Principles and practice of acquiring drone-based image data in marine environments
K. E. Joyce A D , S. Duce A , S. M. Leahy A , J. Leon B and S. W. Maier C
+ Author Affiliations
- Author Affiliations
A College of Science and Engineering, James Cook University, Macgregor Road, Smithfield, Qld 4870, Australia
B School of Science and Engineering, University of the Sunshine Coast, Sippy Downs, Qld 4556, Australia
C maitec, PO Box U19, Charles Darwin University, NT 0815, Australia.
D Corresponding author. Email: karen.joyce@jcu.edu.au
Marine and Freshwater Research 70(7) 952-963 https://doi.org/10.1071/MF17380
Submitted: 14 December 2017 Accepted: 26 March 2018 Published: 12 July 2018
Abstract
With almost limitless applications across marine and freshwater environments, the number of people using, and wanting to use, remotely piloted aircraft systems (or drones) is increasing exponentially. However, successfully using drones for data collection and mapping is often preceded by hours of researching drone capabilities and functionality followed by numerous limited-success flights as users tailor their approach to data collection through trial and error. Working over water can be particularly complex and the published research using drones rarely documents the methodology and practical information in sufficient detail to allow others, with little remote pilot experience, to replicate them or to learn from their mistakes. This can be frustrating and expensive, particularly when working in remote locations where the window of access is small. The aim of this paper is to provide a practical guide to drone-based data acquisition considerations. We hope to minimise the amount of trial and error required to obtain high-quality, map-ready data by outlining the principles and practice of data collection using drones, particularly in marine and freshwater environments. Importantly, our recommendations are grounded in remote sensing and photogrammetry theory so that the data collected are appropriate for making measurements and conducting quantitative data analysis.
Additional keywords: high resolution, thermal, three-dimensional mapping, UAS, UAV, unmanned aerial system, unmanned aerial vehicle.
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