Metadata: Identification_Information: Citation: Citation_Information: Originator: Phillipe A. Wernette Originator: Daniel D. Buscombe Originator: Sharon Fitzpatrick Originator: Jaycee Favela Originator: Nicholas Enwright Originator: Evan Goldstein Originator: Erin Dunand Publication_Date: 20220319 Title: Coast Train--Labeled imagery for training and evaluation of data-driven models for image segmentation Geospatial_Data_Presentation_Form: list of images and details in csv format; imagery in NumPy binary file format Series_Information: Series_Name: data release Issue_Identification: DOI:10.5066/P91NP87I Publication_Information: Publication_Place: Pacific Coastal and Marine Science Center, Santa Cruz, California Publisher: U.S. Geological Survey Online_Linkage: https://doi.org/10.5066/P91NP87I Description: Abstract: Coast Train is a library of images of coastal environments, annotations, and corresponding thematic label masks (or ‘label images’) collated for the purposes of training and evaluating machine learning (ML), deep learning, and other models for image segmentation. It includes image sets from both geospatial satellite, aerial, and UAV imagery and orthomosaics, as well as non-geospatial oblique and nadir imagery. Images include a diverse range of coastal environments from the U.S. Pacific, Gulf of Mexico, Atlantic, and Great Lakes coastlines, consisting of time-series of high-resolution (≤1m) orthomosaics and satellite image tiles (10–30m). Each image, image annotation, and labelled image is available as a single NPZ zipped file. NPZ files follow the following naming convention: {datasource}_{numberofclasses}_{threedigitdatasetversion}.zip, where {datasource} is the source of the original images (for example, NAIP, Landsat 8, Sentinel 2), {numberofclasses} is the number of classes used to annotate the images, and {threedigitdatasetversion} is the three-digit code corresponding to the dataset version (in other words, 001 is version 1). Each zipped folder contains a collection of NPZ format files, each of which corresponds to an individual image. An individual NPZ file is named after the image that it represents and contains (1) a CSV file with detail information for every image in the zip folder and (2) a collection of the following NPY files: orig_image.npy (original input image unedited), image.npy (original input image after color balancing and normalization), classes.npy (list of classes annotated and present in the labelled image), doodles.npy (integer image of all image annotations), color_doodles.npy (color image of doodles.npy), label.npy (labelled image created from the classes present in the annotations), and settings.npy (annotation and machine learning settings used to generate the labelled image from annotations). All NPZ files can be extracted using the utilities available in Doodler (Buscombe, 2022). A merged CSV file containing detail information on the complete imagery collection is available at the top level of this data release, details of which are available in the Entity and Attribute section of this metadata file. Purpose: Training machine learning (ML) and other models for segmentation will greatly facilitate the creation of land cover maps from geospatial imagery with greater specificity, as well as mapping coastal sediments, transient waterbodies, landforms, and other features of interest, in both geospatial and non-geospatial imagery. Coast Train adheres to the principle of ‘Map Once, Use Many Times’ and is well positioned to transfer learning across a wide range of coastal environments. Supplemental_Information: Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Time_Period_of_Content: Time_Period_Information: Range_of_Dates/Times: Beginning_Date: 20080101 Ending_Date: 20201231 Currentness_Reference: date range of imagery in library Status: Progress: Planned Maintenance_and_Update_Frequency: As needed Spatial_Domain: Bounding_Coordinates: West_Bounding_Coordinate: -180.0 East_Bounding_Coordinate: 180.0 North_Bounding_Coordinate: 90.0 South_Bounding_Coordinate: -90.0 Keywords: Theme: Theme_Keyword_Thesaurus: USGS Metadata Identifier Theme_Keyword: USGS:9cdb71c1-cc5a-4786-9232-93d7e7a340cf Theme: Theme_Keyword_Thesaurus: ISO 19115 Topic Category Theme_Keyword: environment Theme_Keyword: geoscientificinformation Theme: Theme_Keyword_Thesaurus: Data Categories for Marine Planning Theme_Keyword: distributions Theme_Keyword: Physical Habitats and Geomorphology Theme_Keyword: habitat Theme_Keyword: infrastructure Theme_Keyword: structures Theme: Theme_Keyword_Thesaurus: USGS Thesaurus Theme_Keyword: image analysis Theme_Keyword: mitigation of coastal hazards Theme_Keyword: remote sensing Theme_Keyword: aerial photography Theme_Keyword: multispectral imaging Theme_Keyword: visible light imaging Theme_Keyword: datasets Theme_Keyword: geospatial datasets Theme_Keyword: image collections Theme_Keyword: earth sciences Theme_Keyword: geography Theme_Keyword: geology Theme_Keyword: life sciences Theme_Keyword: botany Theme_Keyword: ecology Theme_Keyword: social sciences Theme_Keyword: biological and physical processes Theme_Keyword: hazards Theme_Keyword: human impacts Theme_Keyword: land use change Theme_Keyword: land use and land cover Theme_Keyword: coastal ecosystems Theme: Theme_Keyword_Thesaurus: Marine Realms Information Bank (MRIB) keywords Theme_Keyword: agents of coastal change Theme_Keyword: coastal processes Theme_Keyword: anthropogenic agents of coastal change Theme_Keyword: coastal development Theme_Keyword: coastal protection structures Theme_Keyword: effects of coastal change Theme_Keyword: human responses to coastal change Theme_Keyword: earth system Theme_Keyword: bay Theme_Keyword: beach Theme_Keyword: cape Theme_Keyword: cliff Theme_Keyword: coast Theme_Keyword: coastal barrier Theme_Keyword: coastal plain Theme_Keyword: cove Theme_Keyword: dune Theme_Keyword: island Theme_Keyword: lagoon Theme_Keyword: lake Theme_Keyword: marsh Theme_Keyword: mudflat Theme_Keyword: ocean Theme_Keyword: shore Theme_Keyword: swamp Theme_Keyword: tidal flat Theme_Keyword: tidal inlet Theme_Keyword: beach zone communities Theme_Keyword: breakwater/shoreline stabilization structure Theme_Keyword: bridge Theme_Keyword: canal Theme_Keyword: jetty Theme_Keyword: environment Theme_Keyword: hazards and disasters Theme_Keyword: erosion Theme_Keyword: floods Theme_Keyword: remote sensing Theme_Keyword: aerial and satellite photography Theme_Keyword: biology Theme_Keyword: ecology Theme_Keyword: computer science Theme_Keyword: geography Theme_Keyword: environmental geography Theme_Keyword: physical geography Theme_Keyword: geology Theme_Keyword: information science 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 Theme_Keyword: St. Petersburg Coastal and Marine Science Center Theme_Keyword: SPCMSC Theme_Keyword: Wetland and Aquatic Research Center Theme_Keyword: WARC Theme_Keyword: Woods Hole Coastal and Marine Science Center Theme_Keyword: WHCMSC Place: Place_Keyword_Thesaurus: Geographic Names Information System (GNIS) Place_Keyword: United States Access_Constraints: None 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. 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 Browse_Graphic: Browse_Graphic_File_Name: coast_train_thumbnail.png Browse_Graphic_File_Description: Split graphic with the original image on the left and the segmented right half of the image on the right. Browse_Graphic_File_Type: PNG Native_Data_Set_Environment: Images were processed using Doodler software (Buscombe, 2022) in Windows operating systems. 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 Online_Linkage: https://doi.org/10.5066/P9YVHL23 Data_Quality_Information: Attribute_Accuracy: Attribute_Accuracy_Report: Mean Intersection over Union (IoU) scores for quantifying inter-labeler agreement were computed using 120 images across two datasets, namely NAIP (70 image pairs) and Sentinel-2 (50 image pairs), that have been labeled independently by experienced labelers. Mean IoU is the standard way to report agreement between two realizations of the same label image. Further, because IoU quantifies spatial overlap and is prone to class imbalance, Kullback-Leibler divergence scores were also computed to quantify agreement between class-frequency distributions. When comparing IoU and Dice scores, it is preferable to examine agreement using multiple independent metrics. The mean of mean IoU scores was 0.88, which we recommend using as an expected irreducible error. Previous research suggests that mean IoU scores tend to be inversely correlated with number of classes; therefore, this error is a conservative estimate. Logical_Consistency_Report: All annotation values are integer based, with each integer corresponding to a unique class. The program used to generate the final classified/labelled images ensured that every pixel in the original image is classified into one of the annotated classes. There is no possibility that the actual values are outside of the reported ranges of values. Completeness_Report: Dataset is considered complete for the information presented, as described in the abstract. Users are advised to read the rest of the metadata record carefully for additional details. Positional_Accuracy: Horizontal_Positional_Accuracy: Horizontal_Positional_Accuracy_Report: A formal accuracy assessment of the horizontal positional information in the dataset has not been conducted. Each of the input data sources has its own horizontal accuracy available in their source metadata. Lineage: Process_Step: Process_Description: Image Annotation/Doodling--Each image was opened using Doodler with the class list provided in the metadata sheet. The user would then select a single class from the options on the right and click and hold on the image to begin drawing a line (annotate/doodle) where the selected class exists on the image. Annotations can be quick and as simple as a point or single line or as complex as a meandering or looping back series of lines. This annotation process was repeated one or more times for every class present in the image. Process_Date: 20211231 Process_Step: Process_Description: Image Classification/Segmentation--Once image annotations were complete for all classes present in the image, the program will segment the image and classify every pixel in it by checking the “Compute/Show segmentation” box on the right. If the final image is not accurate to the classes present and their distribution, then the user can uncheck the “Compute/Show segmentation” box and repeat the annotation and classification/segmentation steps until they are satisfied with the final segmented image. Process_Date: 20211231 Process_Step: Process_Description: Edited to correct spelling of author name. No data were changed. (scochran@usgs.gov) Process_Date: 20230504 Spatial_Data_Organization_Information: Indirect_Spatial_Reference: Original images were downloaded at sites along the conterminous U.S. coastline, including sites along the U.S. Atlantic, Gulf of Mexico, Pacific, and Great Lakes coasts. Sites were selected to provide a representative sample of an array of coastal types (for example, sandy, cliff, marsh, wetland, developed). Refer to the self-contained NPZ files for more information on locations of original images. Entity_and_Attribute_Information: Detailed_Description: Entity_Type: Entity_Type_Label: CoastTrain_imagery_details.csv Entity_Type_Definition: Table containing detailed information about the imagery in this dataset. Entity_Type_Definition_Source: Producer defined Attribute: Attribute_Label: name Attribute_Definition: Name of image source Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Unrepresentable_Domain: Unique identifier of image name. Attribute: Attribute_Label: publisher Attribute_Definition: Original publisher of the image source Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Unrepresentable_Domain: Unique identifier of image publisher. Attribute: Attribute_Label: labels Attribute_Definition: The image label file. One-hot-encoded label image (2D raster) in 8-bit unsigned integer. Each integer encodes a class label, incrementing through 'classes' starting at zero. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Unrepresentable_Domain: Unique identifier of label image file. Attribute: Attribute_Label: images Attribute_Definition: The original image file used in classification. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Unrepresentable_Domain: Unique identifier of image filename. Attribute: Attribute_Label: annotation_image_filename Attribute_Definition: Image filename with annotations. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Unrepresentable_Domain: Unique identifier of annotation image filename. Attribute: Attribute_Label: classes_array Attribute_Definition: An array of classification classes in the image. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: water Enumerated_Domain_Value_Definition: Classified as water Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: whitewater Enumerated_Domain_Value_Definition: Classified as whitewater Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: surf Enumerated_Domain_Value_Definition: Classified as surf Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: mud_silt Enumerated_Domain_Value_Definition: Classified as mud or fine sediment Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: sand Enumerated_Domain_Value_Definition: Classified as bare sand Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: gravel Enumerated_Domain_Value_Definition: Classified as gravel Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: gravel_shell Enumerated_Domain_Value_Definition: Classified as mixture of gravel and shells Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: cobble_gravel Enumerated_Domain_Value_Definition: Classified as gravel with cobbles Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: bedrock Enumerated_Domain_Value_Definition: Classified as exposed bedrock Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: ice_snow Enumerated_Domain_Value_Definition: Classified as ice or snow Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: bare_ground Enumerated_Domain_Value_Definition: Classified as bare ground Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: sediment Enumerated_Domain_Value_Definition: Classified as bare sediment Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: other_natural_terrain Enumerated_Domain_Value_Definition: Classified as other natural terrain Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: other_bare_natural_terrain Enumerated_Domain_Value_Definition: Classified as other bare natural terrain Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: vegetated Enumerated_Domain_Value_Definition: Classified as vegetation Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: vegetated_ground Enumerated_Domain_Value_Definition: Classified as ground with vegetation Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: vegetated_surface Enumerated_Domain_Value_Definition: Classified as vegetation Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: marsh_vegetation Enumerated_Domain_Value_Definition: Classified as marsh vegetation Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: terrestrial_vegetation Enumerated_Domain_Value_Definition: Classified as terrestrial vegetation Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: agricultural Enumerated_Domain_Value_Definition: Classified as agricultural Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: cloud Enumerated_Domain_Value_Definition: Classified as cloud Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: development Enumerated_Domain_Value_Definition: Classified as consisting of human development Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: dev Enumerated_Domain_Value_Definition: Classified as consisting of human development Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: coastal_defense Enumerated_Domain_Value_Definition: Classified as coastal defense Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: buildings Enumerated_Domain_Value_Definition: Classified as building Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: pavement_road Enumerated_Domain_Value_Definition: Classified as pavement Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: vehicles Enumerated_Domain_Value_Definition: Classified as vehicles Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: people Enumerated_Domain_Value_Definition: Classified as person Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: other_anthro Enumerated_Domain_Value_Definition: Classified as other anthropogenic object Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: unusual Enumerated_Domain_Value_Definition: Classified as unusal object or land cover Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: unknown Enumerated_Domain_Value_Definition: Classified as unknown land cover Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: no_data Enumerated_Domain_Value_Definition: No data contained in pixels Enumerated_Domain_Value_Definition_Source: Producer defined Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: nodata Enumerated_Domain_Value_Definition: No data contained in pixels Enumerated_Domain_Value_Definition_Source: Producer defined Attribute: Attribute_Label: num_classes Attribute_Definition: Number of classification classes in the image. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 1 Range_Domain_Maximum: 12 Attribute: Attribute_Label: classes_integer Attribute_Definition: One integer per class in num_classes. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 0 Range_Domain_Maximum: 12 Attribute: Attribute_Label: classes_present_integer Attribute_Definition: An array of integer classes present in the image. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 0 Range_Domain_Maximum: 12 Attribute: Attribute_Label: classes_present_array Attribute_Definition: An array of classes present in the image. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Unrepresentable_Domain: Values present in image from classes Attribute: Attribute_Label: pen_width Attribute_Definition: Final width in pixels of pen used to annotate in the Doodler program. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 1 Range_Domain_Maximum: 10 Attribute: Attribute_Label: CRF_theta Attribute_Definition: Internal classifier hyperparameter used by the Doodler program. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 1 Range_Domain_Maximum: 1 Attribute: Attribute_Label: CRF_mu Attribute_Definition: Internal classifier hyperparameter used by the Doodler program. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 1 Range_Domain_Maximum: 99 Attribute: Attribute_Label: CRF_downsample_factor Attribute_Definition: Internal classifier hyperparameter used by the Doodler program. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 1 Range_Domain_Maximum: 5 Attribute: Attribute_Label: Classifier_downsample_factor Attribute_Definition: Internal classifier hyperparameter used by the Doodler program. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 1 Range_Domain_Maximum: 8 Attribute: Attribute_Label: prob_of_unary_potential Attribute_Definition: Internal classifier hyperparameter used by the Doodler program. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 0.1 Range_Domain_Maximum: 3.0 Attribute: Attribute_Label: doodle_spatial_density Attribute_Definition: Proportion of the image annotated. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 0.000526323 Range_Domain_Maximum: 0.999627422 Attribute: Attribute_Label: num_of_scales Attribute_Definition: Internal classifier hyperparameter used by the Doodler program. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 3 Range_Domain_Maximum: 3 Attribute: Attribute_Label: acc_georef Attribute_Definition: Accuracy, in meters, of the specification of 'XMin', 'XMax' and 'YMin', 'YMax'. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 1 Range_Domain_Maximum: 11.248 Attribute: Attribute_Label: epsg Attribute_Definition: EPSG code for the projected coordinate system. See 'CRS' attribute for a complete description of codes used. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 26910 Range_Domain_Maximum: 32618 Attribute: Attribute_Label: year Attribute_Definition: Acquisition year of the image source. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 2008 Range_Domain_Maximum: 2021 Attribute: Attribute_Label: month Attribute_Definition: Acquisition month of the image source. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 1 Range_Domain_Maximum: 12 Attribute: Attribute_Label: day Attribute_Definition: Acquisition day of the image source. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 1 Range_Domain_Maximum: 31 Attribute: Attribute_Label: hour Attribute_Definition: Acquisition hour of the image source. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 0 Range_Domain_Maximum: 23 Attribute: Attribute_Label: minute Attribute_Definition: Acquisition minute of the image source. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 0 Range_Domain_Maximum: 59 Attribute: Attribute_Label: second Attribute_Definition: Acquisition second of the image source. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 0 Range_Domain_Maximum: 59 Attribute: Attribute_Label: XMin Attribute_Definition: Minimum easting of the image footprint. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 233870.0 Range_Domain_Maximum: 787860.0 Attribute: Attribute_Label: XMax Attribute_Definition: Maximum easting of the image footprint. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 235750.0 Range_Domain_Maximum: 790530.0 Attribute: Attribute_Label: YMin Attribute_Definition: Minimum northing of the image footprint. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 2875253.0 Range_Domain_Maximum: 5332914.0 Attribute: Attribute_Label: YMax Attribute_Definition: Maximum northing of the image footprint. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 2884030.0 Range_Domain_Maximum: 5333378.0 Attribute: Attribute_Label: LonMin Attribute_Definition: Minimum longitude (WGS84) of image footprint. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: -124.0922272 Range_Domain_Maximum: -69.95201111 Attribute: Attribute_Label: LonMax Attribute_Definition: Maximum longitude (WGS84) of image footprint. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: -124.0478924 Range_Domain_Maximum: -69.9405098 Attribute: Attribute_Label: LatMin Attribute_Definition: Minimum longitude (WGS84) of image footprint. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 25.98761753 Range_Domain_Maximum: 48.14810677 Attribute: Attribute_Label: LatMax Attribute_Definition: Maximum latitude (WGS84) of image footprint. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 26.06287667 Range_Domain_Maximum: 48.15232107 Attribute: Attribute_Label: CRS Attribute_Definition: The projected coordinate system description relating to XMin, XMax, YMin, YMax. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Unrepresentable_Domain: Projected coordinate system definition Attribute: Attribute_Label: px_m Attribute_Definition: Horizontal size of pixel in meters. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 0.15 Range_Domain_Maximum: 15 Attribute: Attribute_Label: ImageHeightPx Attribute_Definition: Number of pixels in horizontal dimension of height. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 31 Range_Domain_Maximum: 2481 Attribute: Attribute_Label: ImageWidthPx Attribute_Definition: Number of pixels in horizontal dimension of width. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 32 Range_Domain_Maximum: 2209 Attribute: Attribute_Label: ImageBands Attribute_Definition: Number of bands in the image. Attribute_Definition_Source: Producer defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 3 Range_Domain_Maximum: 3 Overview_Description: Entity_and_Attribute_Overview: Each image, image annotation, and labelled image is available as a single NPZ zipped file. NPZ files follow the following naming convention: {datasource}_{numberofclasses}_{threedigitdatasetversion}.zip, where {datasource} is the source of the original images (for example, NAIP, Landsat 8, Sentinel 2), {numberofclasses} is the number of classes used to annotate the images, and {threedigitdatasetversion} is the three digit code corresponding to the dataset version (in other words, 001 is version 1). Each zipped folder contains a collection of NPZ format files, each of which corresponds to an induvial image. An individual NPZ file is named after the image that it represents and contains (1) a CSV file with metadata information for every image and (2) a collection of the following NPY files: orig_image.npy (original input image unedited), image.npy (original input image after color balancing and normalization), classes.npy (list of classes annotated and present in the labelled image), doodles.npy (integer image of all image annotations), color_doodles.npy (color image of doodles.npy), label.npy (labelled image created from the classes present in the annotations), and settings.npy (annotation and machine learning settings used to generate the labelled image from annotations). All NPZ files can be extracted using the utilities available in Doodler (Buscombe, 2022; https://doi.org/10.5066/P9YVHL23). Entity_and_Attribute_Detail_Citation: The entity and attribute information was generated by the individual and/or agency identified as the originator of the data set. Please review the rest of the metadata record for additional details and information. Distribution_Information: Distributor: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey - CMGDS 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 Resource_Description: Images are provided in NPZ format. Each NPZ file corresponds to a single image that has been annotated/labelled and classified/segmented. The NPZ file names consist of the {image_source}_{number_of_classes}_{data_release_version_number}, delimited by underscores. The first element {image_source} represents the original source of the image (for example, Landsat 8 would be “L8”, Sentinel 2 would be “S2”), the second element {number_of_classes} represents the number of classes used during labelling (for example, “6 classes”, “11classes”, and The third element {data_release_version_number} represents the data release version that the image is part of (for example, all datasets for version 1 will have “001” as the third part of the NPZ filename). Each NPZ file contains at least seven (7) different NPY files: (1) orig_image.npy (original input image unedited), (2) image.npy (original input image after color balancing and normalization), (3) classes.npy (list of classes annotated and present in the labelled image), (4) doodles.npy (integer image of all image annotations), (5) color_doodles.npy (color image of doodles.npy), (6) label.npy (labelled image created from the classes present in the annotations), and (7) settings.npy (annotation and machine learning settings used to generate the labelled image from annotations). Some NPZ files may contain one or more additional sets of seven files with one or more zeros appended to the beginning of the NPY file names. These additional files are grouped by the number of zeros preceding the regular files described above and represent previous attempts at annotation and classification/segmentation for that image. For example, all NPY files with one zero appended to the beginning of the NPY file names represent the first attempt, all NPY files with two zeros appended to the beginning of the NPY file names represent the second attempt, etc. A merged CSV file (CoastTrain_imagery_details.csv) contains detailed information on the complete imagery collection. Distribution_Liability: Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. Standard_Order_Process: Digital_Form: Digital_Transfer_Information: Format_Name: comma-delimited text File_Decompression_Technique: none Digital_Transfer_Option: Online_Option: Computer_Contact_Information: Network_Address: Network_Resource_Name: https://doi.org/10.5066/P91NP87I Access_Instructions: CSV files can be downloaded using the Network_Resource_Name link then scrolling down to the Land Cover Data section. Digital_Form: Digital_Transfer_Information: Format_Name: NPY File_Decompression_Technique: Each ZIP file contains multiple NPZ files. Individual NPZ files can be unzipped and all NPY files converted to readable raster formats by using utility scripts associated with Doodler (Buscombe, 2022; https://doi.org/10.5066/P9YVHL23). NPZ files were compressed using deflate compression. Digital_Transfer_Option: Online_Option: Computer_Contact_Information: Network_Address: Network_Resource_Name: https://doi.org/10.5066/P91NP87I Access_Instructions: Imagery data can be downloaded using the Network_Resource_Name link then scrolling down to the Land Cover Data section. Fees: None. Technical_Prerequisites: These data can be viewed with Doodler software (Buscombe, 2022; https://doi.org/10.5066/P9YVHL23). Metadata_Reference_Information: Metadata_Date: 20220504 Metadata_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 Metadata_Standard_Name: Content Standard for Digital Geospatial Metadata Metadata_Standard_Version: FGDC-STD-001-1998