Field Activity 2021-607-FA

Identifier 2021-607-FA
Also known as SQUID5 system testing Tahoe Reef
Purpose Field testing of modifications/updates to the SQUID-5 underwater structure from motion mapping vehicle
Location Lake Tahoe, CA near Tahoe City
Summary Successfully collected high resolution lakebed imagery and associated navigation for processing with Structure from Motion (SfM) software.
Info derived Lake bed elevation and orthoimagery
Comments Entries for this field activity are based on entries from Field Activity 2020-634-FA
Projects
Platform
Boat
Vehicles
MarFac; Chevy 9 pass. van - green G42-0422G
MarFac; Expedition G62-3094P
Itinerary
Start Tahoe City, CA 2021-03-08
End Tahoe City, CA 2021-03-12
Days in the field 4
Bounds
West -120.1521492
East -120.08022308
North 39.19346594
South 39.15642106
Marine operations Yes

Personnel

Organization
2885 Mission Street
Santa Cruz, CA95060
(831) 460-7401
Principal investigators Gerald Hatcher
Crew members
Information specialist(s)
Peter Dal Ferro
Specialist, Information
Affiliate principal Brant Allen, Field Lab Director and Boat Captain. UC Davis. S. Geoffrey Schladow, PhD, UC Davis

Data types and categories

Data category: Location-Elevation, Imagery
Data type: Navigation, Photo

Equipment used

Equipment Usage description Data types Datasets
Trimble R7 GPS receiver Benchmarks, LIDAR, Navigation, Profiles, Transects (no data reported)
SQUID-5 Photo 5

Datasets

Datasets produced in this activity

Dataset name Equipment Description Dataset contact
Bathymetric digital elevation model (DEM) of Lake Tahoe near Dollar Point SQUID-5 Underwater images collected near Dollar Point in Lake Tahoe, California, were processed using Structure-from-Motion (SfM) photogrammetry techniques into a classified 3D point cloud. The DEM was derived in Metashape (ver. 1.6.4) from the point cloud, but it excludes the 'high noise' class. The DEM data were output as a geoTIFF raster at 25-mm resolution. Jonathan Warrick
GNSS locations of lakebed images collected near Dollar Point, Lake Tahoe, CA, March 10 and 11, 2021 SQUID-5 This text file (2021-607-FA_Image_Locations.txt) provides the GNSS antenna location for underwater images collected near Dollar Point, Lake Tahoe, CA, using a recently developed towed-surface vehicle with multiple downward-looking underwater cameras. The GNSS antenna location for the time of each image capture is presented with greater precision than is stored in the individual image's EXIF header due to decimal place limitations of the EXIF format. Gerald Hatcher
Orthoimagery of Lake Tahoe near Dollar Point SQUID-5 Lakebed orthoimagery was developed from underwater images collected near Dollar Point in Lake Tahoe, California, and processed using Structure-from-Motion (SfM) photogrammetry techniques. The orthoimages were developed using both image-mosaic and image-averaging methods, which were then output as 5-mm resolution rasters. In general, the "Mosaic" product is somewhat sharper in resolution but will include some distinct seam lines and noticeable differences in image quality across the image. The "Average" product, in contrast, is more uniform in color and quality but blurrier overall. Jonathan Warrick
Overlapping lakebed images collected near Dollar Point, Lake Tahoe, CA, March 10 and 11, 2021 SQUID-5 Underwater images were collected near Dollar Point, Lake Tahoe, CA, using a recently developed towed-surface vehicle with multiple downward-looking underwater cameras. The images are organized in zipped files grouped by survey line. The SQUID-5 system records images as TIFF (.tif) format to maintain the highest resolution and bit depth. Each image includes EXIF metadata, containing GNSS date, time, and latitude and longitude of the GNSS antenna mounted on the towed surface vehicle, copyright, keywords, and other fields. Gerald Hatcher
Point cloud data of Lake Tahoe near Dollar Point SQUID-5 Three-dimensional point clouds (LAZ format) were developed from underwater images collected near Dollar Point in Lake Tahoe, California, and processed using Structure-from-Motion (SfM) photogrammetry techniques. Point cloud data include x,y,z positions, RGB colors, Metashape-computed confidence values, and a two-class classification ('unclassified' and 'high noise') derived from the confidence values. Jonathan Warrick

Publications

Samples collected during this field activity