Coastal Features Extracted from Landsat Satellite Imagery, Northern Chandeleur Islands, Louisiana, 1984-2019

Metadata also available as - [Outline] - [Parseable text] - [XML]

Frequently anticipated questions:

What does this data set describe?

Title:
Coastal Features Extracted from Landsat Satellite Imagery, Northern Chandeleur Islands, Louisiana, 1984-2019
Abstract:
The data release (Bernier, 2021) associated with this metadata record serves as an archive of coastal land-cover and feature datasets derived from Landsat satellite imagery at the northern Chandeleur Islands, Louisiana. To minimize the effects of tidal water-level variations, 75 cloud-free, low-water images acquired between 1984 and 2019 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. The geographic information system (GIS) data files with accompanying formal Federal Geographic Data Committee (FGDC) metadata can be downloaded from https://doi.org/10.5066/P9HY3HOR.
Supplemental_Information:
Information about the Landsat missions, sensor and band specifications, data products, and data access can be found at https://www.usgs.gov/core-science-systems/nli/landsat. The land-cover and feature-extent datasets published in Bernier (2021) support analyses presented by Bernier and others (2021).
  1. How might this data set be cited?
    Bernier, Julie C., 20210921, Coastal Features Extracted from Landsat Satellite Imagery, Northern Chandeleur Islands, Louisiana, 1984-2019:.

    This is part of the following larger work.

    Bernier, Julie C., 20210921, Coastal Land-Cover and Feature Datasets Derived from Landsat Satellite Imagery, Northern Chandeleur Islands, Louisiana: U.S. Geological Survey data release doi:10.5066/P9HY3HOR, U.S. Geological Survey - St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida.

    Online Links:

  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -88.916003
    East_Bounding_Coordinate: -88.808818
    North_Bounding_Coordinate: 30.054845
    South_Bounding_Coordinate: 29.717502
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
    Calendar_Date: 25-Mar-1984
    Currentness_Reference:
    Ground condition
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: Vector and tabular digital data
  6. How does the data set represent geographic features?
    1. How are geographic features stored in the data set?
      This is a Vector data set.
    2. What coordinate system is used to represent geographic features?
      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 coordinates are encoded using Coordinate pair
      Abscissae (x-coordinates) are specified to the nearest 0.6096
      Ordinates (y-coordinates) are specified to the nearest 0.6096
      Planar coordinates are specified in Meters
      The horizontal datum used is D WGS 1984.
      The ellipsoid used is WGS 1984.
      The semi-major axis of the ellipsoid used is 6378137.0.
      The flattening of the ellipsoid used is 1/298.257223563.
  7. How does the data set describe geographic features?
    nchan_features.zip
    Zip archive containing vector shoreline (nchan_shrln.shp), sand (nchan_sandext.shp), and vegetated (nchan_vegext.shp) feature extents from each of 75 Landsat image-acquisition dates in Esri shapefile (.shp) format. (Source: USGS)
    FID
    Internal feature number (Source: Esri) Sequential unique whole numbers that are automatically generated
    Shape
    Feature geometry (Source: Esri) Coordinates defining the features
    CONTOUR
    Contour value used to delineate features based on automatic thresholding of mNDWI (shoreline), NBLI (sand), and NDVI (vegetated) indices. (Source: Esri) Spectral index values range from -1 to 1 but were converted to signed integers ranging from -10000 to 10000 during processing. The units are dimensionless.
    IMG_DATE
    Image acquisition date (Source: USGS) Source image acquisition date written as DD-MON-YYYY (2-digit day, 3-letter month, 4-digit year)
    DATE_TIME
    Image acquisition date and time (Source: USGS) Source image acquisition date and time written as MM/DD/YYYY 00:00:00 PM
    ambur_perp_transects_300m.shp
    Cross-shore transect locations in Esri shapefile (.shp) format (Source: USGS)
    FID
    Internal feature number (Source: Esri) Sequential unique whole numbers that are automatically generated
    Shape
    Feature geometry (Source: Esri) Coordinates defining the features
    ID
    Baseline identifier (Source: AMBUR) AMBUR-generated baseline identifier
    Transect
    Transect number (Source: AMBUR)
    Range of values
    Minimum:1
    Maximum:132
    Units:Dimensionless
    Resolution:1
    TranSpace
    Transect spacing, in meters (Source: AMBUR)
    Range of values
    Minimum:300
    Maximum:300
    Units:Meters
    Resolution:1
    TranDist
    Transect length, in meters (Source: AMBUR)
    Range of values
    Minimum:3500
    Maximum:4500
    Units:Meters
    Resolution:1
    Location
    Location identifier (optional) (Source: AMBUR) AMBUR-generated identifier
    MaxBNum
    Maximum number of baselines (if applicable) (Source: AMBUR) Used to assign the order which transects are drawn if multiple baselines are present
    BaseOrder
    Baseline order (if applicable) (Source: AMBUR) Used if more than one baseline is present
    OFFshore
    Indicates baseline position (offshore or onshore) (Source: AMBUR)
    ValueDefinition
    1Baseline is located offshore of vector shorelines
    CastDir
    Indicates direction (left or right) transects are cast from baseline (Source: AMBUR)
    ValueDefinition
    -1Transects are cast left of baseline position
    BASE_LOC
    Location identifier (optional) (Source: AMBUR) AMBUR-generated identifier
    StartX
    UTM coordinates of transect starting x position (Source: AMBUR)
    Range of values
    Minimum:319282.942095
    Maximum:325039.250404
    Units:Meters
    Resolution:0.000001
    StartY
    UTM coordinates of transect starting y position (Source: AMBUR)
    Range of values
    Minimum:3289009.250058
    Maximum:3326250.763767
    Units:Meters
    Resolution:0.000001
    EndX
    UTM coordinates of transect ending x position (Source: AMBUR)
    Range of values
    Minimum:316175.515168
    Maximum:321539.969229
    Units:Meters
    Resolution:0.000001
    EndY
    UTM coordinates of transect ending y position (Source: AMBUR)
    Range of values
    Minimum:3290619.808313
    Maximum:3323927.400654
    Units:Meters
    Resolution:0.000001
    Azimuth
    Azimuth of transect cast (Source: AMBUR)
    Range of values
    Minimum:48.408288
    Maximum:117.397400
    Units:Meters
    Resolution:0.000001
    Creator
    AMBUR-generated descriptor (Source: AMBUR) AMBUR-generated descriptor
    nchan_featmetrics.csv
    Comma-separated values file detailing derived feature metrics for each of 75 Landsat image-acquisition dates (Source: USGS)
    IMG_DATE
    Image acquisition date (Source: USGS) Source image acquisition date written as DD-MON-YYYY
    Transect
    Transect number (Source: AMBUR)
    Range of values
    Minimum:1
    Maximum:132
    Units:Dimensionless
    Resolution:1
    SHRLN_min
    Distance in meters along transect from baseline to first intersection with shoreline vector. (Source: USGS)
    ValueDefinition
    NoDataFeature is not present along the transect.
    Range of values
    Minimum:308.653
    Maximum:4134.120
    Units:Meters
    Resolution:0.001
    SAND_min
    Distance in meters along transect from baseline to first intersection with sand extent vector. (Source: USGS)
    ValueDefinition
    NoDataFeature is not present along the transect.
    ExclFeature was excluded from dataset (see process step description for additional details).
    Range of values
    Minimum:328.031
    Maximum:4158.547
    Units:Meters
    Resolution:0.0010
    SAND_max
    Distance in meters along transect from baseline to last intersection with sand extent vector. (Source: USGS)
    ValueDefinition
    NoDataFeature is not present along the transect.
    ExclFeature was excluded from dataset (see process step description for additional details).
    Range of values
    Minimum:378.954
    Maximum:4276.354
    Units:Meters
    Resolution:0.001
    VEG_min
    Distance in meters along transect from baseline to first intersection with vegetated extent vector. (Source: USGS)
    ValueDefinition
    NoDataFeature is not present along the transect.
    ExclFeature was excluded from dataset (see process step description for additional details).
    Range of values
    Minimum:348.025
    Maximum:3584.820
    Units:Meters
    Resolution:0.001
    VEG_max
    Distance in meters along transect from baseline to last intersection with vegetated extent vector. (Source: USGS)
    ValueDefinition
    NoDataFeature is not present along the transect.
    ExclFeature was excluded from dataset (see process step description for additional details).
    Range of values
    Minimum:579.304
    Maximum:3675.872
    Units:Meters
    Resolution:0.001
    SHRLN_max
    Distance in meters along transect from baseline to last intersection with shoreline vector. (Source: USGS)
    ValueDefinition
    NoDataFeature is not present along the transect.
    ExclFeature was excluded from dataset (see process step description for additional details).
    Range of values
    Minimum:597.792
    Maximum:4337.832
    Units:Meters
    Resolution:0.001
    ISLP
    Width in meters of barrier-island platform (sea shoreline to back-barrier shoreline). (Source: USGS)
    ValueDefinition
    NoDataFeature is not present along the transect.
    ExclFeature was excluded from dataset (see process step description for additional details).
    Range of values
    Minimum:17.947
    Maximum:1782.744
    Units:Meters
    Resolution:0.001
    BEACH
    Width in meters of barrier-island beach (sand extent). (Source: USGS)
    ValueDefinition
    NoDataFeature is not present along the transect.
    ExclFeature was excluded from dataset (see process step description for additional details).
    Range of values
    Minimum:17.566
    Maximum:628.044
    Units:Meters
    Resolution:0.001
    VEG
    Width in meters of barrier-island vegetation (vegetated extent). (Source: USGS)
    ValueDefinition
    NoDataFeature is not present along the transect.
    ExclFeature was excluded from dataset (see process step description for additional details).
    Range of values
    Minimum:17.960
    Maximum:1499.363
    Units:Meters
    Resolution:0.001

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • Julie C. Bernier
  2. Who also contributed to the data set?
    U.S. Geological Survey, Coastal and Marine Hazards and Resources Program, St. Petersburg Coastal and Marine Science Center
  3. To whom should users address questions about the data?
    U.S. Geological Survey
    Attn: Julie C. Bernier
    Geologist
    600 4th Street South
    St. Petersburg, FL
    USA

    727-502-8000 (voice)
    jbernier@usgs.gov

Why was the data set created?

Dissemination of vector data representing shoreline, sand, and vegetated feature extents derived from 52 Landsat 5 Thematic Mapper (TM), 10 Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and 13 Landsat 8 Operational Land Imager (OLI) image datasets from the northern Chandeleur Islands, Louisiana.

How was the data set created?

  1. From what previous works were the data drawn?
  2. How were the data generated, processed, and modified?
    Date: 2019 (process 1 of 5)
    For each image acquisition date, top-of-atmosphere (TOA) reflectance (reflective bands), TOA brightness temperature (BT; thermal infrared [TIR] bands), and surface reflectance-derived NDVI images were downloaded from the EROS ESPA On Demand Interface (https://espa.cr.usgs.gov/). Person who carried out this activity:
    U.S. Geological Survey
    Attn: Julie C. Bernier
    Geologist
    600 4th Street South
    St. Petersburg, FL
    USA

    727-502-8000 (voice)
    jbernier@usgs.gov
    Date: 2019 (process 2 of 5)
    All images were batch-processed using Spatial Model Editor in ERDAS IMAGINE 2016. The TOA and BT bands were stacked to create 7- (TM, ETM+) or 9- (OLI) band multispectral images and clipped to the study-area extent. From these composite images, two additional spectral indices, mNDWI and NBLI, were calculated. Person who carried out this activity:
    U.S. Geological Survey
    Attn: Julie C. Bernier
    Geologist
    600 4th Street South
    St. Petersburg, FL
    USA

    727-502-8000 (voice)
    jbernier@usgs.gov
    Date: 2019 (process 3 of 5)
    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. We mapped these pixels as sand using the following rule: if NBLI = sand and NDVI = vegetated, then final = sand (based on visual analysis during workflow development). 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. All steps were batch-processed using the Image Processing toolbox in MATLAB version R2018a (Otsu thresholding and binary image creation) or Spatial Model Editor in ERDAS IMAGINE 2016 (spectral index masking and generation of classed land-cover rasters). Person who carried out this activity:
    U.S. Geological Survey
    Attn: Julie C. Bernier
    Geologist
    600 4th Street South
    St. Petersburg, FL
    USA

    727-502-8000 (voice)
    jbernier@usgs.gov
    Date: 2020 (process 4 of 5)
    Vector shoreline (representing the boundary between intertidal and open-water areas), sand, and vegetated extents were extracted by contouring the mNDWI and masked NBLI and NDVI images using the calculated Otsu thresholds. The resulting shapefiles (one per image acquisition date) were merged into 3 shapefiles (one each for shoreline, sand, and vegetated feature extents). Contouring was batch-processed using PythonWin 2.7 with Esri ArcGIS 10.5. Vector features corresponding to a minimum mapping unit of less than 5 pixels were excluded from the final dataset. Person who carried out this activity:
    U.S. Geological Survey
    Attn: Julie C. Bernier
    Geologist
    600 4th Street South
    St. Petersburg, FL
    USA

    727-502-8000 (voice)
    jbernier@usgs.gov
    Data sources produced in this process:
    • nchan_shrln.shp
    • nchan_sandext.shp
    • nchan_vegext.shp
    Date: 2020 (process 5 of 5)
    Barrier platform, beach, and vegetated widths were calculated from the intersection of the shoreline, sand, and vegetated vectors with transects spaced 300 m (10 pixels) apart alongshore. The software package AMBUR version 1.1.27 (Analyzing Moving Boundaries Using R; Jackson and others, 2012) was used to create transects perpendicular to an offshore baseline and extract feature positions along the transects. The western islands, isolated back-barrier islands that are less than 8 pixels in size, and back-barrier islands that are more than 8 pixels from the contiguous island extent were excluded from the features dataset. Feature widths were calculated in Microsoft Excel for Mac version 16.50. Feature widths were not calculated along transect 57, where the oblique nature of the back-barrier marsh island, coupled with a change in baseline orientation, caused inconsistencies in delineating feature extents. Features less than 17 m wide along-transect are considered unresolvable based on the stated 12-m RMSE for Landsat L1TP products (sqrt(12^2 + 12^2) = 16.97) and were also excluded from the final dataset. Person who carried out this activity:
    U.S. Geological Survey
    Attn: Julie C. Bernier
    Geologist
    600 4th Street South
    St. Petersburg, FL
    USA

    727-502-8000 (voice)
    jbernier@usgs.gov
    Data sources produced in this process:
    • ambur_perp_transects_300m.shp
    • nchan_featmetrics.csv
  3. What similar or related data should the user be aware of?
    Bernier, Julie C., Miselis, Jennifer L., and Plant, Nathaniel G., 20210921, Satellite-derived barrier response and recovery following natural and anthropogenic perturbations, northern Chandeleur Islands, Louisiana: Remote Sensing Special Issue "New Insights into Ecosystem Monitoring Using Geospatial Techniques".

    Online Links:

    Otsu, Nobuyuki, 1979, A Threshold Selection Method from Gray-Level Histograms: IEEE Transactions on Systmes, Man and Cybernetics Volume 9.

    Online Links:

    Other_Citation_Details: Pages 62-66
    Jackson, Chester W. Jr., Alexander, Clark R., and Bush, David M., 2012, Gradistat: Application of the AMBUR R package for spatio-temporal analysis of shoreline change: Jekyll Island, Georgia, USA: Computers & Geosciences Volume 41.

    Online Links:

    Other_Citation_Details: Pages 199-207

How reliable are the data; what problems remain in the data set?

  1. How well have the observations been checked?
  2. How accurate are the geographic locations?
    Geodetic accuracy of Landsat L1TP data products depend on the accuracy of the ground control points and the resolution of the digital elevation model (DEM) used. All L1TP data products and derived Level-2 science products meet pre-defined image-to-image georegistration tolerances of <= 12-meter (m) radial root mean square error (RMSE). The positional accuracy of the satellite-derived features was not systematically evaluated in this study; however, recent analyses of satellite-derived shoreline (SDS) positions extracted using similar methods to those presented here report offsets of 1/3 to 1/2 pixel (10 to 15 m) seaward of measured in-situ shoreline positions. Compared with methods that extract shoreline position from precise elevation measurements (for example, lidar or GPS surveys), SDS positions are not based on a vertical datum (for example, mean sea level or mean high water); instead, SDS positions may include intertidal areas.
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
    193 Landsat TM, ETM+, and OLI images (Worldwide Reference System 2 [WRS-2] path 21 row 39) acquired between March 1984 and January 2019 were identified that were cloud free and, for Landsat 7 ETM+ images, were either pre-scan line corrector failure (SLC-off) or SLC-off gap free over 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 52 Landsat 5 TM, 10 Landsat 7 ETM+, and 13 Landsat 8 OLI images.
  5. How consistent are the relationships among the observations, including topology?
    For each image-acquisition date, Landsat Collection 1 Level-1 Precision and Terrain (L1TP) corrected data products and Level-2 science products were downloaded from the USGS Earth Resources Observation and Science (EROS) Center Science Processing Architecture (ESPA) On Demand Interface (https://espa.cr.usgs.gov/).

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?
Access_Constraints: None
Use_Constraints:
The U.S. Geological Survey requests that it be acknowledged as the originator of this dataset in any future products or research derived from these data.
  1. Who distributes the data set? (Distributor 1 of 1)
    U.S. Geological Survey
    Attn: Julie C. Bernier
    Geologist
    600 4th Street South
    St. Petersburg, FL
    USA

    727-502-8000 (voice)
    jbernier@usgs.gov
  2. What's the catalog number I need to order this data set? nchan_featmetrics.csv, ambur_perp_transects_300m.shp, nchan_sandext.shp, nchan_shrln.shp, and nchan_vegext.shp
  3. What legal disclaimers am I supposed to read?
    This publication was prepared by an agency of the United States Government. Although these data have been processed successfully on a computer system at the U.S. Geological Survey, 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 imply any such warranty. The U.S. Geological Survey shall not be held liable for improper or incorrect use of the data described and (or) contained herein. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof.
  4. How can I download or order the data?
    • Availability in digital form:
      Data format: This zip archive contains vector feature datasets in Esri shapefile (.shp) format, a comma-separated values (.csv) file detailing derived feature metrics, and accompanying metadata for each of 75 Landsat image-acquisition dates. in format Compressed (zip) archive
      Network links: https://coastal.er.usgs.gov/data-release/doi-P9HY3HOR/data/nchan_features.zip
    • Cost to order the data: None, if obtained online

  5. What hardware or software do I need in order to use the data set?
    These vector datasets were created using Esri ArcGIS version 10.5 and can be opened using Esri ArcGIS version 10.0 or higher; these data may also be viewed using the free Google Earth Pro GIS viewer.

Who wrote the metadata?

Dates:
Last modified: 21-Sep-2021
Metadata author:
U.S. Geological Survey
Attn: Julie C. Bernier
Geologist
600 4th Street South
St. Petersburg, FL
USA

727-502-8000 (voice)
jbernier@usgs.gov
Metadata standard:
FGDC Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)
This page is <https://cmgds.marine.usgs.gov/catalog/spcmsc/nchan_features-met.faq.html>
Generated by mp version 2.9.50 on Tue Sep 21 18:18:55 2021