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.
Horizontal_Positional_Accuracy:
Horizontal_Positional_Accuracy_Report:
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 DSM. To evaluate the horizontal positional accuracy of the DSM 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 Post Point 4-centimeter resolution DSM (PostPoint_2019-06-06_DSM_4cm.tif), the resulting horizontal RMSE was 0.018 meters (MAE 0.015 meters), and for the Post Point 2-centimeter resolution DSM (PostPoint_2019-06-06_DSM_2cm.tif), 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 4-centimeter resolution DSM, and 0.036 meters for the 2-centimeter resolution DSM. 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 DSM to exceed this estimate.
Vertical_Positional_Accuracy:
Vertical_Positional_Accuracy_Report:
Vertical accuracy was estimated using two methods to compare the DSM vertical elevations to concurrently collected post-processed kinematic (PPK) GPS measurements. The first method used a comparison of SfM-derived ground control point (GCP) positions to PPK GPS measurements at those points. 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 DSM. To evaluate the vertical positional accuracy of the DSM 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 Post Point 4-centimeter resolution DSM (PostPoint_2019-06-06_DSM_4cm.tif), the vertical RMSE was 0.040 meters (MAE 0.030 meters), and for the Post Point 2-centimeter resolution DSM (PostPoint_2019-06-06_DSM_2cm.tif), the vertical RMSE was 0.042 meters (MAE 0.034 meters) relative to the GPS measurements. The addition of the estimated vertical GPS uncertainty (0.030 meters) in quadrature results in a total vertical accuracy estimate of 0.050 meters for the 4-centimeter resolution DSM and 0.052 meters for the 2-centimeter resolution DSM. It should be noted that this 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 DSM to exceed this estimate. A second method was used to attempt to quantify the vertical errors in areas away from the GCPs. During field data collection, topographic measurements on unvegetated areas were collected with backpack-mounted PPK GPS. These measurements were compared to the DSM elevations using bilinear interpolation at each GPS point to derive additional accuracy estimates for the DSM. For the Post Point 4-centimeter resolution DSM (PostPoint_2019-06-06_DSM_4cm.tif) the vertical RMSE of 7,465 backpack-mounted PPK GPS measurements compared to the DSM elevations was 0.061 meters (MAE 0.043 meters). The mean-error (vertical bias) of the GPS measurements relative to DSM elevations was -0.020 meters, meaning the 4-centimeter resolution DSM was, on average, higher than the GPS measurements. For the Post Point 2-centimeter resolution DSM (PostPoint_2019-06-06_DSM_2cm.tif) the vertical RMSE of 3,589 backpack-mounted PPK GPS measurements compared to the DSM elevations was 0.065 meters (MAE 0.048 meters). The mean-error (vertical bias) of the GPS measurements relative to DSM elevations was -0.016 meters, meaning the 2-centimeter resolution DSM was, on average, higher than the GPS measurements. The addition of the estimated vertical uncertainty of the backpack-mounted GPS (0.035 meters) in quadrature results in a total vertical accuracy estimate of 0.070 meters for the 4-centimeter resolution DSM and 0.074 meters for the 2-centimeter resolution DSM using this method. These slightly higher errors are due in part to the less precise nature of the backpack-mounted GPS measurements. However, these backpack-mounted GPS comparisons do provide a more conservative, and more spatially distributed estimate of the true accuracy of the DSM than the GCP check point method. We present both estimates here to provide the end-user with a more complete understanding of the accuracy of the final data product.
Process_Step:
Process_Description:
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.
Process_Date: 20190606
Process_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Joshua Logan
Contact_Organization:
U.S. Geological Survey, Pacific Coastal and Marine Science Center
Contact_Position: Physical Scientist
Contact_Address:
Address_Type: mailing address
Address: 2885 Mission Street
City: Santa Cruz
State_or_Province: CA
Postal_Code: 95060
Country: US
Contact_Voice_Telephone: 831-460-7519
Contact_Facsimile_Telephone: 831-427-4748
Contact_Electronic_Mail_Address: jlogan@usgs.gov
Process_Step:
Process_Description:
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).
Process_Date: 20190606
Process_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Joshua Logan
Contact_Organization:
U.S. Geological Survey, Pacific Coastal and Marine Science Center
Contact_Address:
Address_Type: mailing and physical
Address: 2885 Mission Street
City: Santa Cruz
State_or_Province: CA
Postal_Code: 95060
Contact_Voice_Telephone: 831-460-7519
Contact_Electronic_Mail_Address: jlogan@usgs.gov
Process_Step:
Process_Description:
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"
Process_Date: 2019
Process_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Joshua Logan
Contact_Organization:
U.S. Geological Survey, Pacific Coastal and Marine Science Center
Contact_Address:
Address_Type: mailing and physical
Address: 2885 Mission Street
City: Santa Cruz
State_or_Province: CA
Postal_Code: 95060
Contact_Voice_Telephone: 831-460-7519
Contact_Electronic_Mail_Address: jlogan@usgs.gov
Process_Step:
Process_Description:
Structure-from-motion (SfM) processing techniques were used to create the Digital Surface Models (DSMs) 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 used as a clipping mask to exclude areas of water, obvious edge artifacts, and large areas of interpolation.
9. The main DSM was exported to a GeoTIFF format with a 4-centimeter pixel resolution. The high-resolution DSM was exported to a GeoTIFF format with a 2-centimeter pixel resolution.
10. The DSMs were converted to cloud optimized GeoTIFF format for compatibility with cloud storage services using the GDAL software package. The DSMs were compressed using the lossless LZW compression method, and 'NoData' value set to -32767. Hillshades of the DSMs were created in cloud optimized GeoTIFF format using GDAL.
Process_Date: 2019
Process_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Joshua Logan
Contact_Organization:
U.S. Geological Survey, Pacific Coastal and Marine Science Center
Contact_Position: Physical Scientist
Contact_Address:
Address_Type: mailing address
Address: 2885 Mission Street
City: Santa Cruz
State_or_Province: CA
Postal_Code: 95060
Country: US
Contact_Voice_Telephone: 831-460-7519
Contact_Facsimile_Telephone: 831-427-4748
Contact_Electronic_Mail_Address: jlogan@usgs.gov
