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Training data for: CoastSat image classification

<p><strong>CoastSat image classification training data </strong></p> <p>CoastSat is an open-source global shoreline mapping toolbox, available at https://github.com/kvos/CoastSat, which enables users to extract time-series of shoreline change from 30+ years of publicly available satellite imagery (Landsat 5, 7, 8 and Sentinel-2).</p> <p>The automated shoreline extraction relies on a classifier&nbsp;(Multilayer Perceptron from scikit-learn) which labels each pixels on the images with one of four classes: sand, water, white-water and other land features.</p> <p>The data used to train the classifier is stored here, the README.md file provides information on the data organisation and content of each file.</p>

ShareScore

48/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
8
Access
20
Reuse readiness
8
Engagement
4

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