Digital Surface Models (DSMs) of the Whale's Tail Marsh region, South San Francisco Bay, CA

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Frequently anticipated questions:

What does this data set describe?

Title:
Digital Surface Models (DSMs) of the Whale's Tail Marsh region, South San Francisco Bay, CA
Abstract:
This portion of the data release presents digital surface models (DSM) of the Whale's Tail Marsh region of South San Francisco Bay, CA. The DSMs have resolutions of 5 centimeters per pixel and were derived from structure-from-motion (SfM) processing of repeat aerial imagery collected from fixed-wing aircraft. Unlike a digital elevation model (DEM), a DSM represents the elevation of the highest object within the bounds of a cell. Vegetation, structures, and other objects have not been removed from the data. The raw imagery used to create these elevation models was acquired from an approximate altitude of 427 meters (1,400 feet) above ground level (AGL), using a Hasselblad A6D-100c camera fitted with an HC 80 lens, resulting in a nominal ground-sample-distance (GSD) of 2.5 centimeters per pixel. The acquisition flight lines were designed to provide approximately 50 percent overlap between adjacent flight lines (sidelap), with approximately 70 percent overlap between sequential images along the flight line (forelap). Survey control was established using an onboard camera-synchronized dual-frequency GPS system as well as ground control points (GCPs) distributed throughout the survey area and measured using survey-grade post-processed kinematic (PPK) GPS. Both the data from the onboard GPS and from the GPS used to measure the GCPs were post-processed using a nearby Continuously Operating Reference Station (CORS) station operated by the National Geodetic Survey (NGS). Structure-from-motion processing of these data was conducted using a "4D" processing workflow in which imagery from each of the different acquisition dates were co-aligned in order to increase relative spatial precision between the final data products. The resulting DSMs 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=2021-624-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., Winklerprins, Lukas T., and Lacy, Jessica R., 20230508, Digital Surface Models (DSMs) of the Whale's Tail Marsh region, South San Francisco Bay, CA: data release DOI:10.5066/P9L9R2VS, 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., Winklerprins, Lukas T., and Lacy, Jessica R., 2023, Structure-from-motion derived orthomosaic imagery and digital surface models (DSMs) from the intertidal region at Whale's Tail Marsh, South San Francisco Bay, CA: data release DOI:10.5066/P9L9R2VS, U.S. Geological Survey, Pacific Coastal and Marine Science Center, Santa Cruz, CA.

    Online Links:

    Other_Citation_Details:
    Suggested Citation: Logan, J.B., Winklerprins, L.T., and Lacy, J.R., 2023, Structure-from-motion derived orthomosaic imagery and digital surface models (DSMs) from the intertidal region at Whale's Tail Marsh, South San Francisco Bay, CA: U.S. Geological Survey data release, https://doi.org/10.5066/P9L9R2VS.
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -122.15222
    East_Bounding_Coordinate: -122.11319
    North_Bounding_Coordinate: 37.61345
    South_Bounding_Coordinate: 37.57572
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/630807e2d34e3b967a8c15d1?name=WhaleTailMarsh_DSM_browse_image.jpg&allowOpen=True (JPEG)
    Color-shaded relief image of south Whale's Tail Marsh DSM (2022-02-10)
  4. Does the data set describe conditions during a particular time period?
    Calendar_Date: 30-May-2021
    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: Universal Transverse Mercator
      Universal_Transverse_Mercator:
      UTM_Zone_Number: 10
      Transverse_Mercator:
      Scale_Factor_at_Central_Meridian: 0.9996
      Longitude_of_Central_Meridian: -123.0
      Latitude_of_Projection_Origin: 0.0
      False_Easting: 500000.0
      False_Northing: 0.0
      Planar coordinates are encoded using row and column
      Abscissae (x-coordinates) are specified to the nearest 0.050
      Ordinates (y-coordinates) are specified to the nearest 0.050
      Planar coordinates are specified in meters
      The horizontal datum used is NAD83 (National Spatial Reference System 2011) (EPSG:1116).
      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 GEOID18
      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:-4.433
    Maximum:7.343

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
    • Lukas T. Winklerprins
    • Jessica R. Lacy
  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 are intended to be used to characterize the seasonal patterns and rates of change in the position and morphology of the Whale's Tail marsh in South San Francisco Bay, in California.

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: 19-May-2022 (process 1 of 5)
    Aerial imagery was acquired by the 111th Group, Inc. from a fixed-wing aircraft. Acquisition times were planned in advance to coincide with low tide to maximize the extent of the subaerially exposed portions of the marsh and mud-flats. The imagery was acquired from an approximate altitude of 427 meters (1,400 feet) above ground level (AGL) using a Hasselblad A6D-100c camera with an HC 80 lens mounted in a nadir orientation, resulting in a nominal ground-sample-distance (GSD) of 2.5 centimeters per pixel. The acquisition flight lines were designed to provide approximately 50 percent overlap between adjacent flight lines (sidelap), with approximately 70 percent overlap between sequential images along the flight line (forelap). A camera-synchronized onboard dual-frequency GPS receiver was used to record the precise shutter time and position of each image. The acquisition dates and times were as follows:
    2021-05-30 18:12 - 18:38 (UTC) 2021-09-09 16:10 - 16:38 (UTC) 2021-11-14 22:19 - 22:42 (UTC) 2022-02-10 23:02 - 23:27 (UTC) 2022-05-19 17:46 - 18:46 (UTC) Person who carried out this activity:
    Patrick Belanger
    The 111th Group Inc
    13025 Murphy Ave. Suite 100
    San Martin, CA

    408-683-9111 (voice)
    pat@the111th.com
    Date: 2022 (process 2 of 5)
    The raw aerial images were converted from 3FR to FFF images using the Hasselblad Phocus software package. The software lens corrections were performed for vignetting and chromatic aberration, but they were not performed for lens distortion. Exposure adjustments of up to +1.0 EV were performed on the images from some of the image acquisitions to increase the overall exposure on the imagery. Final images were exported using the JPG Max setting to create high-quality JPG images with low compression artifacts. Person who carried out this activity:
    Joshua Logan
    U.S. Geological Survey, Pacific Coastal and Marine Science Center
    2885 Mission Street
    Santa Cruz, CA

    831-460-7519 (voice)
    jlogan@usgs.gov
    Date: 2022 (process 3 of 5)
    The onboard camera-synchronized GPS data were post-processed using kinematic post-processing (PPK) using the Novatel Waypoint Grafnav software package. The P222 continuously operating reference station (CORS) operated by the National Geodetic Survey (NGS) approximately 7 kilometers southeast of the survey area was used for post-processing. After PPK processing, the precise position of each image was interpolated along the GPS trajectory using GPS-synchronized camera-shutter event marks in Grafnav. The precise positions of each image were then exported to a csv file for use in structure from motion processing software. Person who carried out this activity:
    Joshua Logan
    U.S. Geological Survey, Pacific Coastal and Marine Science Center
    2885 Mission Street
    Santa Cruz, CA

    831-460-7519 (voice)
    jlogan@usgs.gov
    Date: 05-Oct-2022 (process 4 of 5)
    Ground control was established using ground control points (GCPs) consisting of small square tarps with black-and-white cross patterns placed on the ground surface throughout the survey area, as well as painted "X" marks on objects such as rocks or large logs, which were expected to be stable during the course of the project. The GCP positions were measured using survey-grade GPS receivers placed on fixed height tripods, using a static occupation time of 1 minute. The GPS positions were post-processed using kinematic post-processing (PPK) using the P222 continuously operating reference station (CORS) operated by the National Geodetic Survey (NGS) approximately 7 kilometers southeast of the survey area. The GCPs were periodically maintained and re-visited throughout the course of the project to ensure stability and visibility in the imagery. The dates of the GCP surveys were: 2021-05-19, 2021-07-28, 2021-11-01, 2022-02-04, 2022-05-18, and 2022-10-05. Person who carried out this activity:
    Joshua Logan
    U.S. Geological Survey, Pacific Coastal and Marine Science Center
    2885 Mission Street
    Santa Cruz, CA

    831-460-7519 (voice)
    jlogan@usgs.gov
    Date: 2022 (process 5 of 5)
    Structure-from-motion (SfM) processing techniques were used to create point clouds, DSMs, and orthomosaic images in the Agisoft Metashape software package using the following workflow: 1. Imagery from each acquisition date was imported into a single processing group (also known as a chunk in Agisoft), and separated into different camera (sensor) groups. Precise positions from the onboard PPK GPS data were imported to provide precise camera positions for each image. Accuracy for the camera positions was set to 0.250 m. 2. Image alignment was performed using the 4D technique, in which all imagery in project are co-aligned to improve relative precision between the images from each acquisition date. The following alignment parameters were used: Accuracy: 'high'; Pair selection: 'reference', 'generic'; Key point limit: 0 (unlimited); Tie point limit: 0 (unlimited). 3. Ground control point (GCPs) positions were imported and manually placed on all imagery; accuracy for GCP markers was set to 0.050 meters. 4. Sparse point cloud error reduction was conducted using an automated script to perform iterative gradual selection and camera optimization (Logan and others, 2022). Lens calibration parameters f, cx, cy, k1, k2, k3, p1, and p2 were included in the optimization. 5. The aligned imagery from each acquisition date was divided into single-date groups (chunks) for product generation. 6. Dense point clouds were created for each acquisition date using the 'high' accuracy setting, with 'aggressive' depth filtering. 7. Digital Surface Models (DSM) were created for each acquisition date using the dense point clouds, and were exported to GeoTIFF files with 5-centimeter pixel resolutions. 8. RGB orthomosaic images were created using the DSMs as the orthorectification surfaces, and were exported to GeoTIFF files with 2.5-centimeter pixel resolutions. 9. The DSMs were divided into north and south tiles to reduce individual file sizes. The DSM from 2022-05-19, which includes a large portion of a pond to the northeast of the Whale's Tail marsh, was also divided into a northeast tile. Tiling was done using the gdalwarp utility in the GDAL software package. 10. Exterior and interior boundaries were manually digitized in QGIS using both the orthomosaics and the DSMs (displayed as a hillshade) as visual references. The boundaries were used as clipping masks to exclude areas of noise resulting from water, edge artifacts, and large areas of interpolation. Due to the complex nature of the ponded water in some areas of the mud flats represented in the data, it was not possible to remove all areas of noise in the DSMs. The gdalwarp utility in the GDAL software package was used to clip the DSMs using the clipping masks. 11. The DSMs were converted to cloud optimized GeoTIFF format for compatibility with cloud storage services using the gdal_translate utility in the GDAL software package. Compression was applied using the lossless DEFLATE compression method, and 'NoData' value was set to -32767. 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, J.B., Wernette, P.A., and Ritchie, A.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).
    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?
    Horizontal accuracy was estimated by comparing ground control point (GCP) positions measured with PPK GPS measurements to their SfM-estimated positions. For each data set (images from a single acquisition date), five or more GCP positions were used as GCP check points. These positions were marked in the imagery, but they were left disabled (unchecked) during image alignment and sparse point cloud error reduction. The residual errors of the SfM-estimated positions of the check points relative to their GPS-measured position were used to calculate the root-mean-square error (RMSE), mean-absolute error (MAE), and mean error (bias). Following the Federal Geographic Data Committee National Standard for Spatial Data Accuracy (1998) guidelines, we use the RMSE to calculate the horizontal positional accuracy at the 95 percent confidence level. To account for additional uncertainty in the GPS-measured positions of the GCPs (0.020 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:
    WhaleTailMarsh DSM 2021-05-30: Horizontal RMSE (m): 0.034 Horizontal MAE (m): 0.028 Mean error, north (m): 0.015 Mean error, east (m): 0.003 Horizontal accuracy at the 95 percent confidence level (m): 0.058 Total horizontal accuracy estimate at the 95 percent confidence level, including GPS uncertainty (m): 0.062
    WhaleTailMarsh DSM 2021-09-09: Horizontal RMSE (m): 0.039 Horizontal MAE (m): 0.035 Mean error, north (m): 0.013 Mean error, east (m): 0.012 Horizontal accuracy at the 95 percent confidence level (m): 0.067 Total horizontal accuracy estimate at the 95 percent confidence level, including GPS uncertainty (m): 0.070
    WhaleTailMarsh DSM 2021-11-14: Horizontal RMSE (m): 0.046 Horizontal MAE (m): 0.043 Mean error, north (m): 0.010 Mean error, east (m): 0.008 Horizontal accuracy at the 95 percent confidence level (m): 0.079 Total horizontal accuracy estimate at the 95 percent confidence level, including GPS uncertainty (m): 0.081
    WhaleTailMarsh DSM 2022-02-10: Horizontal RMSE (m): 0.036 Horizontal MAE (m): 0.032 Mean error, north (m): 0.025 Mean error, east (m): 0.010 Horizontal accuracy at the 95 percent confidence level (m): 0.062 Total horizontal accuracy estimate at the 95 percent confidence level, including GPS uncertainty (m): 0.065
    WhaleTailMarsh DSM 2022-05-19: Horizontal RMSE (m): 0.039 Horizontal MAE (m): 0.036 Mean error, north (m): 0.029 Mean error, east (m): 0.007 Horizontal accuracy at the 95 percent confidence level (m): 0.067 Total horizontal accuracy estimate at the 95 percent confidence level, including GPS uncertainty (m): 0.070
    It should be noted that these accuracy estimates are for areas of bare ground or low vegetation in the locations where GCPs were placed. Although the GPS control on the image positions (from the post-processed camera-synchronized GPS) can reduce the need for on-the-ground control points, the overall accuracy of the final DSM may vary as a function of the distance to a measured ground control point. Areas where no ground control points were placed (Whale's Tail marsh north of Alameda Creek and any areas east of the unbreached north-south levy on the eastern edge of the marsh, as well as some areas along the marsh edge may have accuracies lower than these estimates. Additional sources of error such as poor image-to-image point matching due to vegetation or uniform substrate texture (such as mud) resulting in poor surface reconstruction may also cause additional localized errors in some portions of the DSM which exceed these estimates.
  3. How accurate are the heights or depths?
    Vertical accuracy was estimated by comparing ground control point (GCP) positions measured with PPK GPS measurements to their SfM-estimated positions. For each data set (images from a single acquisition date), five or more GCP positions were used as GCP check points. These positions were marked in the imagery, but they were left disabled (unchecked) during image alignment and sparse point cloud error reduction. The residual errors of the SfM-estimated positions of the check points relative to their GPS-measured position were used to calculate the root-mean-square error (RMSE), mean-absolute error (MAE), and mean error (bias). Following the Federal Geographic Data Committee National Standard for Spatial Data Accuracy (1998) guidelines, we use the RMSE to calculate the vertical positional 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 vertical accuracy. The error statistics and vertical accuracy estimates for each of the DSMs are below:
    WhaleTailMarsh DSM 2021-05-30: Vertical RMSE (m): 0.028 Vertical MAE (m): 0.026 Mean error, elevation (m, up): 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): 0.063
    WhaleTailMarsh DSM 2021-09-09: Vertical RMSE (m): 0.050 Vertical MAE (m): 0.039 Mean error, elevation (m, up): -0.017 Vertical accuracy at the 95 percent confidence level (m): 0.098 Total vertical accuracy estimate at the 95 percent confidence level, including GPS uncertainty (m): 0.103
    WhaleTailMarsh DSM 2021-11-14: Vertical RMSE (m): 0.014 Vertical MAE (m): 0.013 Mean error, elevation (m, up): 0.008 Vertical accuracy at the 95 percent confidence level (m): 0.027 Total vertical accuracy estimate at the 95 percent confidence level, including GPS uncertainty (m): 0.040
    WhaleTailMarsh DSM 2022-02-10: Vertical RMSE (m): 0.015 Vertical MAE (m): 0.013 Mean error, elevation (m, up): 0.003 Vertical accuracy at the 95 percent confidence level (m): 0.029 Total vertical accuracy estimate at the 95 percent confidence level, including GPS uncertainty (m): 0.042
    WhaleTailMarsh DSM 2022-05-19: Vertical RMSE (m): 0.015 Vertical MAE (m): 0.014 Mean error, elevation (m, up): -0.009 Vertical accuracy at the 95 percent confidence level (m): 0.030 Total vertical accuracy estimate at the 95 percent confidence level, including GPS uncertainty (m): 0.042
    It should be noted that these accuracy estimates are for areas of bare ground or low vegetation in the locations where GCPs were placed. Although the GPS control on the image positions (from the post-processed camera-synchronized GPS) can reduce the need for on-the-ground control points, the overall accuracy of the final DSM may vary as a function of the distance to a measured ground control point. Areas where no ground control points were placed (Whale's Tail marsh north of Alameda Creek and any areas east of the unbreached north-south levy on the eastern edge of the marsh, as well as some areas along the marsh edge may have accuracies lower than these estimates. Additional sources of error such as poor image-to-image point matching due to vegetation or uniform substrate texture (such as mud) resulting in poor surface reconstruction may also cause additional localized errors in some portions of the DSM which exceed these estimates.
  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 DSM, areas of noise resulting from standing water or areas of uniform color and texture were manually masked and removed from the final product. Remaining regions near boundaries of the domain or near standing water should be treated with caution.
  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 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 standing 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 Whale's Tail Marsh DSMs are available as Cloud Optimized GeoTIFF files accompanied by CSDGM FGDC-compliant metadata.
  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: 08-May-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_P9L9R2VS/WhaleTailMarsh_DSM_metadata.faq.html>
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