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CoastSat: A Google Earth Engine-enabled Python']Python toolkit to extract shorelines from publicly available satellite imagery
被引:274
|作者:
Vos, Kilian
[1
]
Splinter, Kristen D.
[1
]
Harley, Mitchell D.
[1
]
Simmons, Joshua A.
[1
]
Turner, Ian L.
[1
]
机构:
[1] UNSW Sydney, Sch Civil & Environm Engn, Water Res Lab, 110 King St, Manly Vale, NSW 2093, Australia
基金:
澳大利亚研究理事会;
关键词:
Google Earth Engine;
Shoreline mapping;
Landsat;
Sentinel-2;
Sub-pixel resolution;
IMPACTS;
CLIMATE;
IDENTIFICATION;
VARIABILITY;
CALIBRATION;
D O I:
10.1016/j.envsoft.2019.104528
中图分类号:
TP39 [计算机的应用];
学科分类号:
081203 ;
0835 ;
摘要:
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 similar to 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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