Comparing sUAS Photogrammetrically-Derived Point Clouds with GNSS Measurements and Terrestrial Laser Scanning for Topographic Mapping

Abstract

Interest in small unmanned aircraft systems (sUAS) for topographic mapping has significantly grown in recent years, driven in part by technological advancements that have made it possible to survey small- to medium-sized areas quickly and at low cost using sUAS aerial photography and digital photogrammetry. Although this approach can produce dense point clouds of topographic measurements, they have not been tested extensively to provide insights on accuracy levels for topographic mapping. This case study examines the accuracy of a sUAS-derived point cloud of a parking lot located at the Citizens Bank Arena (CBA) in Ontario, California, by comparing it to ground control points (GCPs) measured using global navigation satellite system (GNSS) data corrected with real-time kinematic (RTK) and to data from a terrestrial laser scanning (TLS) survey. We intentionally chose a flat surface due to the prevalence of flat scenes in sUAS mapping and the challenges they pose for accurately deriving vertical measurements. When the GNSS-RTK survey was compared to the sUAS point cloud, the residuals were found to be on average 18 mm and −20 mm for the horizontal and vertical components. Furthermore, when the sUAS point cloud was compared to the TLS point cloud, the average difference observed in the vertical component was 2 mm with a standard deviation of 31 mm. These results indicate that sUAS imagery can produce point clouds comparable to traditional topographic mapping methods and support other studies showing that sUAS photogrammetry provides a cost-effective, safe, efficient, and accurate solution for topographic mapping.

Combining Terrestrial Scanned Datasets With Uav Point Clouds for Mining Operations

“…It is important when combining UAV and TLS datasets, the validity of the acquisition can be established, and the accuracy of both sets is investigated. Methods on how to ascertain the accuracy of UAV data has been researched in Riveiro, et al (2013);Ouedraogo, et al (2014); Tong, et al (2015); Tilly,et al (2016); Jo and Kim (2017); Puniach and Kwartnik-Pruc (2018); Mora (2019); Sasak (2019). where the projects have made use of Structure-form-Motion (SfM) software programs.…”

Potentials of Low-Budget Microdrones: Processing 3D Point Clouds and Images for Representing Post-Industrial Landmarks in Immersive Virtual Environments

“…Different studies exist which are methodologically built on microdrones and structure-from-motion (SfM) approaches (e.g., Mora et al, 2019 ; Aboutalebi et al, 2019 ; Kwon et al, 2017 ). Mora et al (2019) used a DJI Phantom 4 Pro apparatus.…”

“…Different studies exist which are methodologically built on microdrones and structure-from-motion (SfM) approaches (e.g., Mora et al, 2019 ; Aboutalebi et al, 2019 ; Kwon et al, 2017 ). Mora et al (2019) used a DJI Phantom 4 Pro apparatus. They examined the accuracy of an sUAS-derived point cloud of a parking lot located in Ontario, California, by comparing it to ground control points (GCPs).…”

Construction of digital terrain models for testing active-pulse television measuring systems

“…Currently, georeferenced digital models and orthophotomaps of the terrain built from aerial photographs from unmanned aerial vehicles (UAVs) have high spatial resolution, as well as high accuracy of geospatial data [1]. These data are used in many areas of human activity: construction, monitoring, agriculture, design, land management, cadastral work, etc.…”