Skydio elevation model, orthomosaic, imagery, and GCP data collected during UAS operations at Marconi Beach, CACO, Wellfleet, MA on September 25, 2024

GROUND CONTROL: Five AeroPoint2 GCPs were spaced out over the field site and left on for at least 30 minutes to collect GNSS data. After collection the AeroPoint2s data were uploaded via a Wi-Fi connection and run through a post-processing kinematic algorithm of the Propeller Correction network to get corrected positions. 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 GEOID 18 to produce easting and northing and orthometric heights. These were exported to a CSV file and named 2024024FA_Marconi_Sep_AeroPoints.csv. Step processed by S. Brosnahan, J. Over, and C. Sherwood.

UAS FLIGHTS: The Skydio X10 is a small UAS with an integrated VT300-L camera system. The radiometric thermal camera is a FLIR Boson+ with less than 30 millikelvin sensitivity and takes a 0.3 megapixel (MP) image. The Skydio X10 also has two RGB cameras, one has a 50-degree field of view (narrow) that takes a 64 MP image and the second has a 93-degree field of view (wide) that takes a 50 MP image. A flight in auto mapping mode was flown at 5 m/s at 60 meters above ground level (AGL) with 70% desired sidelap and overlap and 1.21 cm ground sampling distance using only the wide camera. A second flight was flown manually between 55-65 meters AGL with the wide camera tilted to look at the bluff obliquely, the speed varied between 2-7 m/s. Note, the SX10 geotagged positions embedded in the imagery Exif information were in native WGS84 (EPSG:4326) and GEOID EGM96 (EPSG:5773). The positions were converted to EPSG:6348 and EPSG:5703 in the processing software and the converted positions are reported in the imagery locations file (2024024FA_Marconi_Sep_ImageLocations.csv) and represented in the final SfM products. Step processed by S. Brosnahan.

RAW IMAGERY: All images were processed to add additional information required by the USGS to the 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. 1. ExifTools was used to tag each photo headers following the Imagery Data System Exif Guidance. 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 '2024024FA_f01SX10c_20240925T165822Z_IMG_####_#', 2024024FA is the field activity ID; f01 is the flight number; SX10c are the Skydio RGB images; 20240925 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. 4. The 2024024FA_Marconi_Sep_ImageLocations.csv was created with the exif command: exiftool –ImageName –GPSDateTime –csv *.JPG > .\2024024FA_Marconi_Sep_ImageLocations.csv Step processed by J. Over.

PHOTOGRAMMETRY: The SfM products were created in Agisoft Metashape v. 2.1.4 using the following general steps (see Over and others, 2021 for a more detailed SfM methodology explanation) 1. A project was created and imagery, geotagged from UAS FLIGHTS, was imported and assigned the WGS84 (EPSG:4326) and GEOID EGM96 (EPSG:5773) reference systems and then were immediately converted to EPSG: 6318 and then EPSG:6348 and EPSG:5703. These converted positions were added to the 2024024FA_Marconi_Sep_ImageryLocations.csv. 2. Photos were aligned at a low accuracy and then GCPs were automatically detected in the point cloud. GCP positions (2024024FA_Marconi_Sep_AeroPoints.csv) were added to the project in the reference systems EPSG:6348 and EPSG:5703 using GEOID 18. 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 13, one iteration of the 'Projection accuracy' filter at a level of 3, and three iterations of the 'Reprojection accuracy' filter to get to a level of 1. 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 working region was resized to smaller area surrounding the focus area and AeroPoint2s. A interpolated DSM was built from the dense point cloud and then an orthomosaic was built from the DSM with refined seamlines. The SX10 orthomosaic is a 3-band orthomosaic exported at 5 cm resolution (2024024FA_Marconi_Sep_SX10_Ortho_5cm.tif). A non-interpolated DSM was built from the dense point cloud and exported at 5 cm resolution (2024024FA_Marconi_Sep_SX10_DSM_5cm.tif). Step processed by J. Over.

CLOUD OPTIMIZATION: All GeoTIFF products were Deflate compressed and turned into a cloud-optimized GeoTIFFs (COG) using gdal_translate with the following command: for %i in (.\*.tif) do gdal_translate %i .\cog\%~ni.tif -of COG -stats -co BLOCKSIZE=256 -co COMPRESS=DEFLATE -co PREDICTOR=YES -co NUM_THREADS=ALL_CPUS -co BIGTIFF=YES (v. 3.1.4 accessed October 20, 2020 https://gdal.org/). Where i is the name of each GeoTIFF section. Step processed by J. Over.