Digital Surface Models (DSM) from UAS surveys of the beaches at Fort Stevens State Park, OR, and Cape Disappointment State Park, WA, August 2017

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Frequently anticipated questions:

What does this data set describe?

Title:
Digital Surface Models (DSM) from UAS surveys of the beaches at Fort Stevens State Park, OR, and Cape Disappointment State Park, WA, August 2017
Abstract:
This portion of the data release presents digital surface models (DSM) of the ocean beach at Fort Stevens State Park, OR, and Benson Beach at Cape Disappointment State Park, WA. The DSMs have resolutions of 10 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected with unoccupied aerial systems (UAS) during low tides on 7 and 8 August 2017. Unlike a digital elevation model (DEM), the DSMs represent the elevation of the highest object within the bounds of a cell. Vegetation, buildings, and other objects have not been removed from the data. The raw imagery used to create the DSMs was acquired with a UAS fitted with a Ricoh GR II digital camera featuring a global shutter. The UAS was flown on pre-programmed autonomous flight lines spaced to provide approximately 70 percent overlap between images from adjacent lines. The camera was triggered at 1 Hz using a built-in intervalometer. The raw imagery was geotagged using positions from the UAS onboard single-frequency autonomous GPS. Survey control was established using temporary ground control points (GCPs) consisting of a combination of small square tarps with black-and-white cross patterns and temporary chalk marks placed on the ground. The GCP positions were measured using dual-frequency post-processed kinematic (PPK) GPS with corrections referenced to a static base station operating nearby. The images and GCP positions were used for structure-from-motion (SfM) processing to create topographic point clouds, high-resolution orthomosaic images, and DSMs. The DSMs, which are presented in this portion of the data release have been formatted as cloud optimized GeoTIFFs with internal overviews and masks to facilitate cloud-based queries and display.
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=2017-666-FA
Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
  1. How might this data set be cited?
    Logan, Joshua B., Stevens, Andrew W., and Harrison, Shawn R., 20230623, Digital Surface Models (DSM) from UAS surveys of the beaches at Fort Stevens State Park, OR, and Cape Disappointment State Park, WA, August 2017: data release DOI:10.5066/P9BVTVAW, U.S. Geological Survey, Pacific Coastal and Marine Science Center, Santa Cruz, California.

    Online Links:

    This is part of the following larger work.

    Logan, Joshua B., Stevens, Andrew W., Harrison, Shawn R., and Johnson, Cordell D., 2023, Aerial imagery and structure-from-motion data products from UAS surveys of the beaches at Fort Stevens State Park, OR, and Cape Disappointment State Park, WA: data release DOI:10.5066/P9BVTVAW, U.S. Geological Survey, Pacific Coastal and Marine Science Center, Santa Cruz, CA.

    Online Links:

    Other_Citation_Details:
    Suggested Citation: Logan, J.B., Stevens, A.W., Harrison, S.R., and Johnson, C.D., 2023, Aerial imagery and structure-from-motion data products from UAS surveys of the beaches at Fort Stevens State Park, OR, and Cape Disappointment State Park, WA: U.S. Geological Survey data release, https://doi.org/10.5066/P9BVTVAW.
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -124.08829
    East_Bounding_Coordinate: -123.99237
    North_Bounding_Coordinate: 46.29986
    South_Bounding_Coordinate: 46.19996
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/63af854bd34e92aad3ca60f3?name=FortStevens_BensonBeach_2017-08_DSM_browse.jpg&allowOpen=true (JPEG)
    Color-shaded relief of DSMs from August 2017 UAS surveys.
  4. Does the data set describe conditions during a particular time period?
    Calendar_Date: 07-Aug-2017
    Currentness_Reference:
    ground condition at time data were collected
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: 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 Grid Cell
    2. What coordinate system is used to represent geographic features?
      Grid_Coordinate_System_Name: State Plane Coordinate System 1983
      State_Plane_Coordinate_System:
      SPCS_Zone_Identifier: 4602
      Lambert_Conformal_Conic:
      Standard_Parallel: 47.33333
      Standard_Parallel: 45.83333
      Longitude_of_Central_Meridian: -120.50000
      Latitude_of_Projection_Origin: 45.33333
      False_Easting: 500000.0
      False_Northing: 0.0
      Planar coordinates are encoded using row and column
      Abscissae (x-coordinates) are specified to the nearest 0.100
      Ordinates (y-coordinates) are specified to the nearest 0.100
      Planar coordinates are specified in meters
      The horizontal datum used is North American Datum of 1983 (EPSG:4269).
      The ellipsoid used is GRS 1980 (EPSG:7019).
      The semi-major axis of the ellipsoid used is 6378137.0.
      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 (EPSG:5703), derived using GEOID12B
      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?
    GeoTIFF
    GeoTIFF containing elevation values. (Source: Producer defined)
    Band_1
    Elevation relative to NAVD88 in units of meters. (Source: Producer defined)
    Range of values
    Minimum:-5.154
    Maximum:67.062
    Entity_and_Attribute_Overview:
    The dataset consists of a raster which represents elevation values and contains a single attribute. Each cell in the raster corresponds to a location and contains a numeric value indicating the elevation relative to NAVD88 in units of meters.
    Entity_and_Attribute_Detail_Citation: U.S. Geological Survey

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • Joshua B. Logan
    • Andrew W. Stevens
    • Shawn R. Harrison
  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?

These data were obtained to evaluate changes in shoreline position and coastal morphology. These data are intended for science researchers, students, policy makers, and the general public. These data can be used with geographic information systems or other software to identify topographic features on the sub-aerially exposed portions of the beaches surveyed.

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: Aug-2017 (process 1 of 4)
    Aerial imagery was collected using a Department of Interior-owned 3DR Solo quadcopter fitted with a Ricoh GR II digital camera featuring a global shutter. The camera was mounted using a fixed mount on the bottom of the UAS and oriented in an approximately nadir orientation. During acquisition the UAS was flown on pre-programmed autonomous flight lines at a variable altitude of less than 120 meters above ground level (AGL). Altitude for each flight was determined in the field depending on operational restrictions related to the cloud ceiling. Each flight was programmed to provide approximately 66 percent overlap between images from adjacent lines. The camera was triggered at 1 Hz using a built-in intervalometer. Before each flight, the camera’s digital ISO, aperture and shutter speed were manually set to adjust for ambient light conditions. Although these settings were changed between flights, they were not permitted to change during a flight; thus, the images from each flight were acquired with consistent camera settings.
    Date: Aug-2017 (process 2 of 4)
    Ground control was established using ground control points (GCPs) consisting of a combination of small square tarps with black-and-white cross patterns and temporary "X" marks placed with chalk on the ground surface throughout the survey area. The GCP positions were measured using post-processed kinematic (PPK) GPS, using corrections from GPS base stations located near the survey area. For each GCP measurement the GPS receiver was placed on a fixed-height tripod and set to occupy the GCP for a minimum occupation time of one minute. Post-processing was conducted using the Trimble Business Center software package.
    Date: 2017 (process 3 of 4)
    The image files were renamed using a custom python script. The file names were formed using the following pattern Fx-YYYYMMDDThhmmssZ_Ryz.*, where: - Fx = Flight number - YYYYMMDDThhmmssZ = date and time in the ISO 8601 standard, where 'T' separates the date from the time, and 'Z' denotes UTC ('Zulu') time. - Ry = RA or RB to distinguish camera 'RicohA' from 'RicohB' - z = original image name assigned by camera during acquisition - * = file extension (JPG)
    The approximate image acquisition coordinates were added to the image metadata (EXIF) ('geotagged') using the image timestamp and the telemetry logs from the UAS onboard single-frequency 1-Hz autonomous GPS. The geotagging process was done using the GeoSetter utility. To improve timestamp accuracy, the image acquisition times were adjusted to true ('corrected') UTC time by comparing the image timestamps with several images taken of a clock showing accurate time synchronized from Network Time Protocol (NTP) servers. For the Fort Stevens survey on 2017-08-07 the image time stamps from camera "RA" were adjusted by +00:01:14 (+1 minute, and 14 seconds) to synchronize with corrected UTC time. For the Benson Beach survey on 2017-08-08 the image time stamps from camera "RA" were adjusted by +00:01:16 (+1 minute, and 16 seconds) to synchronize with corrected UTC time. The positions stored in the EXIF are in geographic coordinates referenced to the WGS84(G1150) coordinate reference system (EPSG:4979), with elevation in meters relative to the WGS84 ellipsoid.
    Additional information was added to the EXIF using the command-line 'exiftool' software. For the Fort Stevens imagery the following command was used: exiftool ^ -P ^ -IPTC:Credit="U.S. Geological Survey" ^ -IPTC:Contact="pcmsc_data@usgs.gov" ^ -EXIF:Copyright="Public Domain" ^ -XMP:UsageTerms="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." ^ -EXIF:ImageDescription="Aerial image of the beach at Fort Stevens State Park, Oregon, USA, from USGS Unoccupied Aircraft System (UAS) survey 2017-666-FA (https://cmgds.marine.usgs.gov/fan_info.php?fan=2017-666-FA), conducted under Oregon Parks and Recreation Department Scientific Research Permit #024-17" ^ -XMP:Event="Unoccupied Aircraft System survey of the beach at Fort Stevens State Park, Oregon, USA, during USGS field activity 2017-666-FA, conducted under Oregon Parks and Recreation Department Scientific Research Permit #024-17" ^ -EXIF:GPSAreaInformation="Position from UAS onboard autonomous single-frequency GNSS." ^ -EXIF:GPSMapDatum="EPSG:4979 (WGS 84)" ^ -EXIF:Artist="U.S. Geological Survey, Pacific Coastal and Marine Science Center" ^ -IPTC:CopyrightNotice="Public Domain. Please credit U.S. Geological Survey." ^ -IPTC:Caption-Abstract="Aerial image of the beach at Fort Stevens State Park, Oregon, USA, from USGS Unoccupied Aircraft System (UAS) survey 2017-666-FA conducted under Oregon Parks and Recreation Department Scientific Research Permit #024-17" ^ -sep ", " ^ -keywords="Columbia River, Fort Stevens State Park, South Jetty, Oregon, 2017-666-FA, Unoccupied Aircraft System, UAS, drone, aerial imagery, U.S. Geological Survey, USGS, Pacific Coastal and Marine Science Center" ^ -comment="Low-altitude aerial image from USGS Unoccupied Aircraft System (UAS) survey 2017-666-FA conducted under Oregon Parks and Recreation Department Scientific Research Permit #024-17" ^ -Orientation= ^ -XMP:AttributionURL="https://doi.org/10.5066/P9BVTVAW" ^ -ext DNG ^ -ext JPG ^
    For the Benson Beach imagery the following command was used: exiftool ^ -P ^ -IPTC:Credit="U.S. Geological Survey" ^ -IPTC:Contact="pcmsc_data@usgs.gov" ^ -EXIF:Copyright="Public Domain" ^ -XMP:UsageTerms="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." ^ -EXIF:ImageDescription="Aerial image of Benson Beach at Cape Disappointment State Park, Washington, USA, from USGS Unoccupied Aircraft System (UAS) survey 2017-666-FA (https://cmgds.marine.usgs.gov/fan_info.php?fan=2017-666-FA), conducted under Washington State Parks and Recreation Commission Scientific Research Permit 170603" ^ -XMP:Event="Unoccupied Aircraft System survey of Benson Beach at Cape Disappointment State Park, Washington, USA, during USGS field activity 2017-666-FA, conducted under Washington State Parks and Recreation Commission Scientific Research Permit 170603" ^ -EXIF:GPSAreaInformation="Position from UAS onboard autonomous single-frequency GNSS." ^ -EXIF:GPSMapDatum="EPSG:4979 (WGS 84)" ^ -EXIF:Artist="U.S. Geological Survey, Pacific Coastal and Marine Science Center" ^ -IPTC:CopyrightNotice="Public Domain. Please credit U.S. Geological Survey." ^ -IPTC:Caption-Abstract="Aerial image of Benson Beach at Cape Disappointment State Park, Washington, USA, from USGS Unoccupied Aircraft System (UAS) survey 2017-666-FA conducted under Washington State Parks and Recreation Commission Scientific Research Permit 170603" ^ -sep ", " ^ -keywords="Columbia River, Cape Disappointment State Park, North Jetty, Washington, 2017-666-FA, Unoccupied Aircraft System, UAS, drone, aerial imagery, U.S. Geological Survey, USGS, Pacific Coastal and Marine Science Center" ^ -comment="Low-altitude aerial image from USGS Unoccupied Aircraft System (UAS) survey 2017-666-FA conducted under Washington State Parks and Recreation Commission Scientific Research Permit 170603" ^ -Orientation= ^ -XMP:AttributionURL="https://doi.org/10.5066/P9BVTVAW" ^ -ext DNG ^ -ext JPG ^
    Additional metadata tags were populated for all of the imagery metadata using the following command: exiftool ^ -P ^ "-XMP-photoshop:Credit<IPTC:Credit" ^ "-XMP-iptcCore:CreatorWorkEmail<IPTC:Contact" ^ "-XMP-dc:Rights<EXIF:Copyright" ^ "-XMP-dc:Description<EXIF:ImageDescription" ^ "-XMP-exif:all<GPS:all" ^ "-XMP-exif:GPSLatitude<Composite:GPSLatitude" ^ "-XMP-exif:GPSLongitude<Composite:GPSLongitude" ^ "-XMP-exif:GPSDateTime<Composite:GPSDateTime" ^ "-XMP-photoshop:DateCreated<EXIF:DateTimeOriginal" ^ "-XMP-xmp:ModifyDate<EXIF:ModifyDate" ^ "-XMP-dc:Creator<EXIF:Artist" ^ "-XMP-tiff:Make<EXIF:Make" ^ "-XMP-tiff:Model<EXIF:Model" ^ -overwrite_original ^ -ext JPG ^ -ext DNG
    Date: 2017 (process 4 of 4)
    Structure-from-motion (SfM) processing techniques were used to create point clouds, DSMs, and orthomosaic images in the Agisoft Photoscan/Metashape software package using the following workflow: 1. Initial image alignment was performed using an automated python script (Logan and others, 2022), with the following parameters: Accuracy: 'high' Pair selection: 'reference', 'generic' Key point limit: 100,000 Tie point limit: 0 (unlimited) 2. Sparse point cloud error reduction was performed using the automated python script (Logan and others, 2022), to sequentially apply the Reconstruction Uncertainty and Projection Accuracy gradual selection filters to iteratively remove a portion of the lowest quality sparse points, followed by camera optimization. This resulted in the following final gradual selection filter values: - For Fort Stevens: Final Reconstruction Uncertainty: 10 Final Projection Accuracy: 3.0 Lens calibration parameters for optimization: f, cx, cy, k1, k2, k3, p1, and p2 - For Benson Beach: Final Reconstruction Uncertainty: 10.0 Final Projection Accuracy: 3.0 Lens calibration parameters for optimization: f, cx, cy, k1, k2, k3, p1, and p2 3. Ground control point (GCP) positions were imported, and markers were manually identified and placed in the images. 4. Additional sparse point cloud error reduction was performed using the automated python script to iteratively apply the Reprojection Error gradual selection filter and camera optimization such that no more than 10percent of the remaining sparse points are deleted at a time. Between each iteration of the filter, camera optimization was performed with the following lens calibration parameters: f, cx, cy, k1, k2, k3, p1, and p2. Once Reprojection Error was reduced below 1 pixel, additional lens calibration parameters (k4, b1, b2, p3, and p4) were included during optimization. This process was repeated until the following final Reprojection Error filter levels were achieved: - For Fort Stevens: Final Reprojection Error: 0.3 Lens calibration parameters for optimization: f, b1, b2, cx, cy, k1, k2, k3, k4, p1, p2, p3 and p4 - For Benson Beach: Final Reprojection Error: 0.3 Lens calibration parameters for optimization: f, b1, b2, cx, cy, k1, k2, k3, k4, p1, p2, p3 and p4 Additional remaining sparse points obviously above or below the true surface were manually deleted after the last error reduction iteration, and a final optimization was performed. 5. Dense point clouds were created using the 'high' accuracy setting, with 'aggressive' depth filtering, and exported to LAZ format. 6. Preliminary Digital Surface Models (DSM) with native resolutions of 5.32 and 4.65 centimeters per pixel (for Fort Stevens and Benson Beach, respectively) were created using all points in the dense point clouds and exported to GeoTIFF files with 10-centimeter pixel resolutions. 7. RGB orthomosaics with native resolutions of 2.7 and 2.32 centimeters per pixel (for Fort Stevens and Benson Beach, respectively) were created using the preliminary DSM as the orthorectification surface and exported to GeoTIFF files with 5-centimeter pixel resolutions. 8. The RGB orthomosaics were converted to cloud optimized GeoTIFF formats (using internal JPEG compression with a quality of 90) for compatibility with cloud storage services using the gdal_translate utility in the GDAL software package. 9. The orthomosaics and DSM GeoTIFFs were used as background maps in QGIS to manually delineate clipping polygons to exclude areas of poor surface reconstruction in the DSMs due to standing water, or waves in the surf zone. 10. The digitized polygons were used to clip the final DSMs using the gdalwarp utility in the GDAL software package. 11. The gdal_translate utility in the GDAL software package was used to convert the DSMs to cloud optimized GeoTIFF formats with DEFLATE compression, and internal statistics. Person who carried out this activity:
    Joshua Logan
    U.S. Geological Survey, Pacific Coastal and Marine Science Center
    Physical Scientist
    2885 Mission Street
    Santa Cruz, CA
    US

    831-460-7519 (voice)
    831-427-4748 (FAX)
    jlogan@usgs.gov
  3. What similar or related data should the user be aware of?
    Logan, Joshua B., Wernette, Phillipe A., and Ritchie, Andrew C., 2022, Agisoft Metashape/Photoscan Automated Image Alignment and Error Reduction version 2.0.

    Online Links:

    Other_Citation_Details:
    Logan, J.B., Wernette, P.A. and Ritchie, A.C., 2022, Agisoft Metashape/Photoscan Automated Image Alignment and Error Reduction version 2.0: U.S. Geological Survey code repository, U.S. Geological Survey software release, python package, Reston, Va., (https://doi.org/10.5066/P9DGS5B9).
    Stevens, Andrew W., Weiner, Heather M., Wood, Jeffrey M., Ruggiero, Peter, Kaminsky, George M., and Gelfenbaum, Guy R., 2021, Beach topography and nearshore bathymetry of the Columbia River littoral cell, Washington and Oregon (ver. 3.0, December 2021).

    Online Links:

    Other_Citation_Details:
    Stevens, A.W., Weiner, H.M., Wood, J.M., Ruggiero, P., Kaminsky, G.M., and Gelfenbaum G.R., 2019, Beach topography and nearshore bathymetry of the Columbia River littoral cell, Washington and Oregon (ver. 3.0, December 2021): U.S. Geological Survey data release, https://doi.org/10.5066/P9W15JX8.
    Federal Geographic Data Committee, 1998, Geospatial Positioning Accuracy Standards Part 3: National Standard for Spatial Data Accuracy.

    Online Links:

    Other_Citation_Details: FGDC-STD-007.3-1998

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

  1. How well have the observations been checked?
    The attribute values of these DSMs represent elevation, the accuracy of which is discussed in the Vertical Positional Accuracy Report section of the metadata.
  2. How accurate are the geographic locations?
    For each DSM, horizontal accuracy was estimated by comparing ground control point (GCP) positions measured with RTK GPS measurements to their SfM-estimated positions. Due to the time-intensive process of placing GCPs in the field, all available GCPs were used for registration and camera optimization in the SfM processing workflow. To evaluate the horizontal positional accuracy of the final SfM alignments, each GCPs was disabled one at a time using a python script to create a 'temporary check point'. With the single GCP temporarily disabled, camera optimization was performed with all lens parameters fixed, and all other GCPs enabled. The residual errors of the check point relative to its GPS-measured position were recorded. After all temporary check point iterations were complete, the root-mean-square error (RMSE) and mean-absolute error (MAE) were calculated. Following the Federal Geographic Data Committee (FGDC) National Standard for Spatial Data Accuracy guidelines, we use the RMSE to calculate the positional horizontal accuracy at the 95 percent confidence level. To account for additional uncertainty in the GPS-measured positions of the GCPs (0.030 meters) we include this as an additional error term through summation in quadrature to arrive at an estimate of total positional horizontal accuracy. The error statistics and horizontal accuracy estimates for each of the DSMs are below: - FortStevens_2017-08-07_DSM_10cm.tif: Horizontal RMSE (m): 0.016; Horizontal MAE (m): 0.013; Horizontal accuracy at the 95 percent confidence level (m): 0.028; Total horizontal accuracy estimate at the 95 percent confidence level, including GPS uncertainty (m): 0.041;
    - BensonBeach_2017-08-08_DSM_10cm.tif: Horizontal RMSE (m): 0.023; Horizontal MAE (m): 0.018; Horizontal accuracy at the 95 percent confidence level (m): 0.040; Total horizontal accuracy estimate at the 95 percent confidence level, including GPS uncertainty (m): 0.050;
    It should be noted that this error estimate is for areas of bare ground where GCPs were placed. Additional sources of error such as poor image-to-image point matching due to vegetation or uniform substrate texture (such as sand with uniform coloration) resulting in poor surface reconstruction may cause localized errors in some portions of the point clouds to exceed this estimate.
  3. How accurate are the heights or depths?
    For each DSM, vertical accuracy was estimated using two methods to compare the DSM vertical elevations to concurrently collected real-time kinematic (RTK) GPS measurements.
    The first method used a comparison of ground control point (GCP) positions measured with PPK GPS measurements to their SfM-estimated positions. Due to the time-intensive process of placing GCPs in the field, all available GCPs were used for registration and camera optimization in the SfM processing workflow during the creation of the final DSM. To evaluate the vertical positional accuracy of the final SfM alignments, each GCPs was disabled one at a time using a python script to create a 'temporary check point'. With a single GCP temporarily disabled, camera optimization was performed with all lens parameters fixed, and all other GCPs enabled. The residual errors of the check point relative to its GPS-measured position were recorded. After all temporary check point iterations were complete, the root-mean-square error (RMSE) and mean-absolute error (MAE) were calculated. Following the Federal Geographic Data Committee (FGDC) National Standard for Spatial Data Accuracy guidelines, we use the RMSE to calculate the positional vertical accuracy at the 95 percent confidence level. To account for additional uncertainty in the GPS-measured positions of the GCPs (0.038 meters) we include this as an additional error term through summation in quadrature to arrive at an estimate of total positional vertical accuracy. The error statistics and vertical accuracy estimates for each of the DSMs are below:
    - FortStevens_2017-08-07_DSM_10cm.tif: Vertical RMSE (m): 0.018; Vertical MAE (m): 0.012; Mean vertical error (m): -0.001; Vertical accuracy at the 95 percent confidence level (m): 0.035; Total vertical accuracy estimate at the 95 percent confidence level, including GPS uncertainty (m): 0.052;
    - BensonBeach_2017-08-08_DSM_10cm.tif: Vertical RMSE (m): 0.028; Vertical MAE (m): 0.017; Mean vertical error (m): -0.006; Vertical accuracy at the 95 percent confidence level (m): 0.055; Total vertical accuracy estimate at the 95 percent confidence level, including GPS uncertainty (m): 0.067;
    It should be noted that this error estimate is 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 (such as sand with uniform coloration) resulting in poor surface reconstruction may cause localized errors in some portions of the point clouds to exceed this estimate.
    A second method was used to attempt to quantify the vertical errors in areas away from the GCPs, through comparison with concurrently collected backpack and ATV-mounted RTK GPS data (Stevens and others, 2021). The DSM elevations were compared to these measurements using bilinear interpolation at each GPS point to calculate the root-mean-square error (RMSE), mean-absolute error (MAE), and mean vertical error (bias). The error statistics and vertical accuracy estimates relative to the RTK-measured backpack and ATV RTK-GPS data for each of the DSMs are below:
    - FortStevens_2017-08-07_DSM_10cm.tif: Number of measurements: 9,229; Vertical RMSE relative to concurrently collected RTK GPS measurements (m): 0.058; Vertical MAE relative to concurrently collected RTK GPS measurements (m): 0.033; Mean vertical error (bias) relative to concurrently collected RTK GPS measurements (m): -0.011 (DSM higher than RTK GPS measurements);
    - BensonBeach_2017-08-08_DSM_10cm.tif: Number of measurements: 20,345; Vertical RMSE relative to concurrently collected RTK GPS measurements (m): 0.045; Vertical MAE relative to concurrently collected RTK GPS measurements (m): 0.027; Mean vertical error (bias) relative to concurrently collected RTK GPS measurements (m): -0.008 (DSM higher than RTK GPS measurements);
    These slightly RMSE are due in part to the less precise nature of the backpack and ATV-mounted GPS measurements used as check points for this process. However, these comparisons do provide a more conservative, spatially distributed estimate of the true accuracy of the elevation models than the GCP check point method. We present both estimates here to provide the end-user with a more complete understanding of the accuracy of the final data products.
  4. Where are the gaps in the data? What is missing?
    Dataset is considered complete for the information presented, as described in the abstract. For the purpose of creating the final DSMs areas of data artifacts caused by waves and water in the surf zone, and ponded water on the beach, or areas of uniform color and texture were removed from the data by visual analysis and clipping. Users are advised to read the rest of the metadata record carefully for additional details.
  5. How consistent are the relationships among the observations, including topology?
    Accuracy tests were performed on these data to estimate positional accuracy. These tests are discussed in the Positional Accuracy section of the metadata. Some areas of noise resulting from waves and water in the surf zone, standing water, or areas of uniform color and texture were manually masked and removed from the final product. Some noise may remain near boundaries of the domain or near water and should be treated with caution.

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 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. This information is not intended for navigation purposes.
  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 DSMs are available as Cloud Optimized GeoTIFF files.
  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.
  4. How can I download or order the data?
  5. What hardware or software do I need in order to use the data set?
    These data can be viewed with GIS software or other software capable of displaying geospatial raster data.

Who wrote the metadata?

Dates:
Last modified: 23-Jun-2023
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_P9BVTVAW/FortStevens_BensonBeach_2017-08_DSM_metadata.faq.html>
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