Topographic point cloud for the Liberty Island Conservation Bank Wildlands restoration site, Sacramento-San Joaquin Delta, California, 2018-10-23

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Frequently anticipated questions:

What does this data set describe?

Title:
Topographic point cloud for the Liberty Island Conservation Bank Wildlands restoration site, Sacramento-San Joaquin Delta, California, 2018-10-23
Abstract:
This portion of the data release presents a topographic point cloud of the Liberty Island Conservation Bank Wildlands restoration site in the Sacramento-San Joaquin Delta, derived from structure-from-motion (SfM) processing of aerial imagery collected with an Unmanned Aerial System (UAS) on 2018-10-23. The point cloud contains 380,296,568 points at an approximate point density of 323 point per square-meter. Each point contains an explicit horizontal and vertical coordinate, color, intensity, and classification. The point cloud is tiled into 500 x 500-meter tiles to reduce file size. The raw imagery used to create this point cloud was acquired using two UAS fitted with Ricoh GR II digital cameras global shutters. The UAS were flown on pre-programmed autonomous flight lines at an approximate altitude of 120 meters above-ground-level. The flight lines were oriented roughly east-west and were spaced to provide approximately 66 percent overlap between images from adjacent lines. The cameras were triggered at 1 Hz using a built-in intervalometer. The imagery was geotagged using positions from the UAS onboard single-frequency autonomous GPS. Ground control was established using twenty-four ground control points (GCPs) consisting of small square tarps with black-and-white cross patterns distributed throughout the mapping area. The GCP positions were measured using RTK GPS, with real-time corrections from a GPS base station located approximately 3 kilometers south of the study area.
Supplemental_Information:
Additional information about the field activity from which these data were derived is available online at:
http://cmgds.marine.usgs.gov/fan_info.php?fan=2018-676-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., Johnson, Cordell D., and Lacy, Jessica R., 20200817, Topographic point cloud for the Liberty Island Conservation Bank Wildlands restoration site, Sacramento-San Joaquin Delta, California, 2018-10-23: data release DOI:10.5066/P9GF8R1M, 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., Johnson, Cordell D., and Lacy, Jessica R., 2020, Aerial imagery and structure-from-motion derived data products from UAS survey of the Liberty Island Conservation Bank Wildlands restoration site, Sacramento-San Joaquin Delta, California, October 2018: data release DOI:10.5066/P9GF8R1M, 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: -121.6769
    East_Bounding_Coordinate: -121.6657
    North_Bounding_Coordinate: 38.3370
    South_Bounding_Coordinate: 38.3247
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/5eb210fc82cefae35a29c45d?name=Wildlands_2018-10-23_pointcloud_browse.PNG (PNG)
    Perspective view of Wildlands topographic point cloud from 2018-10-23 survey.
  4. Does the data set describe conditions during a particular time period?
    Calendar_Date: 23-Oct-2018
    Currentness_Reference:
    ground condition at time data were collected
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: point cloud digital data
  6. How does the data set represent geographic features?
    1. How are geographic features stored in the data set?
      This is a Point 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: 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 coordinate pair
      Abscissae (x-coordinates) are specified to the nearest 0.001
      Ordinates (y-coordinates) are specified to the nearest 0.001
      Planar coordinates are specified in meters
      The horizontal datum used is NAD83_National_Spatial_Reference_System_2011.
      The ellipsoid used is GRS 1980.
      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
      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?
    Entity_and_Attribute_Overview:
    The attribute information associated with point cloud follows the LAZ file standard. Attributes include location (northing, easting, and elevation in the NAD83(2011)/UTM zone 10N (EPSG:6339) horizontal and NAVD88 vertical coordinate systems), color (red, blue, and green components), intensity, and classification. All points are classified as 0 (unclassified), 7 (noise), or 9 (water).
    Entity_and_Attribute_Detail_Citation:
    American Society for Photogrammetry and Remote Sensing (ASPRS; 2013, https://www.asprs.org/committee-general/laser-las-file-format-exchange-activities.html) and Isenburg (2013, https://doi.org/10.14358/PERS.79.2.209)

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
    • Cordell D. Johnson
    • 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 were collected in support of ongoing field experiments and numerical modeling by the USGS and others, with funding from the U.S. Bureau of Reclamation, to improve our understanding of habitat quality, the influence on various landscape features on ecosystem function, and the effects of restoration actions in the Sacramento–San Joaquin Delta. These data are intended for science researchers, students, policy makers, and the general public.

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: 23-Oct-2018 (process 1 of 5)
    Aerial imagery was collected using two Department of Interior owned 3DR Solo quadcopters fitted with Ricoh GR II digital cameras featuring global shutters. The cameras were mounted using a fixed mount on the bottom of the UAS and oriented in a roughly nadir orientation. The UAS were flown on pre-programmed autonomous flight lines at an approximate altitude of 120 meters above-ground-level. The flight lines were oriented roughly east-west and were spaced to provide approximately 66 percent overlap between images from adjacent lines. The cameras were triggered at 1 Hz using a built in intervalometer, and were programmed to simultaneously acquire imagery in both JPG and camera raw (Adobe DNG) formats. Due to the limited UAS battery life, a total of 8 flights were required to achieve full coverage of the study area. The flights were conducted on 2018-10-23 between 18:21 and 20:35 Universal Coordinated Time (UTC) (11:21 and 13:35 Pacific Daylight Time (PDT)). Before each flight, the camera 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 individual flight were acquired with consistent camera settings. 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
    Date: 23-Oct-2018 (process 2 of 5)
    Ground control was established using twenty-four ground control points (GCPs) consisting of small square tarps with black-and-white cross patterns placed on the ground surface throughout the survey area. The GCP positions were measured using survey-grade GPS receivers operating in real-time-kinematic (RTK) mode. The GPS receivers were placed on short fixed-height tripods and set to occupy each GCP for a minimum occupation time of one-minute. The RTK corrections were referenced to a static GPS base station operating on a benchmark approximately 3 kilometers south of the survey area. The position of the benchmark was previously established using the average of three static GPS occupations (2017-06-26 to 2017-06-28) with durations between 4 and 8 hours, processed using the National Geodetic Survey (NGS) Online Positioning User Service (OPUS). 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: 2018 (process 3 of 5)
    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 or DNG)
    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 GeoSetter software. 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 smartphone app ('Emerald Time') showing accurate time from Network Time Protocol (NTP) servers. For RicohA no image time adjustment was needed; for RicohB, +00:00:02 (2 seconds) were added to the image time 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:7660), with elevation in meters relative to the WGS84 ellipsoid.
    Additional information was added to the EXIF using the command-line 'exiftool' software with the following command: exiftool ^ -P ^ -Copyright="Public Domain. Please credit U.S. Geological Survey." ^ -CopyrightNotice="Public Domain. Please credit U.S. Geological Survey." ^ -ImageDescription="Low-altitude aerial image of the Liberty Island Conservation Bank Wildlands restoration site, Cache Slough Complex, Sacramento-San Joaquin Delta, California, USA, from USGS survey 2018-676-FA" ^ -Caption-Abstract="Liberty Island Conservation Bank Wildlands restoration site, Cache Slough Complex, Sacramento-San Joaquin Delta, California, USA, from USGS survey 2018-676-FA" ^ -Caption="Liberty Island Conservation Bank Wildlands restoration site, Cache Slough Complex, Sacramento-San Joaquin Delta, California, USA, from survey 2018-676-FA" ^ -sep ", " ^ -keywords="Liberty Island, Liberty Island Conservation Bank, Wildlands restoration site, Cache Slough Complex, Sacramento-San Joaquin Delta, California, 2018-676-FA, Unmanned Aircraft System, UAS, aerial imagery, USGS, Pacific Coastal and Marine Science Center" ^ -comment="Low-altitude aerial image from USGS Unmanned Aircraft System (UAS) survey 2018-676-FA" ^ -Credit="U.S. Geological Survey" ^ -Contact="pcmsc_data@usgs.gov" ^ -Artist="Pacific Coastal and Marine Science Center" 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: 2018 (process 4 of 5)
    Structure-from-motion (SfM) processing techniques were used to create the topographic point cloud in the Agisoft Photoscan/Metashape software package using the following workflow: 1. Initial image alignment was performed with the following parameters - Accuracy: 'high'; Pair selection: 'reference', 'generic'; Key point limit: 0 (unlimited); Tie point limit: 0 (unlimited). 2. Sparse point cloud error reduction was performed using an iterative gradual selection and camera optimization process with the following parameters: Reconstruction Uncertainty: 10; Projection Accuracy: 3. Lens calibration parameters f, cx, cy, k1, k2, k3, p1, and p2 were included in the optimization. Additional sparse points obviously above or below the true surface were manually deleted after the last error reduction iteration. 3. Ground control points (GCPs) were automatically detected using the 'Cross (non-coded)' option. False matches were manually removed, and all markers were visually checked and manually placed or adjusted if needed. 4. Additional sparse point cloud error reduction was performed using an iterative gradual selection and camera optimization process with the following parameters: Reconstruction Error: 0.3. Lens calibration parameters f, cx, cy, k1, k2, k3, p1, and p2 were initially included in the optimization, but additional parameters k4, b1, b2, p3, and p4 were included once Reconstruction Error was reduced below 1 pixel. Additional 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. A dense point cloud was created using the 'high' accuracy setting, with 'aggressive' depth filtering. 6. Low-noise points were identified using the 'Classify Ground Points' tool in Agisoft with the following parameters: Max. Angle: 15 degrees; Max. Distance: 0.5 meters; Cell Size: 5 meters. Due to the prevalence of water, vegetation and tree cover some areas, it is not expected that this step identified all noise. 7. The point cloud was exported in 500x500-meter tiles using the LAZ format to reduce file sizes. 8. An exterior boundary was digitized and used as a clipping mask to exclude obvious edge artifacts and large areas of interpolation. 9. An initial Digital Surface Model (DSM) with a native resolution of 6.3 centimeters per-pixel was created using all points in the dense point cloud, except those classified as 'low-noise'. The DSM was exported to a GeoTIFF format with a 10-centimeter pixel resolution. 10. A water clipping mask was developed in ArcGIS by filtering elevation values below 1.6 meters and combining those with large areas of interpolation in the DSM (representing large areas of the original point cloud which had been classified as noise). The water clipping mask was converted to a polygon shapefile. 11. LAStools 'las2las' was used to reset the 'ground' classification to 'unclassified' due to the high likelihood of misclassification resulting from the prevalence of dense vegetation in the survey area. The horizontal and vertical coordinate reference system were also defined during this process. 12. LAStools 'lasclip' was used to set the classification of all points falling within the horizontal bounds of the water clipping mask as Class 9 ('water'). 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
    Date: 19-Oct-2020 (process 5 of 5)
    Edited metadata to add keywords section with USGS persistent identifier as theme keyword. No data were changed. Person who carried out this activity:
    U.S. Geological Survey
    Attn: VeeAnn A. Cross
    Marine Geologist
    384 Woods Hole Road
    Woods Hole, MA

    508-548-8700 x2251 (voice)
    508-457-2310 (FAX)
    vatnipp@usgs.gov
  3. What similar or related data should the user be aware of?
    Fregoso, Theresa A., Stevens, Andrew W., Wang, Rueen-Fang, Handley, Thomas, Dartnell, Peter, Lacy, Jessica R., Ateljevich, Eli, and Dailey, Evan T., 2020, Bathymetry, topography, and acoustic backscatter data, and a digital elevation model (DEM) of the Cache Slough Complex and Sacramento River Deep Water Ship Channel, Sacramento-San Joaquin Delta, California: U.S. Geological Survey, Pacific Coastal and Marine Science Center, Santa Cruz, California.

    Online Links:

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

  1. How well have the observations been checked?
    No formal attribute accuracy tests were conducted.
  2. How accurate are the geographic locations?
    All available GCPs were used in the SfM processing workflow. To evaluate horizontal positional accuracy a python script was used in Agisoft to iteratively disable selected GCPs one-at-a-time to create temporary 'check points'. With the check point disabled, a camera optimization was performed with all lens parameters fixed, and all other GCPs enabled. The residual errors of each 'check point' relative to its measured position were logged. After all iterations were complete, the root-mean-square error (RMSE) of all residuals was calculated. For this analysis a subset of eight interior GCPs (GCPs which were within the convex hull of all GCPs) were used, resulting in a horizontal RMSE of 0.076 meters. It should be noted that this estimate is for areas of low vegetation where GCPs were placed. Additional sources of error such as poor image-to-image point matching due to dense vegetation and resulting poor surface reconstruction may cause additional errors in some portions of the DSM which may exceed this uncertainty estimate.
  3. How accurate are the heights or depths?
    All available GCPs were used in the SfM processing workflow. To evaluate horizontal positional accuracy a python script was used in Agisoft to iteratively disable selected GCPs one-at-a-time to create temporary 'check points'. With the check point disabled, a camera optimization was performed with all lens parameters fixed, and all other GCPs enabled. The residual errors of each 'check point' relative to its measured position were logged. After all iterations were complete, the root-mean-square error (RMSE) of all residuals was calculated. For this analysis a subset of eight interior GCPs (GCPs which were within the convex hull of all GCPs) were used, resulting in a vertical RMSE of 0.107 meters. It should be noted that this estimate is for the vertical position of the vegetation canopy at the time of the survey only and not for the bare ground. Due to the dense vegetation in the survey area, the ground surface is not visible in much of the imagery and therefore not represented in the SfM reconstruction. Additional sources of error such as poor image-to-image point matching due to dense vegetation and resulting poor surface reconstruction may cause additional errors in some portions of the DSM which may exceed this uncertainty estimate.
  4. Where are the gaps in the data? What is missing?
    Dataset is considered complete for the information presented, as described in the abstract. 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?
    No formal logical accuracy tests were conducted.

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 topographic point clouds are available as LAZ 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?
    This zip file contains point cloud data in LAZ format (LAS 1.2 specification). The user must have software capable of uncompressing the .zip compressed file and displaying or processing the .laz format file.

Who wrote the metadata?

Dates:
Last modified: 19-Oct-2020
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_P9GF8R1M/Wildlands_2018-10-23_point_cloud.faq.html>
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