Document of bibliographic reference 318199

BibliographicReference record

Type

Bibliographic resource

Type of document

Journal article

BibLvlCode

AS

Title

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

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.

WebOfScience code

https://www.webofscience.com/wos/woscc/full-record/WOS:000498063900004

Bibliographic citation

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

Topic

Marine

Is peer reviewed

true

Access rights

open access

Is accessible for free

true