Structure-from-motion point cloud of Mud Creek, Big Sur, California, 2017-10-12

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Frequently anticipated questions:


What does this data set describe?

Title:
Structure-from-motion point cloud of Mud Creek, Big Sur, California, 2017-10-12
Abstract:
Presented here is a point cloud collected by the U.S. Geological Survey (USGS) using a UAS-mounted camera system, covering the area of the Mud Creek landslide on California State Route 1 (SR1), Mud Creek, Big Sur, California. The point cloud is referenced to previously published lidar data and contains RGB information as well as XYZ. Point cloud coordinates are in NAD83 UTM Zone 10 meters. Imagery was collected with a Ricoh GR camera in DNG format and processed using structure-from-motion photogrammetry with Agisoft PhotoScan version 1.2.8 through 1.3.2. Pointclouds were clipped to an AOI using LASTools. The AOI was created from a KMZ in Google Earth and transformed to a shapefile using ArcMap 10.5.
Supplemental_Information:
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?
    Ritchie, Andrew C., Warrick, Jonathan A., and Logan, Joshua B., 2019, Structure-from-motion point cloud of Mud Creek, Big Sur, California, 2017-10-12: data release DOI:10.5066/P973FQ3M, U.S. Geological Survey, Pacific Coastal and Marine Science Center, Santa Cruz, California.

    Online Links:

    This is part of the following larger work.

    Ritchie, Andrew C., Warrick, Jonathan A., and Logan, Joshua B., 2019, Topographic point clouds for the Mud Creek landslide, Big Sur, California from structure-from-motion photogrammetry from aerial photographs: data release DOI:10.5066/P973FQ3M, U.S. Geological Survey, Pacific Coastal and Marine Science Center, Santa Cruz, California.

    Online Links:

  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -121.43695799
    East_Bounding_Coordinate: -121.42370183
    North_Bounding_Coordinate: 35.87056698
    South_Bounding_Coordinate: 35.86081387
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
    Calendar_Date: 12-Oct-2017
    Currentness_Reference:
    ground condition
  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?
      Indirect_Spatial_Reference:
      Mud Creek, Monterey County, California. Located on California State Route 1 (SR1), 2 km (1 mi) south of Gorda, CA, and 57 km (35 mi) north of Cambria CA.
      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 0.1
      Ordinates (y-coordinates) are specified to the nearest 0.1
      Planar coordinates are specified in METERS
      The horizontal datum used is NAD83.
      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.
  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/UTM zone 10N (EPSG:26910) horizontal and NAVD88 vertical coordinate systems), color (red, blue, and green components), intensity, and classification. All points are classified as 0 (unclassified).
    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)
    • Andrew C. Ritchie
    • Jonathan A. Warrick
    • Joshua B. Logan
  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
    United States

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

Why was the data set created?

Data were collected to monitor an unstable area of the Big Sur coastline presenting a natural hazard to life, property, and navigation, as part of the USGS Remote Sensing Coastal Change (RSCC) Project. The area failed catastrophically on 20 May 2017 and subsequent data collection continued to monitor both the natural and human-modified evolution of the slide area.

How was the data set created?

  1. From what previous works were the data drawn?
    2016 USGS West Coast El-Nino lidar (WA, OR, CA) (source 1 of 2)
    Dewberry, 20170412, 2016 USGS lidar: West Coast El Nino (WA, OR, CA) point cloud files with orthometric vertical datum North American Vertical Datum of 1988 (NAVD88) using GEOID12B.

    Online Links:

    Other_Citation_Details:
    Type_of_Source_Media: Digital and/or Hardcopy
    Source_Contribution: ground control and error analysis
    2010 ARRA lidar: California Coastal Project (Zone 4) (source 2 of 2)
    Digital Mapping, Inc, 2011, 2010 ARRA lidar: California Coastal Project (Zone 4) point cloud files with orthometric vertical datum North American Vertical Datum of 1988 (NAVD88) using GEOID12B.

    Online Links:

    Other_Citation_Details:
    Type_of_Source_Media: Digital and/or Hardcopy
    Source_Contribution: ground control and error analysis
  2. How were the data generated, processed, and modified?
    Date: 2018 (process 1 of 1)
    1. Aerial imagery was collected using a USGS-operated UAS (3DR Solo) and a Ricoh GR camera, at approximately 100m altitude/distance from ground and 2 cm pixel resolution. Images were tagged with approximate location from flight control software, and 16 Ground Control Points (GCPs) were placed in the survey area and measured with GNSS to 0.02/0.03 cm accuracy (horizontal/vertical).
    2. Geotagged images containing imagery from the survey area were imported into Agisoft Photoscan Professional v. 1.4.2 software using the “Add photos” tool.
    3. The photos were processed through an initial alignment and optimization procedure using the following settings: Alignment - Accuracy: “High”; Pair selection: “Reference, generic”; Key point limit: 0 (unlimited); Tie point limit; 0 (unlimited). Optimization - Lens-calibration parameters f, cx, cy, k1, k2, k3, p1, and p2 were included; b1, b2, and higher-order parameters k4, p3, and p4 were not.
    4. The sparse point cloud (tie points; created as a result of photo alignment and optimization) was edited using an iterative error-reduction procedure to filter the data. This was done in several iterations of a process called "Gradual Selection" to first reduce reconstruction uncertainty (to a unitless value of 10) and then projection accuracy (to a weighted value of 3).
    5. Ground control points (GCPs) were surveyed on sixteen aerial targets placed in the lower landslide area, which were also visible in the aerial images (see larger work for specific methods).
    6. GCP location files, which assigned coordinates (northing, easting, and elevation in UTM Zone 10 North meters in NAD83 and NAVD88 coordinate systems) were imported, and markers were autodetected and/or manually placed on imagery where they were visible.
    7. Another round of "Gradual Selection" was done to reduce the reprojection error (to a value of 0.3 pixels).
    8. A dense point cloud was then created with the parameters "High" quality and "moderate" depth filtering.
    9. The dense point cloud was exported in LAZ format and clipped to a shapefile of the survey area using lastools with the following command:
    lasclip -i [input_file.laz] -poly [clip_shape.shp] -odir clipped -olaz
  3. What similar or related data should the user be aware of?
    Warrick, Jonathan A., Ritchie, Andrew C., Schmidt, Kevin M., Reid, Mark E., and Logan, Joshua B., 2019, Characterizing the catastrophic 2017 Mud Creek landslide, California, using repeat structure-from-motion (SfM) photogrammetry.

    Online Links:

    Other_Citation_Details:
    Warrick, J.A., Ritchie, A.C., Schmidt, K.M., Reid, M.E., and Logan, J.B., 2019, Characterizing the catastrophic 2017 Mud Creek landslide, California, using repeat structure-from-motion (SfM) photogrammetry: Landslides, doi:10.1007/s10346-019-01160-4

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?
    Ground control was derived from sixteen surveyed aerial target ground-control points located in the lower, accessible portion of the landslide area. Positions for these targets were derived from survey-grade global navigation satellite system (GNSS) measurements collected by USGS field crews during the flight data collection. Vertical and horizontal accuracies for these positions were 0.02 and 0.03 m for the GNSS measurements. While total estimated 3D uncertainty of 0.5 m is reported for the UAS and Plane-based surveys, this is likely to be the upper bound of the UAS survey error, and error will be lower in the lower slide area where the targets were placed.
  3. How accurate are the heights or depths?
    Ground control was derived from sixteen surveyed aerial target ground-control points located in the lower, accessible portion of the landslide area. Positions for these targets were derived from survey-grade global navigation satellite system (GNSS) measurements collected by USGS field crews during the flight data collection. Vertical and horizontal accuracies for these positions were 0.02 and 0.03 m for the GNSS measurements. While total estimated 3D uncertainty of 0.5 m is reported for the UAS and Plane-based surveys, this is likely to be the upper bound of the UAS survey error, and error will be lower in the lower slide area where the targets were placed.
  4. Where are the gaps in the data? What is missing?
    Data set 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?
    Coordinates recorded for each point in the point cloud describe discrete positions in space and the visual reflectance (in RGB values) at the time of capture. This final point cloud was checked for accuracy by rotating the point cloud to view from multiple angles to ensure that obvious spurious points do not cause artifacts in measurements or derivative products (DEM and Orthomosaic). Although some outlying points were eliminated during processing, there may still be points that do not represent ground features, but are instead artifacts generated by erroneous tie points or spurious matches in the photogrammetric process.

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.
  1. Who distributes the data set? (Distributor 1 of 1)
    U.S. Geological Survey
    Attn: GS 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?
  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: 18-Mar-2019
Metadata author:
U.S. Geological Survey, Pacific Coastal and Marine Science Center
Attn: PCMSC Science Data Coordinator
2885 Mission Street
Santa Cruz, CA
United States

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/westcoast/cencal/MudCr_BigSur_2017_10_12_UAS_metadata.faq.html>
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