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Assessing the feasibility of UAV-based LiDAR for high resolution forest change detection

Citation

Wallace, LO and Lucieer, A and Watson, CS, Assessing the feasibility of UAV-based LiDAR for high resolution forest change detection, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume 39-B7, 25 August - 1 September 2012, Melbourne, Australia, pp. 499-504. (2012) [Non Refereed Conference Paper]


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DOI: doi:10.5194/isprsarchives-XXXIX-B7-499-2012

Abstract

Airborne LiDAR data has become an important tool for both the scientific and industry based investigation of forest structure. The uses of discrete return observations have now reached a maturity level such that the operational use of this data is becoming increasingly common. However, due to the cost of data collection, temporal studies into forest change are often not feasible or completed at infrequent and at uneven intervals. To achieve high resolution temporal LiDAR surveys, this study has developed a micro-Unmanned Aerial Vehicle (UAV) equipped with a discrete return 4-layer LiDAR device and miniaturised positioning sensors. This UAV has been designed to be low-cost and to achieve maximum flying time. In order to achieve these objectives and overcome the accuracy restrictions presented by miniaturised sensors a novel processing strategy based on a Kalman smoother algorithm has been developed. This strategy includes the use of the structure from motion algorithm in estimating camera orientation, which is then used to restrain IMU drift. The feasibility of such a platform for monitoring forest change is shown by demonstrating that the pointing accuracy of this UAV LiDAR device is within the accuracy requirements set out by the Australian Intergovernmental Committee on Surveying and Mapping (ICSM) standards.

Item Details

Item Type:Non Refereed Conference Paper
Keywords:UAV, LiDAR, forest, inventory, change detection
Research Division:Engineering
Research Group:Geomatic Engineering
Research Field:Photogrammetry and Remote Sensing
Objective Division:Environment
Objective Group:Ecosystem Assessment and Management
Objective Field:Ecosystem Assessment and Management of Forest and Woodlands Environments
Author:Wallace, LO (Dr Luke Wallace)
Author:Lucieer, A (Associate Professor Arko Lucieer)
Author:Watson, CS (Dr Christopher Watson)
ID Code:93125
Year Published:2012
Deposited By:Geography and Environmental Studies
Deposited On:2014-07-14
Last Modified:2014-07-14
Downloads:0

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