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Topographic point cloud from UAS survey of the debris flow at South Fork Campground, Sequoia National Park, CA

Published by U.S. Geological Survey | Department of the Interior | Catalog Last Checked: May 05, 2026 at 10:09 PM | Dataset Last Updated: December 19, 2024 at 12:00 AM
This portion of the data release presents a topographic point cloud of the debris flow at South Fork Campground in Sequoia National Park. The point cloud was derived from structure-from-motion (SfM) photogrammetry using aerial imagery acquired during an uncrewed aerial systems (UAS) survey on 30 April 2024, conducted under authorization from the National Park Service. The raw imagery was acquired with a Ricoh GR II digital camera featuring a global shutter. The UAS was flown on pre-programmed autonomous flight lines spaced to provide approximately 70 percent overlap between images from adjacent lines, from an approximate altitude of 110 meters above ground level (AGL), resulting in a nominal ground-sample-distance (GSD) of 2.9 centimeters per pixel. The imagery was geotagged using positions from the UAS onboard single-frequency autonomous GPS. Survey control was established using temporary ground control points (GCPs) consisting of a combination of small square tarps with black-and-white cross patterns and temporary chalk marks placed on the ground. The GCP positions were measured using dual-frequency real-time kinematic (RTK) GPS with corrections referenced to a static base station operating nearby. The images and GCP positions were used for structure-from-motion (SfM) photogrammetric processing to create a topographic point cloud, a high-resolution orthomosaic image, and a DSM. The point cloud contains 284,906,970 points with an average point-spacing of one point every three centimeters. The point cloud has not been classified, however points with confidence less than three (a measure of the number of depth maps used to generate a point) have been assigned a classification value of 7, which represents low noise. The point cloud is provided in a cloud optimized LAZ format to facilitate cloud-based queries and display.

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