Metadata: Identification_Information: Citation: Citation_Information: Originator: Julie C. Bernier Publication_Date: 20251219 Title: Coastal Land-Cover Data Derived from Landsat Collection 2 Data, Northern Chandeleur Islands, Louisiana Edition: 1.0 Geospatial_Data_Presentation_Form: Raster and tabular digital data Larger_Work_Citation: Citation_Information: Originator: Julie C. Bernier Originator: Breanna N. Williams Originator: Jennifer L. Miselis Publication_Date: 20210921 Title: Coastal Land-Cover and Feature Datasets Derived from Landsat Satellite Imagery, Northern Chandeleur Islands, Louisiana Edition: 2.0 Series_Information: Series_Name: U.S. Geological Survey data release Issue_Identification: doi:10.5066/P9HY3HOR Publication_Information: Publication_Place: St. Petersburg, Florida Publisher: U.S. Geological Survey - St. Petersburg Coastal and Marine Science Center Online_Linkage: https://doi.org/10.5066/P9HY3HOR Description: Abstract: This data release serves as an archive of coastal land-cover and feature datasets derived from Landsat satellite imagery at the northern Chandeleur Islands, Louisiana. To minimize effects of tidal water-level variations, only images that were collected within 2 hours of predicted low tide or that were collected on a rising tide with predicted water levels less than mean sea level at time of image acquisition were analyzed. Water, bare earth (sand), vegetated, and intertidal land-cover classes were mapped from Hewes Point to Palos Island using successive thresholding and masking of the modified normalized difference water index (mNDWI), the normalized difference bare land index (NBLI), and the normalized difference vegetation index (NDVI). Vector shoreline, sand, and vegetated feature extents were extracted for each image by contouring the spectral indices using the calculated threshold values. Barrier platform, beach, and vegetated widths were calculated from the intersection of the shoreline, sand, and vegetated vectors with transects spaced 300 meters (m) (10 pixels) apart alongshore. These data can be used to evaluate decadal-scale barrier landscape changes (Bernier and others, 2021). Purpose: Dissemination of thematic raster data representing land-cover classes derived from 13 Landsat 6 and Landsat 9 Operational Land Imager (OLI) image datasets from the northern Chandeleur Islands, Louisiana. Supplemental_Information: Information about the Landsat missions, sensor and band specifications, data products (including Collection 1 versus Collection 2 processing), and data access can be found at https://www.usgs.gov/landsat-missions. Time_Period_of_Content: Time_Period_Information: Multiple_Dates/Times: Single_Date/Time: Calendar_Date: 20171222 Single_Date/Time: Calendar_Date: 20190110 Single_Date/Time: Calendar_Date: 20190416 Single_Date/Time: Calendar_Date: 20200402 Single_Date/Time: Calendar_Date: 20210115 Single_Date/Time: Calendar_Date: 20210405 Single_Date/Time: Calendar_Date: 20211201 Single_Date/Time: Calendar_Date: 20220331 Single_Date/Time: Calendar_Date: 20230105 Single_Date/Time: Calendar_Date: 20230206 Single_Date/Time: Calendar_Date: 20230214 Single_Date/Time: Calendar_Date: 20230222 Single_Date/Time: Calendar_Date: 20230403 Single_Date/Time: Calendar_Date: 20230918 Single_Date/Time: Calendar_Date: 20231028 Single_Date/Time: Calendar_Date: 20231231 Single_Date/Time: Calendar_Date: 20240225 Single_Date/Time: Calendar_Date: 20240405 Single_Date/Time: Calendar_Date: 20241115 Currentness_Reference: ground condition Status: Progress: Complete Maintenance_and_Update_Frequency: None planned Spatial_Domain: Bounding_Coordinates: West_Bounding_Coordinate: -88.932712 East_Bounding_Coordinate: -88.742256 North_Bounding_Coordinate: 30.097824 South_Bounding_Coordinate: 29.720211 Keywords: Theme: Theme_Keyword_Thesaurus: USGS Metadata Identifier Theme_Keyword: USGS:2c5f9544-1eda-49ed-969b-9ab9a8b0ac98 Theme: Theme_Keyword_Thesaurus: ISO 19115 Topic Category Theme_Keyword: geoscientificInformation Theme_Keyword: imageryBaseMapsEarthCover Theme: Theme_Keyword_Thesaurus: USGS Thesaurus Theme_Keyword: geomorphology Theme_Keyword: geospatial datasets Theme_Keyword: image collections Theme_Keyword: multispectral imaging Theme_Keyword: coastal ecosystems Theme_Keyword: land use and land cover Theme: Theme_Keyword_Thesaurus: None Theme_Keyword: Landsat Theme_Keyword: barrier island Theme_Keyword: spectral indices Theme_Keyword: Otsu thresholding Theme_Keyword: land cover Theme_Keyword: water Theme_Keyword: bare earth Theme_Keyword: sand Theme_Keyword: vegetated Theme_Keyword: intertidal Place: Place_Keyword_Thesaurus: Geographic Names Information System (GNIS) Place_Keyword: State of Louisiana Place_Keyword: Chandeleur Islands Place_Keyword: Gulf of America Place: Place_Keyword_Thesaurus: None Place_Keyword: Gulf of Mexico Access_Constraints: No access constraints. Please see 'Distribution Information' for details. Use_Constraints: These data are marked with a Creative Commons CC0 1.0 Universal License. These data are in the public domain and do not have any use constraints. Users are advised to read the dataset's metadata thoroughly to understand appropriate use and data limitations. Point_of_Contact: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey Contact_Person: Julie C. Bernier Contact_Position: Geologist Contact_Address: Address_Type: Mailing and physical Address: 600 4th Street South City: St. Petersburg State_or_Province: FL Postal_Code: 33701 Country: USA Contact_Voice_Telephone: 727-502-8000 Contact_Electronic_Mail_Address: jbernier@usgs.gov Data_Set_Credit: U.S. Geological Survey, Coastal and Marine Hazards and Resources Program, St. Petersburg Coastal and Marine Science Center (SPCMSC). Funding and (or) support for this analysis were provided as part of the Extending Government Funding and Delivering Emergency Assistance Act (Public Law 117-43), enacted on September 30, 2021. This document was improved by scientific and metadata reviews by Sydney Nick and Tess Rivenbark-Terrano (USGS SPCMSC). Native_Data_Set_Environment: Microsoft Windows 11 Enterprise Version 23H2 (Build 2263.6199); Esri ArcGIS Pro 3.3.2; ERDAS IMAGINE 2023 Version 16.8.0 Build 2100; MATLAB R2025a Update 1 (25.1.0.2973910) Cross_Reference: Citation_Information: Originator: Julie C. Bernier Originator: Jennifer L. Miselis Originator: Nathaniel G. Plant Publication_Date: 20210921 Title: Satellite-Derived Barrier Response and Recovery Following Natural and Anthropogenic Perturbations, Northern Chandeleur Islands, Louisiana Series_Information: Series_Name: Remote Sensing Issue_Identification: 13(18), 3778; Special Issue "New Insights into Ecosystem Monitoring Using Geospatial Techniques" Online_Linkage: https://doi.org/10.3390/rs13183779 Cross_Reference: Citation_Information: Originator: Hanqiu Xu Publication_Date: 2006 Title: Modification of Normalised Difference Water Index (NDWI) to Enhance Open Water Features in Remotely Sensed Imagery Series_Information: Series_Name: International Journal of Remote Sensing Issue_Identification: Volume 27, Issue 14 Other_Citation_Details: Pages 3025-3033 Online_Linkage: https://doi.org/10.1080/01431160600589179 Cross_Reference: Citation_Information: Originator: Hui Li Originator: Cuizhen Wang Originator: Cheng Zhong Originator: Aijun Su Originator: Chengren Xiong Originator: Jinge Wang Originator: Junqi Liu Publication_Date: 20170307 Title: Mapping Urban Bare Land Automatically from Landsat Imagery with a Simple Index Series_Information: Series_Name: Remote Sensing Issue_Identification: 9(3), 249 Online_Linkage: https://doi.org/10.3390/rs9030249 Cross_Reference: Citation_Information: Originator: Nobuyuki Otsu Publication_Date: 197901 Title: A Threshold Selection Method from Gray-Level Histograms Series_Information: Series_Name: IEEE Transactions on Systems, Man and Cybernetics Issue_Identification: Volume 9, Issue 1 Other_Citation_Details: Pages 62-66 Online_Linkage: https://doi.org/10.1109/TSMC.1979.4310076 Data_Quality_Information: Attribute_Accuracy: Attribute_Accuracy_Report: Using the workflow described below to map land cover at the northern Chandeleur Islands from Landsat Collection 1 products acquired between 1984 and 2019, Bernier and others (2021) reported classification accuracies (>=70%) that were comparable to accuracies reported for the National Land Cover Database (NLCD). Logical_Consistency_Report: For each image-acquisition date, Landsat Collection 2 Analysis Ready Data (ARD) and Level-2 science products were downloaded from the USGS EarthExplorer (https://earthexplorer.usgs.gov/) and USGS Earth Resources Observation and Science (EROS) Center Science Processing Architecture (ESPA) On Demand Interface (https://espa.cr.usgs.gov/), respectively. Completeness_Report: 63 Landsat OLI images (Worldwide Reference System 2 [WRS-2] path 21 row 39) acquired between December 2022 and November 2024 were identified that were cloud free in the study area. To minimize the effects of water-level variations on land-cover classification, only images that were collected within 2 hours of predicted low tide or were collected on a rising tide with predicted water levels at time of acquisition less than mean sea level (National Ocean Service [NOS] Center for Operational Oceanographic Products and Services [CO-OPS] station 8760172, Chandeleur Light, LA) were analyzed. The resulting dataset consisted of 13 Landsat 8 and 6 Landsat 9 OLI images. Positional_Accuracy: Horizontal_Positional_Accuracy: Horizontal_Positional_Accuracy_Report: Geodetic accuracy of Landsat data products depend on the accuracy, number, and distribution of the ground control points and the resolution of the digital elevation model (DEM) used. All ARD and Level-2 science products are derived from Landsat Level-1 Precision and Terrain (L1TP) corrected data and meet pre-defined image-to-image georegistration tolerances of <= 12-meter radial root mean square error (RMSE). Lineage: Process_Step: Process_Description: For each image acquisition date, Landsat Collection 2 ARD top-of-atmosphere (TOA) reflectance (reflective bands) and TOA brightness temperature (BT; thermal infrared [TIR] bands) were downloaded from EarthExplorer (https://earthexplorer.usgs.gov/) and Level 2 surface reflectance-derived NDVI images were downloaded from the EROS ESPA On Demand Interface (https://espa.cr.usgs.gov/). Process_Date: 2025 Process_Contact: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey Contact_Person: Julie C. Bernier Contact_Position: Geologist Contact_Address: Address_Type: Mailing and physical Address: 600 4th Street South City: St. Petersburg State_or_Province: FL Postal_Code: 33701 Country: USA Contact_Voice_Telephone: 727-502-8000 Contact_Electronic_Mail_Address: jbernier@usgs.gov Process_Step: Process_Description: All images were batch-processed using Spatial Model Editor in ERDAS IMAGINE. The TOA and BT bands were stacked to create 9-band multispectral images and clipped to the study-area extent. From these composite images, two additional spectral indices, mNDWI (Xu, 2006) and NBLI (Li and others, 2017), were calculated. Process_Date: 2025 Process_Contact: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey Contact_Person: Julie C. Bernier Contact_Position: Geologist Contact_Address: Address_Type: Mailing and physical Address: 600 4th Street South City: St. Petersburg State_or_Province: FL Postal_Code: 33701 Country: USA Contact_Voice_Telephone: 727-502-8000 Contact_Electronic_Mail_Address: jbernier@usgs.gov Process_Step: Process_Description: Land-cover classification was performed using progressive, automatic thresholding of spectral indices. First, Otsu's method (Otsu, 1979) for automatic histogram thresholding was applied to mNDWI images to create a binary land-water raster for each image acquisition date. Second, water area was masked from NBLI and NDVI images, and Otsu's method was applied to the masked images to create binary bare earth-"unclassed" and vegetated-"unclassed" rasters, respectively. Because thresholding was applied to masked NBLI and NDVI simultaneously, some pixels along the sand-vegetation boundary were classed as both sand and vegetated in this step. These pixels were mapped as sand using the following rule: if NBLI = sand and NDVI = vegetated, then final = sand (based on visual analysis during workflow development) (Bernier and others, 2021). Next, water, bare earth (sand), and vegetated areas were masked from mNDWI images, and Otsu's method was applied to the masked mNDWI image to separate the "submerged" and "emergent" intertidal areas. Finally, the binary land-cover images were converted to thematic rasters, merged, and single-pixel "clumps" were removed using a 3x3 majority filter to create a final land-cover raster dataset. The resulting land-cover rasters use the naming convention YYYYMMDD_LC##_nchan_islp_lcr_ce.img, where YYYYMMDD denotes the image-acquisition date (4-digit year, 2-digit month, 2-digit day) and LC## denotes Landsat 8 (LC08) or Landsat 9 (LC09) image source. All steps were batch-processed using the Image Processing toolbox in MATLAB (Otsu thresholding and binary image creation) or Spatial Model Editor in ERDAS IMAGINE (spectral index masking and generation of classed land-cover rasters). Process_Date: 2025 Source_Produced_Citation_Abbreviation: YYYYMMDD_LC08_nchan_islp_lcr_ce.img Source_Produced_Citation_Abbreviation: YYYYMMDD_LC09_nchan_islp_lcr_ce.img Process_Contact: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey Contact_Person: Julie C. Bernier Contact_Position: Geologist Contact_Address: Address_Type: Mailing and physical Address: 600 4th Street South City: St. Petersburg State_or_Province: FL Postal_Code: 33701 Country: USA Contact_Voice_Telephone: 727-502-8000 Contact_Electronic_Mail_Address: jbernier@usgs.gov Process_Step: Process_Description: For 5 datasets, thresholding resulted in significant misclassification of back-barrier seagrass beds as vegetated. These were identified based on visual comparison with ancillary datasets and vegetation persistence maps, and misclassed extents were manually cleaned from the final datasets by selecting and re-classing the pixels in ERDAS IMAGINE (Bernier and others, 2021). The cleaned land-cover rasters use the naming convention YYYYMMDD_LC##_nchan_islp_lcr_ce_cl.img, where YYYYMMDD denotes the image-acquisition date (4-digit year, 2-digit month, 2-digit day) and LC## denotes Landsat 8 (LC08) or Landsat 9 (LC09) image source. Process_Date: 2025 Source_Produced_Citation_Abbreviation: YYYYMMDD_LC08_nchan_islp_lcr_ce_cl.img Source_Produced_Citation_Abbreviation: YYYYMMDD_LC09_nchan_islp_lcr_ce_cl.img Process_Contact: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey Contact_Person: Julie C. Bernier Contact_Position: Geologist Contact_Address: Address_Type: Mailing and physical Address: 600 4th Street South City: St. Petersburg State_or_Province: FL Postal_Code: 33701 Country: USA Contact_Voice_Telephone: 727-502-8000 Contact_Electronic_Mail_Address: jbernier@usgs.gov Process_Step: Process_Description: The histogram (pixel count) for each raster was exported to a text file using Spatial Model Editor in ERDAS IMAGINE, merged into a single file in MATLAB, and used to calculate the total area for each land-cover type based on the relationship 1 pixel = 30 meters x 30 meters. Process_Date: 2025 Source_Produced_Citation_Abbreviation: nchan_coll2_landcover_2017_2024.csv Process_Contact: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey Contact_Person: Julie C. Bernier Contact_Position: Geologist Contact_Address: Address_Type: Mailing and physical Address: 600 4th Street South City: St. Petersburg State_or_Province: FL Postal_Code: 33701 Country: USA Contact_Voice_Telephone: 727-502-8000 Contact_Electronic_Mail_Address: jbernier@usgs.gov Spatial_Data_Organization_Information: Direct_Spatial_Reference_Method: Raster Raster_Object_Information: Raster_Object_Type: Grid cell Row_Count: 591 Column_Count: 1386 Vertical_Count: 1 Spatial_Reference_Information: Horizontal_Coordinate_System_Definition: Planar: Grid_Coordinate_System: Grid_Coordinate_System_Name: Universal Transverse Mercator Universal_Transverse_Mercator: UTM_Zone_Number: 16 Transverse_Mercator: Scale_Factor_at_Central_Meridian: 0.9996 Longitude_of_Central_Meridian: -87.0 Latitude_of_Projection_Origin: 0 False_Easting: 500000.0 False_Northing: 0.0 Planar_Coordinate_Information: Planar_Coordinate_Encoding_Method: row and column Coordinate_Representation: Abscissa_Resolution: 30 Ordinate_Resolution: 30 Planar_Distance_Units: Meters Geodetic_Model: Horizontal_Datum_Name: D WGS 1984 Ellipsoid_Name: WGS 1984 Semi-major_Axis: 6378137.0 Denominator_of_Flattening_Ratio: 298.257223563 Entity_and_Attribute_Information: Detailed_Description: Entity_Type: Entity_Type_Label: nchan_coll2_landcover.zip Entity_Type_Definition: Zip archive containing thematic land-cover raster datasets in ERDAS IMAGINE (.img) format. Filenames use the convention YYYYMMDD_LC##_nchan_islp_lcr_ce(_cl).img as described above. Entity_Type_Definition_Source: USGS Attribute: Attribute_Label: OID Attribute_Definition: Internal feature number Attribute_Definition_Source: Esri Attribute_Domain_Values: Unrepresentable_Domain: Sequential unique whole numbers that are automatically generated Attribute: Attribute_Label: Value Attribute_Definition: Land-cover class number Attribute_Definition_Source: USGS Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: 0 Enumerated_Domain_Value_Definition: Out - pixels outside of analysis extent Enumerated_Domain_Value_Definition_Source: USGS Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: 1 Enumerated_Domain_Value_Definition: Water - pixels classified as water Enumerated_Domain_Value_Definition_Source: USGS Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: 3 Enumerated_Domain_Value_Definition: Bare earth (sand) - pixels classified as bare earth (sand) land cover Enumerated_Domain_Value_Definition_Source: USGS Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: 4 Enumerated_Domain_Value_Definition: Vegetated - pixels classified as vegetated land cover Enumerated_Domain_Value_Definition_Source: USGS Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: 11 Enumerated_Domain_Value_Definition: Intertidal (submerged) - pixels classified as submerged intertidal areas Enumerated_Domain_Value_Definition_Source: USGS Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: 12 Enumerated_Domain_Value_Definition: Intertidal (emergent) - pixels classified as emergent intertidal areas Enumerated_Domain_Value_Definition_Source: USGS Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: 14 Enumerated_Domain_Value_Definition: Intertidal (cleaned) - pixels re-classified as intertidal (submerged) after manual cleaning of misclassed seagrass extents Enumerated_Domain_Value_Definition_Source: USGS Attribute_Domain_Values: Unrepresentable_Domain: Values of 2, 5 through 10, 13, and 15 through 255 are not used to define a land-cover class but are stored by default in the 8-bit raster attribute table Attribute: Attribute_Label: Count Attribute_Definition: Number of pixels per land-cover class Attribute_Definition_Source: Hexagon Geospatial Attribute_Domain_Values: Unrepresentable_Domain: Number of pixels per land-cover class Attribute: Attribute_Label: Red Attribute_Definition: Red value for RGB color map Attribute_Definition_Source: Hexagon Geospatial Attribute_Domain_Values: Unrepresentable_Domain: Red value for RGB colormap Attribute: Attribute_Label: Green Attribute_Definition: Green value for RGB color map Attribute_Definition_Source: Hexagon Geospatial Attribute_Domain_Values: Unrepresentable_Domain: Green value for RGB colormap Attribute: Attribute_Label: Blue Attribute_Definition: Blue value for RGB color map Attribute_Definition_Source: Hexagon Geospatial Attribute_Domain_Values: Unrepresentable_Domain: Blue value for RGB colormap Attribute: Attribute_Label: Opacity Attribute_Definition: Opacity (on or off) of land-cover class. Values in the attribute table depend on the software used to view the data but are most commonly 0 (off) and 1 or 255 (on). Attribute_Definition_Source: Hexagon Geospatial Attribute_Domain_Values: Unrepresentable_Domain: Opacity (on or off) of land-cover class Attribute: Attribute_Label: Class_Name Attribute_Definition: Land-cover type Attribute_Definition_Source: USGS Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: Out Enumerated_Domain_Value_Definition: Pixels outside of analysis extent Enumerated_Domain_Value_Definition_Source: USGS Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: Water Enumerated_Domain_Value_Definition: Pixels classified as water Enumerated_Domain_Value_Definition_Source: USGS Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: Bare earth (sand) Enumerated_Domain_Value_Definition: Pixels classified as bare earth (sand) land cover Enumerated_Domain_Value_Definition_Source: USGS Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: Vegetated Enumerated_Domain_Value_Definition: Pixels classified as vegetated land cover Enumerated_Domain_Value_Definition_Source: USGS Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: Intertidal (submerged) Enumerated_Domain_Value_Definition: Pixels classified as submerged intertidal areas Enumerated_Domain_Value_Definition_Source: USGS Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: Intertidal (emergent) Enumerated_Domain_Value_Definition: Pixels classified as emergent intertidal areas Enumerated_Domain_Value_Definition_Source: USGS Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: Intertidal (cleaned) Enumerated_Domain_Value_Definition: Pixels re-classified as intertidal after manual cleaning of misclassed seagrass extents Enumerated_Domain_Value_Definition_Source: USGS Detailed_Description: Entity_Type: Entity_Type_Label: nchan_coll2_landcover_2017_2024.csv Entity_Type_Definition: Comma-separated values file detailing land-cover pixel count and total area for each image-acquisition date, contained in nchan_coll2_landcover.zip Entity_Type_Definition_Source: USGS Attribute: Attribute_Label: FileName Attribute_Definition: File name of classed land-cover raster Attribute_Definition_Source: USGS Attribute_Domain_Values: Unrepresentable_Domain: Character string; YYYYMMDD_LC##_nchan_islp_lcr_ce(_cl).img Attribute: Attribute_Label: ImageDate Attribute_Definition: Source image-acquisition date Attribute_Definition_Source: USGS Attribute_Domain_Values: Unrepresentable_Domain: Source image acquisition date written as DD-MON-YYYY (2-digit day, 3-letter month, 4-digit year) Attribute: Attribute_Label: DecYear Attribute_Definition: Source image-acquisition date, in decimal years Attribute_Definition_Source: USGS Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 2017.975 Range_Domain_Maximum: 2024.873 Attribute_Units_of_Measure: Decimal year Attribute_Measurement_Resolution: 0.001 Attribute: Attribute_Label: SceneID Attribute_Definition: Landsat Collection 2, Level 2 source data identifier downloaded from EROS ESPA Attribute_Definition_Source: USGS Attribute_Domain_Values: Unrepresentable_Domain: Landsat source imagery data identifier Attribute: Attribute_Label: Water_count Attribute_Definition: Number of pixels classed as water Attribute_Definition_Source: USGS Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 124105 Range_Domain_Maximum: 137091 Attribute_Units_of_Measure: Pixels Attribute_Measurement_Resolution: 1 Attribute: Attribute_Label: BareEarth_count Attribute_Definition: Number of pixels classed as bare earth (sand) Attribute_Definition_Source: USGS Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 1350 Range_Domain_Maximum: 3721 Attribute_Units_of_Measure: Pixels Attribute_Measurement_Resolution: 1 Attribute: Attribute_Label: Vegetated_count Attribute_Definition: Number of pixels classed as vegetated Attribute_Definition_Source: USGS Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 4220 Range_Domain_Maximum: 8181 Attribute_Units_of_Measure: Pixels Attribute_Measurement_Resolution: 1 Attribute: Attribute_Label: IntertidalSub_count Attribute_Definition: Number of pixels classed as intertidal (submerged) Attribute_Definition_Source: USGS Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 1941 Range_Domain_Maximum: 8827 Attribute_Units_of_Measure: Pixels Attribute_Measurement_Resolution: 1 Attribute: Attribute_Label: IntertidalEmrg_count Attribute_Definition: Number of pixels classed as intertidal (emergent) Attribute_Definition_Source: USGS Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 1363 Range_Domain_Maximum: 6324 Attribute_Units_of_Measure: Pixels Attribute_Measurement_Resolution: 1 Attribute: Attribute_Label: IntertidalRcl_count Attribute_Definition: Number of pixels re-classed as intertidal (cleaned) Attribute_Definition_Source: USGS Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 0 Range_Domain_Maximum: 264 Attribute_Units_of_Measure: Pixels Attribute_Measurement_Resolution: 1 Attribute: Attribute_Label: Water_m2 Attribute_Definition: Area classed as water, in square meters Attribute_Definition_Source: USGS Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 111694500 Range_Domain_Maximum: 123381900 Attribute_Units_of_Measure: Square meters Attribute_Measurement_Resolution: 1 Attribute: Attribute_Label: BareEarth_m2 Attribute_Definition: Area classed as bare earth (sand), in square meters Attribute_Definition_Source: USGS Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 1215000 Range_Domain_Maximum: 3348900 Attribute_Units_of_Measure: Square meters Attribute_Measurement_Resolution: 1 Attribute: Attribute_Label: Vegetated_m2 Attribute_Definition: Area classed as vegetated, in square meters Attribute_Definition_Source: USGS Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 3798000 Range_Domain_Maximum: 7362900 Attribute_Units_of_Measure: Square meters Attribute_Measurement_Resolution: 1 Attribute: Attribute_Label: IntertidalSub_m2 Attribute_Definition: Area classed as intertidal (submerged), in square meters Attribute_Definition_Source: USGS Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 1746900 Range_Domain_Maximum: 7944300 Attribute_Units_of_Measure: Square meters Attribute_Measurement_Resolution: 1 Attribute: Attribute_Label: IntertidalEmrg_m2 Attribute_Definition: Area classed as intertidal (emergent), in square meters Attribute_Definition_Source: USGS Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 1226700 Range_Domain_Maximum: 5691600 Attribute_Units_of_Measure: Square meters Attribute_Measurement_Resolution: 1 Attribute: Attribute_Label: IntertidalRcl_m2 Attribute_Definition: Area classed as intertidal (reclassed), in square meters Attribute_Definition_Source: USGS Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 0 Range_Domain_Maximum: 237600 Attribute_Units_of_Measure: Square meters Attribute_Measurement_Resolution: 1 Distribution_Information: Distributor: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center Contact_Person: USGS SPCMSC Data Management Contact_Address: Address_Type: Mailing and physical Address: 600 4th Street South City: St. Petersburg State_or_Province: FL Postal_Code: 33701 Country: USA Contact_Voice_Telephone: 727-502-8000 Contact_Electronic_Mail_Address: gs-g-spcmsc_data_inquiries@usgs.gov Resource_Description: YYYYMMDD_LC08_nchan_islp_lcr_ce.img, YYYYMMDD_LC09_nchan_islp_lcr_ce.img, YYYYMMDD_LC08_nchan_islp_lcr_ce_cl.img, YYYYMMDD_LC09_nchan_islp_lcr_ce_cl.img, nchan_coll2_landcover_2017_2024.csv 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 for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Standard_Order_Process: Digital_Form: Digital_Transfer_Information: Format_Name: ERDAS IMAGINE, comma-delimited text Format_Information_Content: Download file contains ERDAS IMAGINE (.img) land-cover rasters and comma-separated values (.csv) text files. Digital_Transfer_Option: Online_Option: Computer_Contact_Information: Network_Address: Network_Resource_Name: https://coastal.er.usgs.gov/data-release/doi-P9HY3HOR/data/nchan_coll2_landcover.zip Fees: None Technical_Prerequisites: Raster datasets were created using ERDAS IMAGINE 2023 and can be opened using ERDAS IMAGINE 2020 or Esri ArcGIS Pro version 3.1 or higher; these data may also be viewed using free Google Earth Pro or QGIS software. Metadata_Reference_Information: Metadata_Date: 20251219 Metadata_Contact: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center Contact_Person: USGS SPCMSC Data Management Contact_Address: Address_Type: Mailing and physical Address: 600 4th Street South City: St. Petersburg State_or_Province: FL Postal_Code: 33701 Country: USA Contact_Voice_Telephone: 727-502-8000 Contact_Electronic_Mail_Address: gs-g-spcmsc_data_inquiries@usgs.gov Metadata_Standard_Name: Content Standard for Digital Geospatial Metadata Metadata_Standard_Version: FGDC-STD-001-1998