Digital elevation models (DEMs) of coastal North Carolina, from 2019-09-08 to 2019-09-13, Post-Hurricane Dorian

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Frequently anticipated questions:

What does this data set describe?

Title:
Digital elevation models (DEMs) of coastal North Carolina, from 2019-09-08 to 2019-09-13, Post-Hurricane Dorian
Abstract:
Digital elevation models (DEMs) were created from aerial imagery collected between September 08 and September 13, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document ground conditions post-Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers estimate the land surface after Hurricane Dorian and were created to document inter-annual changes in shoreline position and coastal morphology in response to storm events using aerial imagery collections and a structure from motion (SFM) workflow. These data can be used with geographic information systems or other software to identify topographic and shallow-water bathymetric features.
Supplemental_Information:
Additional information about the field activity from which these data were derived is available online at:
https://cmgds.marine.usgs.gov/fan_info.php?fan=2019-311-CNT
Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
The raw imagery and navigation data used to produce the DEMs are available online at https://doi.org/10.5066/P9TPKMBB. Bounding coordinates for the metadata are derived from the overall flight path and are not necessarily representative of individual DEM product boundaries, which are split up along the coast to have more accessible data-download sizes. See image at https://www.sciencebase.gov/catalog/file/get/617352c1d34ea36449a8838b?name=Product_Boundary_Map.jpg for geographic locations used to create the data subsets. Note that the term DEM is used throughout this data release, but digital surface model (DSM) is also appropriate, as the models include vegetation and other canopy returns.
  1. How might this data set be cited?
    Ritchie, Andrew C., and Over, Jin-Si R., 20221011, Digital elevation models (DEMs) of coastal North Carolina, from 2019-09-08 to 2019-09-13, Post-Hurricane Dorian: data release DOI:10.5066/P9K3TWY7, U.S. Geological Survey, Pacific Coastal and Marine Science Center, Santa Cruz, CA.

    Online Links:

    This is part of the following larger work.

    Ritchie, Andrew C., Over, Jin-Si R., Kranenburg, Christine J., Brown, Jenna A., Buscombe, Daniel D., Sherwood, Christopher R., Warrick, Jonathan A., and Wernette, Phillipe A., 2022, Aerial photogrammetry data and products of the North Carolina coast: data release DOI:10.5066/P9K3TWY7, U.S. Geological Survey, Pacific Coastal and Marine Science Center, Santa Cruz, CA.

    Online Links:

  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -76.54407699
    East_Bounding_Coordinate: -75.45763017
    North_Bounding_Coordinate: 36.55388938
    South_Bounding_Coordinate: 34.58690112
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/619bea7fd34eb622f692fdd4?name=201909_DEM_NC_example.JPG&allowOpen=true (JPEG)
    Example segment of an elevation-colored digital elevation model from 2019-09-12.
  4. Does the data set describe conditions during a particular time period?
    Calendar_Date: 08-Sep-2019
    Currentness_Reference:
    Ground condition, data were collected on three days: September 8, 12, and 13 2019.
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: raster digital data (GeoTIFF)
  6. How does the data set represent geographic features?
    1. How are geographic features stored in the data set?
      This is a Raster data set. It contains the following raster data types:
      • Dimensions, type Pixel
    2. What coordinate system is used to represent geographic features?
      Grid_Coordinate_System_Name: Universal Transverse Mercator
      Universal_Transverse_Mercator:
      UTM_Zone_Number: 18
      Transverse_Mercator:
      Scale_Factor_at_Central_Meridian: 0.999600
      Longitude_of_Central_Meridian: -69.000000
      Latitude_of_Projection_Origin: 0.000000
      False_Easting: 500000.000000
      False_Northing: 0.000000
      Planar coordinates are encoded using row and column
      Abscissae (x-coordinates) are specified to the nearest 1
      Ordinates (y-coordinates) are specified to the nearest 1
      Planar coordinates are specified in meters
      The horizontal datum used is NAD83_National_Spatial_Reference_System_2011.
      The ellipsoid used is Geodetic Reference System 80.
      The semi-major axis of the ellipsoid used is 6378137.000000.
      The flattening of the ellipsoid used is 1/298.257222101.
      Vertical_Coordinate_System_Definition:
      Altitude_System_Definition:
      Altitude_Datum_Name: North American Vertical Datum of 1988
      Altitude_Resolution: 0.001
      Altitude_Distance_Units: meters
      Altitude_Encoding_Method:
      Explicit elevation coordinate included with horizontal coordinates
  7. How does the data set describe geographic features?
    20190908_DEM_VA_to_Oregon_Inlet_NAD83_2011_UTM18N_NAVD88_1m_cog.tif
    A raster dataset (cloud-optimized GeoTIFF format) with encoded elevation values of the North Carolina coast from the vicinity of the Virginia state border to Oregon Inlet on September 8, 2019. Pixel resolution is 1-meter. (Source: U.S. Geological Survey)
    Value
    Surface elevation orthometric height (m) in NAVD88 using Geoid 2018 (Source: U.S. Geological Survey)
    ValueDefinition
    -3.4028234663852886e+38No data
    Range of values
    Minimum:-2.077
    Maximum:44.114
    Units:meters
    20190908_DEM_Oregon_Inlet_to_Hatteras_Inlet_NAD83_2011_UTM18N_NAVD88_1m_cog.tif
    A raster dataset (cloud-optimized GeoTIFF format) with encoded elevation values of the North Carolina coast from Oregon Inlet to Hatteras Inlet on September 8, 2019. Pixel resolution is 1-meter. (Source: U.S. Geological Survey)
    Value
    Surface elevation orthometric height (m) in NAVD88 using Geoid 2018 (Source: U.S. Geological Survey)
    ValueDefinition
    -3.4028234663852886e+38No data
    Range of values
    Minimum:-5.159
    Maximum:20.319
    Units:meters
    20190908_DEM_Hatteras_Inlet_to_Ocracoke_Inlet_NAD83_2011_UTM18N_NAVD88_1m_cog.tif
    A raster dataset (cloud-optimized GeoTIFF format) with encoded elevation values of the North Carolina coast from Hatteras Inlet to Ocracoke Inlet on September 8, 2019. Pixel resolution is 1-meter. (Source: U.S. Geological Survey)
    Value
    Surface elevation orthometric height (m) in NAVD88 using Geoid 2018 (Source: U.S. Geological Survey)
    ValueDefinition
    -3.4028234663852886e+38No data
    Range of values
    Minimum:-3.582
    Maximum:13.409
    Units:meters
    20190908_DEM_Ocracoke_Inlet_to_Ophelia_Inlet_NAD83_2011_UTM18N_NAVD88_1m_cog.tif
    A raster dataset (cloud-optimized GeoTIFF format) with encoded elevation values of the North Carolina coast from Ocracoke Inlet to Ophelia Inlet on September 8, 2019. Pixel resolution is 1-meter. (Source: U.S. Geological Survey)
    Value
    Surface elevation orthometric height (m) in NAVD88 using Geoid 2018 (Source: U.S. Geological Survey)
    ValueDefinition
    -3.4028234663852886e+38No data
    Range of values
    Minimum:-5.000
    Maximum:49.999
    Units:meters
    20190912_DEM_VA_to_Oregon_Inlet_NAD83_2011_UTM18N_NAVD88_1m_cog.tif
    A raster dataset (cloud-optimized GeoTIFF format) with encoded elevation values of the North Carolina coast from the vicinity of the Virginia State border to Oregon Inlet on September 12, 2019. Pixel resolution is 1-meter. (Source: U.S. Geological Survey)
    Value
    Surface elevation orthometric height (m) in NAVD88 using Geoid 2018 (Source: U.S. Geological Survey)
    ValueDefinition
    -3.4028234663852886e+38No data
    Range of values
    Minimum:-1.475
    Maximum:40.268
    Units:meters
    20190912_DEM_Oregon_Inlet_to_Hatteras_Inlet_NAD83_2011_UTM18N_NAVD88_1m_cog.tif
    A raster dataset (cloud-optimized GeoTIFF format) with encoded elevation values of the North Carolina coast from Oregon Inlet to Hatteras Inlet on September 12, 2019. Pixel resolution is 1-meter. (Source: U.S. Geological Survey)
    Value
    Surface elevation orthometric height (m) in NAVD88 using Geoid 2018 (Source: U.S. Geological Survey)
    ValueDefinition
    -3.4028234663852886e+38No data
    Range of values
    Minimum:-3.243
    Maximum:29.821
    Units:meters
    20190912-13_DEM_Hatteras_Inlet_to_Ocracoke_Inlet_NAD83_2011_UTM18N_NAVD88_1m_cog.tif
    A raster dataset (cloud-optimized GeoTIFF format) with encoded elevation values of the coast from Hatteras Inlet to Ocracoke Inlet, NC on September 12 and 13, 2019. Pixel resolution is 1-meter. (Source: U.S. Geological Survey)
    Value
    Surface elevation orthometric height (m) in NAVD88 using Geoid 2018 (Source: U.S. Geological Survey)
    ValueDefinition
    -3.4028234663852886e+38No data
    Range of values
    Minimum:-1.171
    Maximum:23.513
    Units:meters
    20190912-13_DEM_Ocracoke_Inlet_to_Ophelia_Inlet_NAD83_2011_UTM18N_NAVD88_1m_cog.tif
    A raster dataset (cloud-optimized GeoTIFF format) with encoded elevation values of the North Carolina coast from Ocracoke Inlet to Ophelia Inlet on September 12 and 13, 2019. Pixel resolution is 1-meter. (Source: U.S. Geological Survey)
    Value
    Surface elevation orthometric height (m) in NAVD88 using Geoid 2018 (Source: U.S. Geological Survey)
    ValueDefinition
    -3.4028234663852886e+38No data
    Range of values
    Minimum:-7.625
    Maximum:11.878
    Units:meters
    20190912-13_DEM_Ophelia_Inlet_to_Beaufort_Inlet_NAD83_2011_UTM18N_NAVD88_1m_cog.tif
    A raster dataset (cloud-optimized GeoTIFF format) with encoded elevation values of the North Carolina coast from Ophelia Inlet to Beaufort Inlet, NC on September 12 and 13, 2019. Pixel resolution is 1-meter. (Source: U.S. Geological Survey)
    Value
    Surface elevation orthometric height (m) in NAVD88 using Geoid 2018 (Source: U.S. Geological Survey)
    ValueDefinition
    -3.4028234663852886e+38No data
    Range of values
    Minimum:-2.510
    Maximum:50.790
    Units:meters
    Entity_and_Attribute_Overview:
    Pixels represent elevation in meters relative to NAVD88 (Geoid 18). There are eight DEM 32-bit floating point cloud optimized GeoTIFFs. The filename for each DEM is formatted as "date_product_location_to_location_CRS_resolution_cog.tif", where date is the date the images were collected (in YYYYMMDD-DD format), product is digital elevation model (DEM), location_to_location is the specific geographic location in North Carolina of the northern extent to the southern extent, CRS is the horizontal and vertical coordinate reference system used, resolution is the horizontal pixel resolution of the grid, and 'cog' denotes the product is a cloud-optimized GeoTIFF. The horizontal and vertical CRS is NAD83(2011) UTM Zone 18N and NAVD88, respectively, for all DEMs.
    Entity_and_Attribute_Detail_Citation: USGS

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • Andrew C. Ritchie
    • Jin-Si R. Over
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
    U.S. Geological Survey, Pacific Coastal and Marine Science Center
    Attn: PCMSC Science Data Coordinator
    2885 Mission Street
    Santa Cruz, CA

    831-427-4747 (voice)
    pcmsc_data@usgs.gov

Why was the data set created?

U.S. Geological (USGS) researchers use the DEMs to assess future coastal vulnerability, nesting habitats for wildlife, and provide data for hurricane impact models. The products span the coast over both highly developed towns and natural areas, including federal lands. This research is part of the USGS Remote Sensing Coastal Change Project.

How was the data set created?

  1. From what previous works were the data drawn?
    Aerial Imagery (source 1 of 4)
    Kranenburg, Christine, Ritchie, Andrew C, Brown, Jennifer (Jenna) A, Over, Jin-Si R, Buscombe, Daniel D, Sherwood, Christopher R, Warrick, Jonathan A, and Wernette, Phillipe A, 2021, Aerial imagery of the North Carolina coast: 2019-09-08, 2019-09-12 and 2019-09-13, post-Hurricane Dorian: U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center.

    Online Links:

    Type_of_Source_Media: Digital
    Source_Contribution:
    The data in this release are used to make post-Hurricane Dorian SFM products.
    Aerial Imagery 4D dataset 1 (source 2 of 4)
    Kranenburg, Christine J., Ritchie, Andrew C., Brown, Jenna A., Over, Jin-Si R., Sherwood, Christopher R., Warrick, Jonathan A., and Wernette, Phillipe A., 2021, Aerial imagery of the North Carolina coast: 2019-08-30 and 2019-09-02, pre-Hurricane Dorian: U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center.

    Online Links:

    Type_of_Source_Media: Digital
    Source_Contribution:
    The data in this release are used in the 4D alignment Metashape SFM Batch1 process.
    Aerial Imagery 4D dataset 2 (source 3 of 4)
    Kranenburg, Christine J., Ritchie, Andrew C., Brown, Jenna A., Over, Jin-Si R., Buscombe, Daniel, Sherwood, Christopher R., Warrick, Jonathan A., and Wernette, Phillipe A., 2020, Post-Hurricane Florence aerial imagery: Cape Fear to Duck, North Carolina, October 6–8, 2018: U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center.

    Online Links:

    Type_of_Source_Media: Digital
    Source_Contribution:
    The data in this release are used in the 4D alignment Metashape SFM Batch1 process.
    Ground Control Points (source 4 of 4)
    Jennifer (Jenna) A. Brown, Sherwood, Christopher R., Martini, Marinna, Kranenburg, Christine J., and Over, Jin-Si R., 2021, Ground Control Point Data from the Outer Banks, North Carolina, post-Hurricane Dorian, September 2019.

    Online Links:

    Type_of_Source_Media: Digital and/or Hardcopy
    Source_Contribution:
    The Ground Control Points are used in the SFM process and to assess horizontal and vertical positional accuracy.
  2. How were the data generated, processed, and modified?
    Date: Feb-2022 (process 1 of 2)
    On a workstation (AMD Threadripper 3960X /AsRock TRX40 Creator motherboard/256GB 3000MHz RAM) using Win10x64, aerial imagery and associated positional data (Kranenburg and others 2020; 2021a; 2021b) and a single ground control point (Brown and others, 2021) were brought into an Agisoft Metashape Pro (v. 1.6.5) project to align in a 4D manner (see Sherwood and others, 2019). Only one ground control point, GCP 34, was used as a control point to help 'lock' in the camera positions, whereas the rest of the points were used as independent vertical check points (that is, they were not placed in Metashape). See Kranenburg and others (2021a), for Metashape Reference Settings inputs. The additional imagery improves the horizontal and vertical accuracy, but similar products can be reproduced without them. The following steps were performed on the Metashape project in the geographic coordinate system NAD83(2011) in ellipsoid height following the general guidance of Over and others (2021): 1. Separate camera models and camera groups were created for each flight date aligned in 4D. Note that multiple imagery datasets are used in the overall processing effort to produce the end individual survey products that this metadata file covers. 2. Imagery (with positions) are aligned in 4D to create a point cloud using a 'High' alignment setting, keypoint limit of 70,000, tiepoint limit of 0, generic preselection selected, and reference preselection via source selected. The tiepoint accuracy was set to 1 pixel. 3. The resultant point cloud was filtered using one iteration of the 'Reconstruction uncertainty' filter at a level of 10, one iteration of the 'Projection accuracy' filter at a level of 3, and two iterations of the 'Reprojection accuracy' filer at a level of 0.3 (in the second iteration the 'fit additional corrections' option was turned on). With each filter, iteration points are selected, deleted, and then the camera model is optimized to refine the focal length, cx, cy, k1, k2, k3, p1, and p2 camera model coefficients. 4. Natural breaks in the final alignment product were identified based on bodies of water or the extreme northern and southern ends of a flight (see Product_Boundary_Map.jpg at https://doi.org/10.5066/P9K3TWY7). The breaks and dates of imagery in the 4D process are used for ease and speed of processing. The boundaries used for the post-Hurricane Dorian dataset are the Virginia-North Carolina border vicinity to Oregon Inlet, Oregon Inlet to Hatteras Inlet, Hatteras Inlet to Ocracoke Inlet, Ocracoke Inlet to Ophelia Inlet, and Ophelia Inlet to Beaufort Inlet.
    For each region, sub-chunks were created for each mission (one or two flight-days, usually adjacent) by iteratively copying the original 4D chunk and removing all camera groups not part of a single mission. Note that this particular metadata file only covers the post-Hurricane Dorian dataset collected from 2019-09-08 to 2019-09-13. Processing took place starting in June 2021 and into February 2022, the latest processing in YYYYMM is given in the Process Date. Data sources used in this process:
    • Aerial Imagery
    • Ground Control Points
    • Aerial Imagery 4D dataset 1
    • Aerial Imagery 4D dataset 2
    Date: Apr-2022 (process 2 of 2)
    From the previous process step, each 'chunk' is processed as follows to create the final DEM products for each flight date: 1. Targeted imagery sets in the aligned chunk are copied from the workstation to a new Agisoft Metashape Pro. project on the U.S Geological Survey Tallgrass high-performance computing network for processing on CPU and GPU nodes (https://www.usgs.gov/core-science-systems/sas/arc/machine-access). 2. If multiple flight dates were flown for this chunk, imagery from one date is targeted, and the rest are disabled (this is then switched for each flight date in the chunk after the final step and steps 3-6 are repeated). 3. A high quality dense point cloud is generated for the chunk with 'mild' filtering and the options to calculate point color and point confidence selected. 4. Dense point cloud is filtered using the 'Filter by Confidence' tool using the range 0-2, these points selected at this range are classified as low noise. 5. A DEM is built from the dense point cloud with interpolation disabled and without the points classified as low noise. 6. DEM is exported in NAD83(2011) UTM Zone 18N and NAVD88(m) with 1-m cell size and region boundaries rounded to the nearest 10 m interval. West and south bounds are rounded up and east and north bounds are rounded down. 7. In order to minimize elevation differences between flights in the 4D reconstruction, all DEMs were then adjusted to a common datum by adding the median signed difference between GCPs (Brown and others, 2021) and the Oregon Inlet to Hatteras Inlet DEM elevations (GCP - DEM) produced by each survey. That is, for DEMs from 2018-10-06 to 2019-09-13, differences were calculated for all GCPs and all Oregon Inlet to Hatteras Inlet DEMs and then these values were ranked, and the middle value was used (or the middle two values were averaged, for an even number of differences) to adjust each DEM in the chunk, not just the Oregon Inlet to Hatteras Inlet DEM. The median value for this 4D reconstruction was -0.02882. 8. Each adjusted DEM was then masked by a human-edited shapefile in QGIS (v. 3.2.2.) to remove high uncertainty regions. Note that the shapefiles are used as part of the workflow to produce the final product and are not provided, if this extent or shapefile needs to be used by someone else it can be recreated in a GIS setting by extracting the outline(s) of the provided raster(s), for example the raster to vector tool in QGIS. Uncertainty was visualized using a hillshade of the DEM with an elevation factor of 5 and an additional raster that highlights areas with a high standard deviation away from the adjusted DEM elevation values. The shapefiles were edited by either S. Bosse, J. Over, E. Lyons, or J. Favela. 9. Final clipped DEMs for the pre-Hurricane Dorian dataset are turned into cloud-optimized GeoTIFFs (COG) using gdal_translate with the following command:for %i in (.\*.tif) do gdal_translate %i .\cog\%~ni_cog.tif -of COG -stats -co BLOCKSIZE=256 -co COMPRESS=DEFLATE -co PREDICTOR=YES -co NUM_THREADS=ALL_CPUS -co BIGTIFF=YES (v. 3.1.4 accessed October 20, 2020 https://gdal.org/), where i is the name of each geoTIFF section.
  3. What similar or related data should the user be aware of?
    Over, Jin-Si R., Ritchie, Andrew C., Kranenburg, Christine J., Brown, Jenna A., Buscombe, Daniel D., Noble, Tommy, Sherwood, Christopher R., Warrick, Jonathan A., and Wernette, Phillipe A., 2021, Processing coastal imagery with Agisoft Metashape Professional Edition, version 1.6—Structure from motion workflow documentation: Open-File Report 2021-1039, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    This publication includes the general methodology for processing imagery in Metashape to produce DEMs and ortho products.
    NOAA Office for Coastal Management (OCM Partners), 2019, 2018 USACE NCMP Post-Florence Topobathy Lidar DEM: Southeast Coast (VA, NC, SC): Data Series 57345, Office for Coastal Management, Charleston, SC.

    Online Links:

    Other_Citation_Details:
    This data set was used to qualitatively assess the horizontal and vertical accuracy of the DEM products.
    NOAA Office for Coastal Management (OCM Partners), 2019, 2019 USACE NCMP DUNEX Topobathy Lidar DEM: East Coast (NC, VA): Data Series 60197, Office for Coastal Management, Charleston, SC.

    Online Links:

    Other_Citation_Details:
    This data set was used to qualitatively assess the horizontal and vertical accuracy of the DEM products.
    Sherwood, Christopher R., Warrick, Jonathan A., Hill, Andrew D., Ritchie, Andrew C., and Plant, Nathaniel G., 2018, Rapid, remote assessment of Hurricane Matthew impacts using four-dimensional structure-from-motion photogrammetry: Professional Paper DOI:10.2112/JCOASTRES-D-18-00016.1, Journal of Coastal Research, Online.

    Online Links:

    Other_Citation_Details:
    This publication includes the general methodology described for processing imagery in Metashape in four-dimensions to produce DEMs and ortho products.

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

  1. How well have the observations been checked?
    The source imagery and positional information and metadata that were used to create these photogrammetrically derived digital elevation models are available at Kranenburg and others (2021a). Information on the horizontal and vertical accuracies of the source data can be found within the data release metadata. Product vertical accuracy is assessed using published ground control points (Brown and others, 2021). Users are encouraged to do their own accuracy assessment with published lidar or other elevation products to make sure the error estimates and products meet their needs. It should also be noted that accuracy estimates of the products are for areas of bare ground or low vegetation where GCPs were placed. Additional sources of error such as poor image-to-image point matching due to vegetation or uniform substrate texture or moving objects resulting in poor surface reconstruction may cause localized errors in some portions of the DEM to exceed accuracy estimates. Processing imagery in 4D (see processing steps) aims to keep related products precise within the reported accuracies.
  2. How accurate are the geographic locations?
    Horizontal accuracy is affected by the source data and photogrammetry processing and difficult to quantitatively test. One ground control point (GCP 34; 0.037-meter xy accuracy) and post-processed kinematic (PPK) camera positions (Kranenburg and others, 2020; 2021a; 2021b) were used to create the final SfM products. The horizontal (x,y) error of GCP 34 after batch co-alignment and error reduction in the Metashape project (see processing steps) was 0.040,-0.048 m. These values do not represent the absolute horizontal georeferencing accuracy of the product but provide a better sense of the overall accuracy. Due to the nature of the in-place GCPs being difficult to distinguish in the orthomosaics at their published resolution, no further horizontal accuracy assessment was done with them. A qualitative analysis of gridded first-return lidar data at stable points (OCM Partners, 2018; 2019) supports these base horizontal accuracy estimates.
  3. How accurate are the heights or depths?
    Only 1 ground control point (GCP 34; 0.043-meter z accuracy; Brown and others, 2021) and the post-processed kinematic (PPK) camera positions (Kranenburg and others, 2020; 2021a, 2021b) were used in the photogrammetry processing to create the final products. The vertical positional accuracy was independently evaluated, outside of Metashape, against Brown and others (2021) GCPs within the extent of the two Oregon Inlet to Hatteras Inlet DEMs (6 of 34 GCPs on 2019-09-08 and 17 of 24 GCPs on 2019-09-12 were within the SfM product extents), and these were compared to the corrected raster elevations (see processing steps) using bilinear interpolation at each GPS point to derive the RMSE (0.092 and 0.078 meters) and MAE (0.081 and 0.061 meters) of the DEMs. Note that this is separate from the GCP and DEM adjustment detailed in the Processing Step 7. The “corrected” mean-error (vertical bias) of the GCP measurements relative to the DEMs was -0.013 meters, meaning the DEM was, on average, reconstructed at a higher elevational surface than the GPS measurements. The addition of the reported vertical accuracy of the GPS measurements (0.047 meters) in quadrature results in a total vertical accuracy estimate of 0.102 and 0.091 meters for the 2019-09-08 and 2019-09-12 Oregon Inlet to Hatteras Inlet DEMs, respectively, using this method. Given that the ground control points are only available within the Oregon Inlet to Hatteras Inlet DEMs, we assume that all other DEMs in this release (from VA vicinity to Cape Lookout) have similar vertical non-vegetated accuracies. A qualitative analysis of gridded first return lidar data (OCM Partners 2018; 2019) supports these accuracy estimates.
  4. Where are the gaps in the data? What is missing?
    The final DEM products are not interpolated and have been cropped to remove the majority, but not all of, the noise and zones of high uncertainty (for example, foreshore, water bodies, areas with poor overlap). Therefore, the DEMs do not cover the same exact extent as the associated orthorectified products in the larger work citation or the original imagery available. GeoTIFFs are cloud-optimized.
  5. How consistent are the relationships among the observations, including topology?
    There are a total of eight DEMs included in this dataset. All data fall into expected elevation ranges except for points near tall buildings, areas of poorer image overlap, and near water (waves, ponds, shorelines), where the data return is often sparse, noisy, and erroneous. The DEM includes returns from the vegetation on land and in the water. Shallow underwater reconstructions have not been corrected for parallax.

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 Public domain data from the U.S. Government are freely redistributable with proper metadata and source attribution. Please recognize the U.S. Geological Survey (USGS) as the source of this information. These data are not intended for navigational use.
  1. Who distributes the data set? (Distributor 1 of 1)
    U.S. Geological Survey - Sciencebase
    Denver Federal Center, Building 810, Mail Stop 302
    Denver, CO
    United States

    1-888-275-8747 (voice)
    sciencebase@usgs.gov
  2. What's the catalog number I need to order this data set? The eight DEM deflate-compressed cloud-optimized GeoTIFFS (COGs) are available in 1-m resolution and represent the coast of North Carolina post-Hurricane Dorian on September 8, 12, and 13.
  3. What legal disclaimers am I supposed to read?
    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. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
  4. How can I download or order the data?

Who wrote the metadata?

Dates:
Last modified: 11-Oct-2022
Metadata author:
U.S. Geological Survey, Pacific Coastal and Marine Science Center
Attn: PCMSC Science Data Coordinator
2885 Mission Street
Santa Cruz, CA

831-427-4747 (voice)
pcmsc_data@usgs.gov
Metadata standard:
Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)
This page is <https://cmgds.marine.usgs.gov/catalog/pcmsc/DataReleases/ScienceBase/DR_P9K3TWY7/201909_DEM_NC_metadata.faq.html>
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