Spatial Extent of Data
USGS Data Source
USGS Thesaurus Keywords
ISO 19115 Topic Category
Other Subject Keywords
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.
| Author(s) |
Daniel D Buscombe |
| Publication Date | 2025-03-25 |
| Beginning Date of Data | 1984 |
| Ending Date of Data | 2024 |
| Data Contact | |
| DOI | https://doi.org/10.5066/P13EOBZQ |
| Citation | Buscombe, D.D., 2025, Labeled satellite imagery for training machine learning semantic segmentation models of coastal shorelines.: U.S. Geological Survey data release, https://doi.org/10.5066/P13EOBZQ. |
| Metadata Contact | |
| Metadata Date | 2025-03-25 |
| Related Publication | There was no related primary publication associated with this data release. |
| Citations of these data | No citations of these data are known at this time. |
| Access | public |
| License | http://www.usa.gov/publicdomain/label/1.0/ |
Harvest Date: 2026-04-24T04:09:52.367Z