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Communication

Estimating Tree Diameters from an Autonomous Below-Canopy UAV with Mounted LiDAR

1
Department of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore 117543, Singapore
2
Yale-NUS College, 16 College Avenue West, Singapore 138527, Singapore
3
Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117576, Singapore
4
Peng Cheng Laboratory, 2 Xingke Road, Nanshan, Shenzhen 518066, China
*
Author to whom correspondence should be addressed.
Academic Editor: Dominik Seidel
Remote Sens. 2021, 13(13), 2576; https://doi.org/10.3390/rs13132576
Received: 27 May 2021 / Revised: 19 June 2021 / Accepted: 26 June 2021 / Published: 2 July 2021
(This article belongs to the Special Issue Remote Sensing of Tropical Vegetation)
Below-canopy UAVs hold promise for automated forest surveys because their sensors can provide detailed information on below-canopy forest structures, especially in dense forests, which may be inaccessible to above-canopy UAVs, aircraft, and satellites. We present an end-to-end autonomous system for estimating tree diameters using a below-canopy UAV in parklands. We used simultaneous localization and mapping (SLAM) and LiDAR data produced at flight time as inputs to diameter-estimation algorithms in post-processing. The SLAM path was used for initial compilation of horizontal LiDAR scans into a 2D cross-sectional map, and then optimization algorithms aligned the scans for each tree within the 2D map to achieve a precision suitable for diameter measurement. The algorithms successfully identified 12 objects, 11 of which were trees and one a lamppost. For these, the estimated diameters from the autonomous survey were highly correlated with manual ground-truthed diameters (R2=0.92, root mean squared error = 30.6%, bias = 18.4%). Autonomous measurement was most effective for larger trees (>300 mm diameter) within 10 m of the UAV flight path, for medium trees (200–300 mm diameter) within 5 m, and for trees with regular cross sections. We conclude that fully automated below-canopy forest surveys are a promising, but still nascent, technology and suggest directions for future research. View Full-Text
Keywords: below-canopy survey; UAV-mounted LiDAR; simultaneous localization and mapping; tree diameter estimation below-canopy survey; UAV-mounted LiDAR; simultaneous localization and mapping; tree diameter estimation
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MDPI and ACS Style

Chisholm, R.A.; Rodríguez-Ronderos, M.E.; Lin, F. Estimating Tree Diameters from an Autonomous Below-Canopy UAV with Mounted LiDAR. Remote Sens. 2021, 13, 2576. https://doi.org/10.3390/rs13132576

AMA Style

Chisholm RA, Rodríguez-Ronderos ME, Lin F. Estimating Tree Diameters from an Autonomous Below-Canopy UAV with Mounted LiDAR. Remote Sensing. 2021; 13(13):2576. https://doi.org/10.3390/rs13132576

Chicago/Turabian Style

Chisholm, Ryan A., M. E. Rodríguez-Ronderos, and Feng Lin. 2021. "Estimating Tree Diameters from an Autonomous Below-Canopy UAV with Mounted LiDAR" Remote Sensing 13, no. 13: 2576. https://doi.org/10.3390/rs13132576

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