Citation:
Citation_Information:
Originator: Daniel Buscombe
Originator: Mark A. Lundine
Originator: Catherine N. Janda
Originator: Sharon Batiste
Publication_Date: 20250325
Title:
Labeled satellite imagery for training machine learning semantic segmentation models of coastal shorelines.
Geospatial_Data_Presentation_Form: JPEG
Series_Information:
Series_Name: data release
Issue_Identification: DOI:10.5066/P13EOBZQ
Publication_Information:
Publication_Place:
Pacific Coastal and Marine Science Center, Santa Cruz, California
Publisher: U.S. Geological Survey
Other_Citation_Details:
Suggested Citation: Buscombe, D., Lundine, M.A., Janda, C.N., and Batiste, S., 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.
Description:
Abstract:
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.
Purpose:
These data provide resources for automatically detected coastal shoreline position for resource managers, science researchers, students, and the general public. These data can be used with image viewing software and can be used within specialist software for the purposes of training Machine Learning models to segment imagery into water, whitewater/surf, sediment, and 'other' for the purposes of shoreline mapping. Other potential uses of such data include mapping sand and whitewater/surf from geospatial imagery. The imagery are organized into three folders, which constitute three separate versions of the dataset. One folder contains visible-spectrum or RGB (Red-Green-Blue) imagery and corresponding label images. The second folder contains NDWI (Normalized Difference Water Index) imagery and associated labels. The third folder contains MNDWI (Modified Normalized Difference Water Index) imagery and associated labels. MNDWI and NDWI spectral index imagery are commonly used for water and shoreline detection. These data are used to train a Machine Learning model to carry out the task of semantic image segmentation. Labels were created using the image annotation tool, Doodler (Buscombe, 2022; Buscombe and others, 2022).
Supplemental_Information:
This data release was funded by the USGS Coastal and Marine Hazards and Resources Program. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. This data release contains modified Planetscope imagery, provided under the NASA (National Aeronautics and Space Administration) CSDA (Commercial Satellite Data Aquisition) program under the standard Scientific Use License available at
https://cdn.earthdata.nasa.gov/conduit/upload/14226/PlanetEULA042220.pdf, and the End User license agreement available at
https://earthdata.nasa.gov/s3fs-public/2022-02/Planet_Expanded_EULA_06-21.pdf. This license permits redistribution of imagery in significantly modified form. We provide only the visible (R, G, and B) bands of small sub-portions of downloaded tiles, in png format. As such, the original imagery (multispectral scenes in geotiff format) would have been cropped, its geospatial information removed, and re-encoded into 8bit png format.
Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 1984
Ending_Date: 2024
Currentness_Reference: collection years of satellite imagery.
Status:
Progress: Complete
Maintenance_and_Update_Frequency: None Planned
Spatial_Domain:
Bounding_Coordinates:
West_Bounding_Coordinate: 180.00000
East_Bounding_Coordinate: -180.00000
North_Bounding_Coordinate: 90.00000
South_Bounding_Coordinate: -90.00000
Keywords:
Theme:
Theme_Keyword_Thesaurus: USGS Metadata Identifier
Theme_Keyword: USGS:3f0efdeb-7bad-45f8-bbbe-7f70c78929e0
Theme:
Theme_Keyword_Thesaurus: Global Change Master Directory
Theme_Keyword: Hazards Planning
Theme_Keyword: Ocean Waves
Theme_Keyword: Erosion
Theme_Keyword: Sea Level Rise
Theme_Keyword: Extreme Weather
Theme:
Theme_Keyword_Thesaurus: ISO 19115 Topic Category
Theme_Keyword: Oceans
Theme_Keyword: ClimatologyMeteorologyAtmosphere
Theme:
Theme_Keyword_Thesaurus: Data Categories for Marine Planning
Theme_Keyword: Physical Habitats and Geomorphology
Theme:
Theme_Keyword_Thesaurus: USGS Thesaurus
Theme_Keyword: Climate Change
Theme_Keyword: Storms
Theme_Keyword: Sea-level Change
Theme:
Theme_Keyword_Thesaurus: Marine Realms Information Bank (MRIB) keywords
Theme_Keyword: sea level change
Theme_Keyword: waves
Theme_Keyword: coastal erosion
Theme:
Theme_Keyword_Thesaurus: None
Theme_Keyword: U.S. Geological Survey
Theme_Keyword: USGS
Theme_Keyword: Coastal and Marine Hazards and Resources Program
Theme_Keyword: CMHRP
Theme_Keyword: Pacific Coastal and Marine Science Center
Theme_Keyword: PCMSC
Access_Constraints: No access constraints
Use_Constraints:
USGS-authored or produced data and information are in the public domain from the U.S. Government and are freely redistributable with proper metadata and source attribution. Please recognize and acknowledge the U.S. Geological Survey as the originator(s) of the dataset and in products derived from these data. Users are advised to read the rest of the metadata record carefully for additional details.
Point_of_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization:
U.S. Geological Survey, Pacific Coastal and Marine Science Center
Contact_Person: PCMSC Science Data Coordinator
Contact_Address:
Address_Type: mailing and physical
Address: 2885 Mission Street
City: Santa Cruz
State_or_Province: CA
Postal_Code: 95060
Contact_Voice_Telephone: 831-427-4747
Contact_Electronic_Mail_Address: pcmsc_data@usgs.gov
Data_Set_Credit:
This data release was funded by the USGS Coastal and Marine Hazards and Resources Program.
Native_Data_Set_Environment:
The datasets were created in a Windows 11 Operating system, python 3.10. Results were output and saved in JPEG format.
Cross_Reference:
Citation_Information:
Originator: Daniel D. Buscombe
Publication_Date: 2022
Title:
Doodler--A web application built with plotly/dash for image segmentation with minimal supervision
Geospatial_Data_Presentation_Form: software
Series_Information:
Series_Name: software release
Issue_Identification: DOI:10.5066/P9YVHL23
Publication_Information:
Publication_Place:
Pacific Coastal and Marine Science Center, Santa Cruz, California
Publisher: U.S. Geological Survey
Other_Citation_Details:
Buscombe, D.D., 2022, Doodler--A web application built with plotly/dash for image segmentation with minimal supervision: U.S. Geological Survey software release,
https://doi.org/10.5066/P9YVHL23
Cross_Reference:
Citation_Information:
Originator: Daniel D. Buscombe
Originator: Evan B. Goldstein
Originator: Chris R. Sherwood
Originator: Cameron Bodine
Originator: Jenna A. Brown
Originator: Jaycee Favela
Originator: Sharon Fitzpatrick
Originator: Christine J. Kranenburg
Originator: Jin-Si R. Over
Originator: Andrew C. Ritchie
Originator: Jonathan A. Warrick
Publication_Date: 2022
Title: Human‐in‐the‐loop segmentation of Earth surface imagery
Other_Citation_Details:
Buscombe, D., Goldstein, E.B., Sherwood, C.R., Bodine, C., Brown, J.A., Favela, J., Fitzpatrick, S., Kranenburg, C.J., Over, J.R., Ritchie, A.C. and Warrick, J.A., 2022. Human‐in‐the‐loop segmentation of Earth surface imagery. Earth and Space Science, 9(3), p.e2021EA002085.
Online_Linkage: https://doi.org/10.1029/2021EA002085
Cross_Reference:
Citation_Information:
Originator: Buscombe, D.
Originator: Goldstein, E.B.
Publication_Date: 2022
Title:
A reproducible and reusable pipeline for segmentation of geoscientific imagery
Other_Citation_Details:
Buscombe, D., and Goldstein, E.B, 2022, A reproducible and reusable pipeline for segmentation of geoscientific imagery. Journal of Open Source Software, 9(99), 6683
Online_Linkage: https://doi.org/10.1029/2022EA002332
Cross_Reference:
Citation_Information:
Originator: Fitzpatrick, S.
Originator: Buscombe, D.
Originator: Warrick, J.A.
Originator: Lundine, M.A.
Originator: Vos, K.
Publication_Date: 2024
Title:
Sub-annual to multi-decadal shoreline variability from publicly available satellite imagery
Other_Citation_Details:
Fitzpatrick, S., Buscombe, D., Warrick, J.A., Lundine, M.A., and Vos, K., 2024, CoastSeg: an accessible and extendable hub for satellite-derived-shoreline (SDS) detection and mapping. Journal of Open Source Software, 9(99), 6683
Online_Linkage: https://doi.org/10.21105/joss.06683
Cross_Reference:
Citation_Information:
Originator: Vos, K.
Originator: Harley, M.D.
Originator: Splinter, K.D.
Originator: Simmons, J.A.
Originator: Turner, I.L.
Publication_Date: 2019
Title:
Sub-annual to multi-decadal shoreline variability from publicly available satellite imagery
Other_Citation_Details:
Vos, K., Harley, M.D., Splinter, K.D., Simmons, J.A., and Turner, I.L., 2019, Sub-annual to multi-decadal shoreline variability from publicly available satellite imagery: Coastal Engineering, v. 150, p. 160-174.
Online_Linkage: https://doi.org/10.1016/j.coastaleng.2019.04.004
Cross_Reference:
Citation_Information:
Originator: Gorelick, N.
Originator: Hancher, M.
Originator: Dixon, M.
Originator: Ilyshechenko, S.
Originator: Thau, D.
Originator: Moore, R.
Publication_Date: 2017
Title:
Google Earth Engine: Planetary-scale geospatial analysis for everyone.
Other_Citation_Details:
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., and Moore, R., 2017, Google Earth Engine: Planetary-scale geospatial analysis for everyone: Remote Sensing of Environment, v. 202, p. 18-27.
Online_Linkage: https://doi.org/10.1016/j.rse.2017.06.031
