Lidar and photogrammetry point clouds with supporting imagery and GPS information collected during UAS operations at Great Sippewissett Marsh, Cape Cod, Massachusetts in November 2022

GROUND CONTROL: The reference mark was established prior the field activity on October 27, 2022. A Parker-Kalon nail was hammered into the center of a cement post near the parking lot and occupied with a SP80 for three and a half hours. The GFILE off of the base was converted to RINEX format 2.11 and uploaded to OPUS after 24 hours had passed. The OPUS solution is provided unedited as a text file.

GROUND CONTROL: Eight AeroPoint GCPs were spaced out over the field site and left on for at least 60 minutes to collect GNSS data. After collection the AeroPoints data were uploaded via a Wi-Fi connection and run through a post-processing kinematic algorithm of the CORS network to get corrected positions. A SP80 rover connected to MASS CORs was used to take ground truthing points in the marsh. The data were exported in NAD83(2011) (EPSG:6318) to produce latitude, longitude, and ellipsoid heights, and then NAD83(2011)/UTM zone 19N (EPSG:6348) and NAVD88 (EPSP:5703) with GEOID18 to produce easting and northing and orthometric heights. These were exported to a CSV file and named 2022022FA_GSM_GPS.csv.

UAS FLIGHTS: The YellowScan Mapper (YSM) lidar sensor was a 905 nm wavelength Livox Horizon with a 70.4/ 4.5 degree horizontal and vertical field of view (FOV) and Applanix 15 inertial measurement unit. A configuration text file (CONFIG.TXT) that controls camera triggering height, the camera triggering interval, and the lidar scan pattern was pre-loaded onto a 256 GB USB thumb drive. The camera module is a SONY UMC - 10RC collecting at 20.4 megapixels (MP). The system also consists of a Trimble AV18 GNSS antenna mounted to the top of the UAS and connected to the lidar system via GNSS cable. The lidar data was saved to the thumb drive in three different files: (1) the IMUPGPS data, decimated for quick post-processing, in binary *.ys format, (2) the scanner data in *.lvx format (~600 MB per minute of data collection), (3) and the complete IMUPGPS data in Applanix (Trimble) binary *.t04 format. The RGB images are saved to a 64 GB micro SD card as *.jpg files. The YellowScan VX20-100 lidar scanner consists of the Riegl minivux-1uav scanner and Applanix 20 inertial measurement unit. All sensors (YSM, VX20-100, and Ricoh) were attached to an DJI Matrice 600 Pro UAS with approved government edition firmware. The YSM lidar data were collected with the UAS flying at 10 m/s at 61 meters above ground level with north-south and east-west transect passes with the scan angle set to +41/-41 to cover a ~110 m swath. The camera module was set to take images every 2 seconds. The VX20-100 lidar data were collected with the UAS flying at 10 m/s at 61 meters above ground level with north-south and east-west transect passes with the scan angle set to +45/-45 to cover a ~110 m swath. The camera module was set to take images every 2 seconds. After the flight the lidar data were taken off the sensor. The Ricoh data were collected with the UAS flying at 10 m/s at 81 meters above ground level with north-south and east-west transect passes that achieve ~80% forelap and sidelap. Image sets were taken every 2 seconds. After the flight, the UAS was powered off, the SD card was removed, and all images and files relating to the survey were downloaded to a field computer.
Note, the YSM photos were collected in EPSG:4326 (WGS84) The positions were converted to EPSG:6348 and EPSG:5703 in the imagery locations file (2022022FA_GSM_ImageryLocations.csv) and were accounted for when transforming to EPSG:6348 and EPSG:5703 in the products.

RAW IMAGERY: All images were processed to add additional information required by the USGS to the Exchangeable Image File Format (EXIF) headers using ExifTools (https://exiftool.org/, version: 12.06), and the files were renamed to a unique identifier using Namexif (http://www.digicamsoft.com/softnamexif.html, version 2.1) to avoid any possibility of duplicate names. These steps are described here. 1. ExifTools was used to tag each photo headers following internal Imagery Data System EXIF Guidance (see metadata contact for more information). Attributes (e.g. Credit, Copyright, UsageTerms, ImageDescription, Artist, etc) were stored in a csv file and written to each image with the command:' exiftool -csv="C:\directory\name\EXIF.csv" C:\directory\name\of\photos *.jpg ' To read out the photo information to a csv when in the directory with the photos the command is: exiftool -csv *.jpg > directory/name/allheaders_out.csv 2. All the images were renamed with Namexif (https://us.digicamsoft.com/softnamexif.html v 2.2 accessed April 2020) to ensure unique filenames and compliance with the USGS Coastal and Marine Hazards and Resources Program's best practices for image naming convention. Images were renamed with the field survey ID prefix; flight number, and ID that distinguishes USGS cameras by make/camera number, the image acquisition date, coordinated universal time (UTC) in ISO8601 format, and a suffix with the original image name. For example, image name '2022022FA_f07r02_20221102T165822Z_IMG_####', 2022022FA is the field activity ID; f07 is the flight number; YSM is the camera on the YellowScan Mapper and r02 is the Ricoh; 20221102 is the UTC date in the format YYYYMMDD, and a 'T' is used to separate UTC date from UTC time in format HHMMSS followed by a Z. The IMG_#### is the original raw photo name appended to the end of the new filename. 3. Images are validated and uploaded onto the Imagery Data System based on sensor and image type.

SfM PROCESSING: The two sets of imagery were processed in Agisoft Metashape 1.8.0 to produce point clouds following these general steps (see Over and others, 2021 for a more detailed SfM methodology explanation). 1. For each image type (Ricoh and YSM) a project was created and imagery was imported. 2. Photos were aligned at a low accuracy and then GCPs were automatically detected in the point cloud. GCP positions (AeroPoints and vinyl targets in 2022022FA_GSM_GPS.csv) were added to the project in the reference systems EPSG:6348 and EPSG:5703 using GEOID18. The horizontal and vertical accuracies for the GCPs were set to 0.01/0.02 m, respectively, and the camera positions for the images were turned off. The photos were then re-aligned with high accuracy (the pixels were not subsampled) using a keypoint limit of 60,000 and unlimited tie points. 3. The alignment process matched pixels between images to create point clouds and put the imagery into a relative spatial context using the GCPs. The resultant point clouds were filtered using one iteration of the 'Reconstruction uncertainty' filter at a level of 10, one iteration of the 'Projection accuracy' filter at a level of 5, and three iterations of the 'Reprojection accuracy' filter to get to a level of 0.3. With each filter, iteration points are selected, deleted, and then the camera model was optimized to refine the focal length, cx, cy, k1, k2, k3, p1, and p2 camera model coefficients. 4. At this point, for each project multiple ‘chunks’ were created so that independent high quality dense clouds with a low-frequency filtering algorithm could be made. The dense point clouds were then edited by visual inspection to remove points with a low confidence near the edges and near water bodies. 5. The colorized dense point clouds were then exported as 2022022FA_GSM_YSM_SfM_PC.laz and 2022022FA_GSM_Ricoh_SfM_PC.laz. 6. Point clouds were then brought into Global Mapper and manually cleaned of points interpreted to be noise or are above a reasonable elevation threshold based on the surrounding features before the data were QA/QC’d with 3DEP, GCPs, and check points.

LiDAR DATA: The lidar data were processed in YellowScan CloudStation software integrated with Trimble POSPac UAV 9.0. Raw scanner data (.ys file) was imported into YellowScan CloudStation, the sensor lidar (.profile) and camera (.camera) profiles, provided by the vendor, were selected for the project and the project coordinate reference system was set to EPSG:6318. CloudStation flight trajectories were adjusted manually to select the desired data to be processed. The .T04 file and base station GNSS RINEX file were used to correct and optimize the sensor position trajectories and produce a Smoothed Best Estimate of Trajectory (SBET) file in .txt ASCII format, which represents the Post Processing Kinematic (PPK) Solution. The lever arm offsets and boresight angle corrections were applied to the LPCs, along with a strip adjustment between transect swaths using CloudStation's "robust" setting. The YSM LPC was colored by the YSM camera based on the photo timestamp. The LPCs were then brought into Global Mapper and manually cleaned of points interpreted to be noise or are above a reasonable elevation threshold based on the surrounding features before the data were QA/QC’d with 3DEP, GCPs, and check points. The LPCs were then exported as 2022022FA_GSM_YSM_LPC.laz and 2022022FA_GSM_VX20_LPC.laz. All files were exported in EPSG:6348 and EPSG:5703 using GEOID18.