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Enhancing methods for under-canopy unmanned aircraft system based photogrammetry in complex forests for tree diameter measurement

Citation

Krisanski, S and Sadegh Taskhiri, M and Turner, P, Enhancing methods for under-canopy unmanned aircraft system based photogrammetry in complex forests for tree diameter measurement, Remote Sensing, 12, (10) Article 1652. ISSN 2072-4292 (2020) [Refereed Article]


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Copyright 2020 The Authors. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/

DOI: doi:10.3390/rs12101652

Abstract

The application of Unmanned Aircraft Systems (UAS) beneath the forest canopy provides a potentially valuable alternative to ground-based measurement techniques in areas of dense canopy cover and undergrowth. This research presents results from a study of a consumer-grade UAS flown under the forest canopy in challenging forest and terrain conditions. This UAS was deployed to assess under-canopy UAS photogrammetry as an alternative to field measurements for obtaining stem diameters as well as ultra-high-resolution (~400,000 points/m2) 3D models of forest study sites. There were 378 tape-based diameter measurements collected from 99 stems in a native, unmanaged eucalyptus pulchella forest with mixed understory conditions and steep terrain. These measurements were used as a baseline to evaluate the accuracy of diameter measurements from under-canopy UAS-based photogrammetric point clouds. The diameter measurement accuracy was evaluated without the influence of a digital terrain model using an innovative tape-based method. A practical and detailed methodology is presented for the creation of these point clouds. Lastly, a metric called the Circumferential Completeness Index (CCI) was defined to address the absence of a clearly defined measure of point coverage when measuring stem diameters from forest point clouds. The measurement of the mean CCI is suggested for use in future studies to enable a consistent comparison of the coverage of forest point clouds using different sensors, point densities, trajectories, and methodologies. It was found that root-mean-squared-errors of diameter measurements were 0.011 m in Site 1 and 0.021 m in the more challenging Site 2. The point clouds in this study had a mean validated CCI of 0.78 for Site 1 and 0.7 for Site 2, with a mean unvalidated CCI of 0.86 for Site 1 and 0.89 for Site 2. The results in this study demonstrate that under-canopy UAS photogrammetry shows promise in becoming a practical alternative to traditional field measurements, however, these results are currently reliant upon the operatorís knowledge of photogrammetry and his/her ability to fly manually in object-rich environments. Future work should pursue solutions to autonomous operation, more complete point clouds, and a method for providing scale to point clouds when global navigation satellite systems are unavailable.

Item Details

Item Type:Refereed Article
Keywords:drone, UAS, UAV, below-canopy, under-canopy, photogrammetry, structure from motion, point cloud, diameter, forest
Research Division:Information and Computing Sciences
Research Group:Distributed computing and systems software
Research Field:Service oriented computing
Objective Division:Economic Framework
Objective Group:Microeconomics
Objective Field:Supply and demand
UTAS Author:Krisanski, S (Mr Sean Krisanski)
UTAS Author:Sadegh Taskhiri, M (Dr Mohammad Sadegh Taskhiri)
UTAS Author:Turner, P (Associate Professor Paul Turner)
ID Code:139024
Year Published:2020
Web of Science® Times Cited:8
Deposited By:Information and Communication Technology
Deposited On:2020-05-22
Last Modified:2020-06-12
Downloads:6 View Download Statistics

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