Terrestrial lidar data from northern Monterey Bay, California, September 2017

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Frequently anticipated questions:

What does this data set describe?

Title:
Terrestrial lidar data from northern Monterey Bay, California, September 2017
Abstract:
This part of the data release presents topography data from northern Monterey Bay, California collected in September 2017 with a terrestrial lidar scanner.
Supplemental_Information:
Additional information about the field activities from which these data were derived are available online at:
http://cmgds.marine.usgs.gov/fan_info.php?fan=2017-678-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., and Snyder, Alexander G., 2017, Terrestrial lidar data from northern Monterey Bay, California, September 2017: data release DOI:10.5066/F76H4GCW, U.S. Geological Survey, Pacific Coastal and Marine Science Center, Santa Cruz, California.

    Online Links:

    This is part of the following larger work.

    Stevens, Andrew W., Logan, Joshua B., Snyder, Alexander G., Hoover, Daniel J., Barnard, Patrick L., and Warrick, Jonathan A., 2017, Beach topography and nearshore bathymetry of northern Monterey Bay, California: data release DOI:10.5066/F76H4GCW, U.S. Geological Survey, Santa Cruz, CA.

    Online Links:

  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -122.025434
    East_Bounding_Coordinate: -121.946858
    North_Bounding_Coordinate: 36.973293
    South_Bounding_Coordinate: 36.959741
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date: 20-Sep-2017
    Ending_Date: 21-Sep-2017
    Currentness_Reference:
    ground condition at time data were collected
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: comma-delimited text
  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. It contains the following vector data types (SDTS terminology):
      • Point (3377223)
    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 0.001
      Ordinates (y-coordinates) are specified to the nearest 0.001
      Planar coordinates are specified in Meter
      The horizontal datum used is NAD83 (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?
    Attribute Table
    Table containing attribute information associated with the dataset (Source: Producer defined)
    x
    East coordinate of data point relative to the North American Datum of 1983 (2011 realization), projected in the Universal Transverse Mercator (UTM), Zone 10 North, meters, coordinate system (Source: Producer Defined)
    Range of values
    Minimum:586759.297
    Maximum:593738.744
    Units:meters
    y
    North coordinate of data point relative to the North American Datum of 1983 (2011 realization), projected in the Universal Transverse Mercator (UTM), Zone 10 North, meters, coordinate system (Source: Producer defined)
    Range of values
    Minimum:4090850.169
    Maximum:4092427.785
    Units:meters
    z
    Height in meters of data point with reference to the North American Vertical Datum of 1988. (Source: Producer defined)
    Range of values
    Minimum:0.343
    Maximum:6.791
    Units:meters
    R
    Red pixel value from co-registered digital camera for each data point (Source: Producer defined)
    Range of values
    Minimum:0
    Maximum:255
    Units:unitless digital value
    G
    Green pixel value from co-registered digital camera for each data point (Source: Producer defined)
    Range of values
    Minimum:0
    Maximum:255
    Units:unitless digital value
    B
    Blue pixel value from co-registered digital camera for each data point (Source: Producer defined)
    Range of values
    Minimum:0
    Maximum:255
    Units:unitless digital value

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
    • Alexander G. Snyder
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
    Joshua B. Logan
    U.S. Geological Survey, Pacific Coastal and Marine Science Center
    Physical Scientist
    2885 Mission St.
    Santa Cruz, CA
    USA

    831-460-7519 (voice)
    jlogan@usgs.gov

Why was the data set created?

Data were obtained to document changes in shoreline position and coastal morphology as they relate to episodic (storms), seasonal, interannual, and longer (for example, El Niño) processes. 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 and shallow-water bathymetric features.

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: 21-Sep-2017 (process 1 of 3)
    Terrestrial lidar data were collected between September 20 and 21, 2017 using a tripod-mounted Riegl VZ-1000 lidar scanner. For each area surveyed, the scanner was placed at several positions which were selected to provide maximum line-of-sight coverage of the area of interest. Scans were typically conducted in panoramic mode, creating a detailed point cloud of all unobstructed surfaces in a 360 degree view of the scanner. Each individual scan typically contains 20 million or more precise point measurements. At each scan position, co-registered photographic imagery was also collected with a scanner mounted DSLR camera. Scanner registration was performed by placing four or more cylindrical or flat reflective tripod-mounted targets in view of the scanner. The positions of these reflectors were measured using survey grade GNSS, and used in post-processing to register each point cloud into a projected coordinate system.
    Date: 05-Dec-2017 (process 2 of 3)
    Initial data processing of the terrestrial lidar data was conducted using Riegl RiscanPro software. Each scan position and point cloud was registered using the GNSS-measured positions of the tripod-mounted reflectors. The quality of the registration was visually compared against adjacent registered point clouds, and concurrently collected topographic GNSS data. In the unlikely case that initial registration appeared to be inaccurate either due to poor GNSS precision, or poor reflector geometry, a point cloud fitting process called 'Multi-Station Adjustment (MSA)' was used to adjust the spatial registration to match adjacent point clouds. After registration was completed, the point clouds were colorized using RGB pixel values from the co-registered photographic imagery. The point clouds were then hand-edited to remove erroneous data points below the true ground surface caused by reflections on wet sand or water. Additional noise from water, breaking surf, haze, and objects within the point cloud were also removed by hand editing. The point clouds were then exported to comma delimited (.csv) format and converted into LAS format and processed using the LAStools software suite. A batch script was used to: 1) clip the LAS files to the areas of interest, 2) perform a range filter to remove all points further than 700 meters away from the scanner, 3) thin the point cloud to an average spacing of 5 centimeters to reduce point density, and 4) perform a classification algorithm to detect ground points and remove objects and vegetation from the point cloud. At this point a final visual check on the remaining points was performed to verify and correct any misclassification of ground surfaces. To produce the final output files all classified ground points were thinned using the lowest elevation point in 10 centimeter cells, and the resulting points were exported to a comma delimited (.csv) format.
    Date: 19-Oct-2020 (process 3 of 3)
    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?

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?
    Because the terrestrial lidar scanner rotates around the vertical axis during data collection, horizontal errors in the collected measurements are dependent on the range of each measurement from the sensor. To limit errors caused by long-range returns, only measurements within a range of 700 meters of each scan position were used for the final data product. Typical registration errors in the horizontal angle reported during point cloud registration for these data were found to be below 0.01 degrees, suggesting a maximum horizontal error of about 1.7 cm at a range of 100 meters, up to 12.2 cm at 700 meters. Because the majority of measurements in each point cloud are made near the scanner, it is estimated that average horizontal accuracy of the measurements is less than 7 cm (equivalent to 0.01 degrees of error at range of 400 meters).
  3. How accurate are the heights or depths?
    The vertical accuracy of the terrestrial lidar data was tested by comparing the final cleaned point cloud elevation values to concurrently collected topographic GNSS data. The RMS errors calculated for the vertical differences between these data and the point cloud data were typically found to be less than or equal to about 7 cm.
  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?
    All data falls within expected ranges.

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 navigational purposes.
  1. Who distributes the data set? (Distributor 1 of 1)
    U.S. Geological Survey - Science Base
    U.S. Geological Survey
    Denver Federal Center, Building 810, Mail Stop 302
    Denver, CO
    USA

    1-888-275-8747 (voice)
    sciencebase@usgs.gov
  2. What's the catalog number I need to order this data set? Topography data are available as a comma-delimited text files (mb17_sept_tls_capitola.csv; mb17_sept_tls_santacruz.csv), along with associated 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?

Who wrote the metadata?

Dates:
Last modified: 19-Oct-2020
Metadata author:
Joshua B. Logan
U.S. Geological Survey, Pacific Coastal and Marine Science Center
Physical Scientist
2885 Mission St.
Santa Cruz, CA
USA

831-460-7519 (voice)
astevens@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_F76H4GCW/mb17_sept_tls_metadata.faq.html>
Generated by mp version 2.9.50 on Tue Sep 21 18:17:10 2021