Acquisition of Data for Building Photogrammetric Virtual Outcrop Models for the Geosciences using Remotely Piloted Vehicles (RPVs)

Abstract

Over the past five years the use of 3D models in the Earth Sciences has become ubiquitous. These models, termed Virtual outcrops, are most commonly generated using Structure from Motion (SfM) photogrammetry, an image-based modelling method that has achieved widespread uptake and utilization. Data for these models is commonly acquired using remotely piloted aerial vehicles (RPVs), commonly called drones. The purpose of this document is to present a basic acquisition methodology, which is based on the workflows used by the authors for the acquisition of over 500 virtual outcrops over the last decade. This article is part of a series from the editors of V3Geo, which is an online forum for sharing high quality virtual 3D geoscience models. Virtual outcrops submitted to V3Geo are subject to a technical quality control to ensure that data can be reliably utilized by the wider professional and scientific community. This document provides guidelines for the robust acquisition of data which are required to build high quality models suitable for sharing in V3Geo. The document focuses on outcrop selection, mission planning, RPV setup, data acquisition and management. Related documents in this series cover data processing and model building.

Facies models for rocky shorelines and their application to transgressed basement highs in the North Sea.

“…Detailed sedimentary logs were collected from each of the onshore Miocene examples, recording information on grain size, roundness, sorting, sedimentary structures and fossil content. This was complemented with UAVacquired images, which were subsequently used to create virtual outcrops (Buckley et al 2008) following the method outlined in Howell et al, (2021). Images were first imported and georeferenced into Agisoft PhotoScan, a photogrammetry software used to reconstruct the geometry of the outcrops and create 3D models based on the identification of common points between images.…”

The sedimentological expression of transgression–regression cycles upon aeolian–marine margins

“…Sedimentary logs were combined with high‐resolution unmanned aerial vehicle (UAV) photogrammetry to provide a 3D visualisation of the preserved aeolian successions. Aerial photographs were collected using a ‘DJI Phantom 4 Pro’ drone, which was flown along a horizontal axis, while allowing for 80% overlap between images at a near‐parallel viewing angle (Bemis et al, 2014; Howell et al, 2021; Priddy et al, 2019). The UAV‐based photogrammetry was completed at four separate localities (Figure 1A), and ground‐based photogrammetry was used at Bartlett Wash due to proximity to Moab Airport and aerospace restrictions, with care taken to reduce inaccuracies in scaling and parallax error.…”