Structure-from-Motion (SfM) surface models derived from seafloor video from the Channel Islands, California

Structure-from-Motion (SfM) surface models were created using seafloor video collected over a visible fault scarp in the Channel Islands, California, during a 2016 U.S. Geological Survey (USGS) field activity. Four SfM surface models were created, each with a different combination of locating, scaling, and optimizing methods. Video imagery was collected using the USGS Pacific Coastal and Marine Science Center's BOBSled, equipped with high-definition (720p) video cameras (video published in Coastal and Marine Geology Program video and photo portal, Golden and others, 2015). The sled was towed behind the R/V Shearwater and shipboard GPS locations were recorded every 1 second in the video's audio channel. The models were geolocated and scaled using either shipboard GPS or georeferencing the imagery to existing sonar bathymetry at a lower resolution (Cochrane and others, 2018). The models were optimized using either a fixed lens model or automatic calibration in the SfM software, and the files presented here are named to reflect their processing method: "AutoCal" refers to automatic calibration by the SfM software; "Cal" refers to image calibration using a fixed lens model; "Georef" refers to locations derived from georeferencing the video imagery to the existing sonar data; and "ShipGPS" refers to locations derived from the shipboard GPS embedded in the video. Each file was created using one of each of the calibration and location methods, indicated in the filename as "SfM_CalibrationMethod_LocationMethod_UTM10N."

References:

Cochrane, G.R., Finlayson, D.P., and Dailey, E.T., 2018, Bathymetry and acoustic backscatter data from the San Miguel Passage in the Channel Islands, California, 2007: U.S. Geological Survey data release, https://doi.org/10.5066/F78G8HVC.

Golden, N.E., Ackerman, S.D., and Dailey, E.T., 2015, Coastal and Marine Geology Program video and photograph portal. U.S. Geological Survey data release, http://doi.org/10.5066/F7JH3J7N.