, Kristen D.; Harley, Mitchell D.; Simmons, Joshua A.; Turner, Ian L.
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. Highlights: Global shoreline mapping toolbox from publicly available Landsat and Sentinel-2 satellite imagery. Open-source Python toolkit that enables users to obtain 30+ years of satellite-derived shorelines at any beach worldwide. Satellite images of the user-defined region of interest are retrieved efficiently with Google Earth Engine. The sand/water interface is automatically mapped using a robust sub-pixel resolution shoreline detection technique.