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Open AccessArticle

Assessing the Ability of Image Based Point Clouds Captured from a UAV to Measure the Terrain in the Presence of Canopy Cover

1
School of Science, RMIT University, Melbourne, VIC 3001, Australia
2
Bushfire and Natural Hazards Cooperative Research Centre, East Melbourne, VIC 3002, Australia
3
Geomatics and Landscape Lab, Universidad de Chile, La Pintana, Santiago 8820808, Chile
*
Author to whom correspondence should be addressed.
Forests 2019, 10(3), 284; https://doi.org/10.3390/f10030284
Received: 21 February 2019 / Revised: 15 March 2019 / Accepted: 20 March 2019 / Published: 22 March 2019
Point clouds captured from Unmanned Aerial Systems are increasingly relied upon to provide information describing the structure of forests. The quality of the information derived from these point clouds is dependent on a range of variables, including the type and structure of the forest, weather conditions and flying parameters. A key requirement to achieve accurate estimates of height based metrics describing forest structure is a source of ground information. This study explores the availability and reliability of ground surface points available within point clouds captured in six forests of different structure (canopy cover and height), using three image capture and processing strategies, consisting of nadir, oblique and composite nadir/oblique image networks. The ground information was extracted through manual segmentation of the point clouds as well as through the use of two commonly used ground filters, LAStools lasground and the Cloth Simulation Filter. The outcomes of these strategies were assessed against ground control captured with a Total Station. Results indicate that a small increase in the number of ground points captured (between 0 and 5% of a 10 m radius plot) can be achieved through the use of a composite image network. In the case of manually identified ground points, this reduced the root mean square error (RMSE) error of the terrain model by between 1 and 11 cm, with greater reductions seen in plots with high canopy cover. The ground filters trialled were not able to exploit the extra information in the point clouds and inconsistent results in terrain RMSE were obtained across the various plots and imaging network configurations. The use of a composite network also provided greater penetration into the canopy, which is likely to improve the representation of mid-canopy elements. View Full-Text
Keywords: UAS; forest measurement; structure from motion; image based point clouds; RPAS; drones UAS; forest measurement; structure from motion; image based point clouds; RPAS; drones
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Wallace, L.; Bellman, C.; Hally, B.; Hernandez, J.; Jones, S.; Hillman, S. Assessing the Ability of Image Based Point Clouds Captured from a UAV to Measure the Terrain in the Presence of Canopy Cover. Forests 2019, 10, 284.

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