Labeled satellite imagery for training machine learning semantic segmentation models of coastal shorelines.
A dataset of Landsat, Sentinel, and Planetscope satellite images of coastal shoreline regions, and corresponding semantic segmentations. The dataset consists of folders of images and label images. Label images are images where each pixel is given a discrete class by a human annotator, among the following classes: a) water, b) whitewater/surf, c) sediment, and d) other. These data are intended only to be used as a training and validation dataset for a machine learning based image segmentation model that is specifically designed for the task of coastal shoreline satellite image semantic segmentation.
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Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[ "010:12" ] |
| contactPoint |
{ "fn": "PCMSC Science Data Coordinator", "@type": "vcard:Contact", "hasEmail": "mailto:pcmsc_data@usgs.gov" } |
| description | A dataset of Landsat, Sentinel, and Planetscope satellite images of coastal shoreline regions, and corresponding semantic segmentations. The dataset consists of folders of images and label images. Label images are images where each pixel is given a discrete class by a human annotator, among the following classes: a) water, b) whitewater/surf, c) sediment, and d) other. These data are intended only to be used as a training and validation dataset for a machine learning based image segmentation model that is specifically designed for the task of coastal shoreline satellite image semantic segmentation. |
| distribution |
[ { "@type": "dcat:Distribution", "title": "Digital Data", "format": "XML", "accessURL": "https://doi.org/10.5066/P13EOBZQ", "mediaType": "application/http", "description": "Landing page for access to the data" }, { "@type": "dcat:Distribution", "title": "Original Metadata", "format": "XML", "mediaType": "text/xml", "description": "The metadata original format", "downloadURL": "https://data.usgs.gov/datacatalog/metadata/USGS.3f0efdeb-7bad-45f8-bbbe-7f70c78929e0.xml" } ] |
| identifier | http://datainventory.doi.gov/id/dataset/USGS_3f0efdeb-7bad-45f8-bbbe-7f70c78929e0 |
| keyword |
[ "CMHRP", "Climate Change", "ClimatologyMeteorologyAtmosphere", "Coastal and Marine Hazards and Resources Program", "Erosion", "Extreme Weather", "Hazards Planning", "Ocean Waves", "Oceans", "PCMSC", "Pacific Coastal and Marine Science Center", "Physical Habitats and Geomorphology", "Sea Level Rise", "Sea-level Change", "Storms", "U.S. Geological Survey", "USGS", "USGS:3f0efdeb-7bad-45f8-bbbe-7f70c78929e0", "coastal erosion", "sea level change", "waves" ] |
| modified | 2025-03-25T00:00:00Z |
| publisher |
{ "name": "U.S. Geological Survey", "@type": "org:Organization" } |
| spatial | 180.00000, -90.00000, -180.00000, 90.00000 |
| theme |
[ "geospatial" ] |
| title | Labeled satellite imagery for training machine learning semantic segmentation models of coastal shorelines. |
