High resolution structure from motion digital surface models representing three sites on North Core Banks, NC in October 2022

The DSMs were created in Agisoft Metashape v. 1.8.1 using the following general steps (see Over and others, 2021 for a more detailed methodology explanation): 1. For each site (NP0, NP1, and NP3) a new project was created and Ricoh imagery and Altum-PT panchromatic band imagery (located in larger work citation) were imported. 2. Photos were aligned at a low accuracy and then GCPs were automatically detected in the point cloud. GCP positions (2022034FA_NCB_GCPs.csv located in the larger work citation) were added to the project in the reference systems NAD83(2011)/UTM Zone 18N and NAVD88 (geoid 18). Accuracies for the GCPs were set to 0.05 m and the camera positions for the panchromatic band images were turned off. The photos were then re-aligned with high accuracy (the pixels were not subsampled but processing speed decreased) using a keypoint limit of 60,000 and unlimited tie points. 3. The alignment process matched pixels between images and created 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 12, 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 0.3. With each filter, iteration points were 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, the Ricoh images were disabled so only the Altum-PT images were used to create a dense point cloud using the high-quality setting (images were not subsampled) and a low-frequency filtering algorithm. Note, this process was reversed so only Ricoh imagery was enabled, but the final product from that iteration was inferior when compared to the GPS points (see accuracy report). The dense point cloud was then edited by visual inspection and Metashape’s confidence filter to remove points with a low confidence near the edges and near water bodies. 4. The DSM products were exported at 5 cm in NAD83(2011)/UTM Zone 18N and NAVD88 (m). Region boundaries were rounded to the nearest 5 m interval. West and south bounds were rounded up and east and north bounds were rounded down.

The DSMs were then turned into cloud-optimized GeoTIFFz (COG) using gdal_translate with the following command: for %i in (.\*.tif) do gdal_translate %i .\%~ni_cog.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.