Published July 13, 2019
| Version v1
Dataset
Open
Training data for: CoastSat image classification
Description
CoastSat image classification training data
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).
The automated shoreline extraction relies on a classifier (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.
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.
Files
classif_example.jpg
Files
(70.3 MB)
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md5:cc018beeb5af64c00845169fd30a9ccd
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Additional details
Related works
- Is documented by
- Journal article: 10.1016/j.coastaleng.2019.04.004 (DOI)
- Is referenced by
- Journal article: 10.1016/j.envsoft.2019.104528 (DOI)
- Is supplement to
- Software: 10.5281/zenodo.2779294 (DOI)
References
- Vos et al. 2019 https://doi.org/10.1016/j.coastaleng.2019.04.004
- Vos et al. 2019 https://doi.org/10.1016/j.envsoft.2019.104528