Topographic point cloud for the intertidal zone at Post Point, Bellingham Bay, WA, 2019-06-06

Frequently anticipated questions:

• What does this data set describe?
  1. How might this data set be cited?
  2. What geographic area does the data set cover?
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
  5. What is the general form of this data set?
  6. How does the data set represent geographic features?
  7. How does the data set describe geographic features?
• Who produced the data set?
  1. Who are the originators of the data set?
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
• Why was the data set created?
• How was the data set created?
  1. From what previous works were the data drawn?
  2. How were the data generated, processed, and modified?
  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?
  2. How accurate are the geographic locations?
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
  5. How consistent are the relationships among the data, including topology?
• How can someone get a copy of the data set?
  1. Are there legal restrictions on access or use of the data?
  2. Who distributes the data?
  3. What's the catalog number I need to order this data set?
  4. What legal disclaimers am I supposed to read?
  5. How can I download or order the data?
• Who wrote the metadata?

What does this data set describe?

1. How might this data set be cited?
   Logan, Joshua B., Grossman, Eric E., VanArendonk, Nathan R., and Maverick, Avery F.G., 20210222, Topographic point cloud for the intertidal zone at Post Point, Bellingham Bay, WA, 2019-06-06: data release DOI:10.5066/P94LH20J, U.S. Geological Survey, Pacific Coastal and Marine Science Center, Santa Cruz, California.

   Online Links:

   • https://doi.org/10.5066/P94LH20J
   • https://www.sciencebase.gov/catalog/item/5ef522a582ced62aaae6a015

   This is part of the following larger work.
   Logan, Joshua B., Grossman, Eric E., VanArendonk, Nathan R., and Maverick, Avery F.G., 2021, Aerial imagery and structure-from-motion data products from UAS survey of the intertidal zone at Post Point, Bellingham Bay, WA, June 2019: data release DOI:10.5066/P94LH20J, U.S. Geological Survey, Pacific Coastal and Marine Science Center, Santa Cruz, CA.

   Online Links:

   • https://doi.org/10.5066/P94LH20J
   • https://www.sciencebase.gov/catalog/item/5f2c568b82ceae4cb3c2cffc

2. What geographic area does the data set cover?

   West_Bounding_Coordinate: -122.5201
   East_Bounding_Coordinate: -122.5156
   North_Bounding_Coordinate: 48.7204
   South_Bounding_Coordinate: 48.7113
   

3. What does it look like?

   https://www.sciencebase.gov/catalog/file/get/5ef522a582ced62aaae6a015?name=PostPoint_2019-06-06_pointcloud_browse.jpg (JPEG)

   Perspective view of the Post Point topographic point cloud from the 2019-06-06 UAS survey.

4. Does the data set describe conditions during a particular time period?

   Calendar_Date: 06-Jun-2019

   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) (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 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?

   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) 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
   • Eric E. Grossman
   • Nathan R. VanArendonk
   • Avery F.G. Maverick
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 to characterize the morphology, substrate composition and roughness of intertidal areas to support modeling of coastal storm and wave impacts with sea-level rise as part of the USGS Puget Sound Coastal Storm Modeling System (PS-CoSMoS). The data are also intended to be used to model and evaluate sediment transport and its effects on coastal habitats, a focus of the USGS Coastal Habitats in Puget Sound Project (CHIPS) and its partners to inform resource management and adaptive planning for our Nation's coasts.

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: 06-Jun-2019 (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. The UAS was flown on pre-programmed autonomous flight lines. Flights F01, F02, and F03 were flown at an approximate altitude of 70 meters above ground level (AGL); flights F04 and F05 were flown at an approximate altitude of 35 meters AGL. The flight lines were oriented roughly shore-parallel and were spaced to provide approximately 70 percent overlap between images from adjacent lines. After the flight lines were completed some additional imagery was collected in manual flight mode to fill in additional areas and to collect redundant imagery with the camera sensor at different orientations to improve lens-model reconstruction. The camera was triggered at 1 Hz using a built-in intervalometer and was programmed to simultaneously acquire imagery in both JPG and camera raw (Adobe DNG) formats. 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. 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: 06-Jun-2019 (process 2 of 4)

   Ground control was established using ground control points (GCPs) consisting of small square tarps with black-and-white cross patterns and temporary chalk 'X' marks placed on the ground surface throughout the survey area. The GCP positions were measured using survey-grade GPS receivers operating in post-processed-kinematic (PPK) 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 PPK corrections were referenced to a Continuously Operating Reference (CORS) GPS base station ('BELI') located approximately 5 kilometers from the study area operated by the Washington State Reference Network (WSRN). 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: 2019 (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 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 a custom Python script which processes the GPS data from the UAS telemetry log and calls the command-line 'exiftool' 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 this survey, +00:00:02 (2 seconds) were added to the image timestamp 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 intertidal zone at Post Point, Bellingham Bay, Bellingham, Washington, USA, from USGS survey 2019-623-FA." ^ -Caption-Abstract="Intertidal zone at Post Point, Bellingham Bay, Bellingham, Washington, USA, from USGS survey 2019-623-FA." ^ -Caption="Aerial image of the intertidal zone at Post Point, Bellingham Bay, Bellingham, Washington, USA, from USGS survey 2019-623-FA." ^ -sep ", " ^ -keywords="Marine Nearshore Intertidal, Post Point, Bellingham Bay, Bellingham, Washington, 2019-623-FA, Unmanned Aircraft System, UAS, drone, aerial imagery, U.S. Geological Survey, USGS, Pacific Coastal and Marine Science Center" ^ -comment="Low-altitude aerial image from USGS Unmanned Aircraft System (UAS) survey 2019-623-FA." ^ -Credit="U.S. Geological Survey" ^ -Contact="pcmsc_data@usgs.gov" ^ -Artist="U.S. Geological Survey, 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: 2019 (process 4 of 4)

   Structure-from-motion (SfM) processing techniques were used to create the point clouds 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. Markers were manually placed for GCPs that consisted of chalk 'X' marks. 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. A Digital Surface Model (DSM) with a native resolution of 3.57 centimeters per pixel was created using all points in the dense point cloud for the main DSM. For the high-resolution data a DSM with a native resolution of 1.78 centimeters per pixel was created using all points in the high-resolution dense point cloud. 7. An RGB orthomosaic with a native resolution of 1.84 centimeters per pixel was created using the main DSM as the orthorectification surface. For the high-resolution data an RGB orthomosaic with a native resolution of 0.92 centimeters per pixel was created using the high-resolution DSM as the orthorectification surface. 8. An exterior boundary was digitized using the orthomosaics as a reference and was used as a clipping mask to exclude areas of water, obvious edge artifacts, and large areas of interpolation. 9. The point clouds were exported in LAZ format. 10. LAStools 'lasclip' was used to set the classification of all points falling within the horizontal bounds of the water clipping mask shapefile 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

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?
   Horizontal accuracy was estimated by comparing SfM-derived ground control point (GCP) positions to PPK GPS measurements. 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 point clouds. To evaluate the horizontal positional accuracy of the point clouds after processing was completed, a subset of GCPs was disabled one-at-a-time using a python script to create 'temporary check points'. 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. For the main survey area point cloud (files contained in PostPoint_2019-06-06_pointcloud.zip), the resulting horizontal RMSE was 0.018 meters (MAE 0.015 meters), and for the high-resolution Post Point point cloud (files contained in PostPointHighRes_2019-06-06_pointcloud.zip), the resulting horizontal RMSE was 0.030 meters (MAE 0.027 meters). The addition of the estimated horizontal GPS uncertainty (0.020 meters) in quadrature results in a total accuracy estimate of 0.027 meters for the main resolution point cloud, and 0.036 meters for the high-resolution point cloud. 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) 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?
   Vertical accuracy was estimated by comparing SfM-derived ground control point (GCP) positions to PPK GPS measurements. These 'check points' consisted of GCPs which were temporarily disabled after the completion of the SfM processing workflow. 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 point cloud. To evaluate the vertical positional accuracy of the point cloud, a subset of GCPs was disabled one-at-a-time using a python script to create 'temporary check points'. 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. For the main survey area point cloud (files contained in PostPoint_2019-06-06_pointcloud.zip), the resulting vertical RMSE was 0.040 meters (MAE 0.030 meters), and for the high-resolution Post Point point cloud (files contained in PostPointHighRes_2019-06-06_pointcloud.zip), the resulting vertical RMSE was 0.042 meters (MAE 0.034 meters). The addition of the estimated vertical GPS uncertainty (0.030 meters) in quadrature results in a total accuracy estimate of 0.050 meters for the main resolution point cloud, and 0.052 meters for the high-resolution point cloud. 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) resulting in poor surface reconstruction may cause localized errors in some portions of the point clouds to exceed this 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?
   • Availability in digital form:

     Data format:	These zip files contain point cloud data in LAZ format (LAS 1.2 specification). in format LAZ (version LAS 1.2) Size: 1180
     Network links:	https://www.sciencebase.gov/catalog/file/get/5ef522a582ced62aaae6a015?name=PostPoint_2019-06-06_pointcloud.zip https://www.sciencebase.gov/catalog/item/5ef522a582ced62aaae6a015 https://doi.org/10.5066/P94LH20J

     Data format:	These zip files contain point cloud data in LAZ format (LAS 1.2 specification). in format LAZ (version LAS 1.2) Size: 1120
     Network links:	https://www.sciencebase.gov/catalog/file/get/5ef522a582ced62aaae6a015?name=PostPointHighRes_2019-06-06_pointcloud.zip https://www.sciencebase.gov/catalog/item/5ef522a582ced62aaae6a015 https://doi.org/10.5066/P94LH20J

   • Cost to order the data: None.

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: 22-Feb-2021

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)