CoastSat: A Google Earth Engine-enabled Python toolkit to extract shorelines from publicly available satellite imagery

• Published in: Environmental modelling & software : with environment data news Vol. 122; p. 104528
• Main Authors: Vos, Kilian, Splinter, Kristen D., Harley, Mitchell D., Simmons, Joshua A., Turner, Ian L.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.12.2019; Elsevier Science Ltd
• Subjects: Algorithms; Coastal engineering; Coastal management; Coasts; Computer programs; computer software; Google Earth Engine; Image classification; Image detection; Image enhancement; Image processing; Image segmentation; Internet; Landsat; Landsat satellites; Open source software; Pixels; Remote sensing; Satellite imagery; Sentinel-2; Shoreline mapping; Shorelines; Software; Source code; Spatial discrimination; Spatial resolution; Sub-pixel resolution; time series analysis; Shoreline mapping; Google Earth Engine; Sub-pixel resolution; Landsat; Sentinel-2
• ISSN: 1364-8152; 1873-6726; 1873-6726
• DOI: 10.1016/j.envsoft.2019.104528

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. •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.