Research on volume prediction of single tree canopy based on three-dimensional (3D) LiDAR and clustering segmentation

References

• Ahmed, R., P. Siqueira, and S. Hensley. 2013. “A study of forest biomass estimates from LiDAR in the northern temperate forests of New England.” Remote Sensing of Environment 130: 121–135.
   Web of Science ®Google Scholar
• Chen, Q., D. Baldocchi, P. Gong, and M. Kelly. 2006. “Isolating individual trees in a Savanna Woodland using small footprint LiDAR data.” Photogrammetric Engineering and Remote Sensing 72 (8): 923–932.
   Web of Science ®Google Scholar
• Cui, G., W.-K. Lee, D. Kim, E. J. Lee, H. Kwak, H.-A. Choi, D.-A. Kwak, S. Jeon, and W. Zhu. 2014. “Estimation of forest carbon budget from land cover change in south and north korea between 1981 and 2010.” Journal of Plant Biology 57 (4): 225–238.
   Web of Science ®Google Scholar
• Dean, T. J., Q. V. Cao, S. D. Roberts, and D. L. Evans. 2009. “Measuring heights to crown base and crown median with LiDAR in a mature, even-aged loblolly pine stand.” Forest Ecology and Management 257 (1): 126–133.
   Web of Science ®Google Scholar
• Erik, N., and Ø. Tonje. 2002. “Estimating tree height and tree crown properties using airborne scanning laser in a boreal nature reserve.” Remote Sensing of Environment 79 (1): 105–115.
   Web of Science ®Google Scholar
• Fan, Z., J. M. Kabrick, M. A. Spetich, S. R. Shifley, and R. G. Jensen. 2008. “Oak mortality associated with crown dieback and oak borer attack in the Ozark highlands.” Forest Ecology and Management 255 (7): 2297–2305.
   Web of Science ®Google Scholar
• Fieber, K. D., Davenport, I. J., Ferryman, J. M., Gurney, R. J., Becerra, V. M., Walker, J. P., Hacker, J. M. 2016. CHP Toolkit: Case Study of LAIe Sensitivity to Discontinuity of Canopy Cover in Fruit Plantations.“ IEEE Transactions on Geoscience and Remote Sensing 54 (9):5071–5080.
   Web of Science ®Google Scholar
• Ge, L., Z. Yang, Z. Sun, G. Zhang, M. Zhang, K. Zhang, C. Zhang, Y. Tan, and W. Li. 2019. “A method for broccoli seedling recognition in natural environment based on binocular stereo vision and Gaussian mixture model.” Sensors 19 (5): 1132.
   Web of Science ®Google Scholar
• Goetz, S. J., B. Bondlamberty, B. E. Law, J. A. Hicke, C. Huang, R. A. Houghton, S. Mcnulty, T. O’Halloran, M. Harmon, and A. J. H. Meddens. 2015. “Observations and assessment of forest carbon dynamics following disturbance in North America.” Journal of Geophysical Research Biogeosciences 117 (G2): 109–119.
   Google Scholar
• Hierro, J. L., L. C. Branch, D. Villarreal, and K. L. Clark. 2000. “Predictive equations for biomass and fuel characteristics of Argentine shrubs.” Journal of Range Management 53 (6): 617–621.
   Google Scholar
• Holmgren, J., and Å. Persson. 2004. “Identifying species of individual trees using airborne laser scanner.” Remote Sensing of Environment 90 (4): 415–423.
   Web of Science ®Google Scholar
• Ji, Z., and S. Singh. 2014. “LOAM: LiDAR odometry and mapping in real-time.” Paper presented at the Robotics: Science and Systems Conference, Berkeley, California, USA.
   Google Scholar
• Kato, A., M. L. Moskal, P. Schiess, M. E. Swanson, D. Calhoun, and W. Stuetzle. 2009. “Capturing tree crown formation through implicit surface reconstruction using airborne LiDAR data.” Remote Sensing of Environment 113 (6): 1148–1162.
   Web of Science ®Google Scholar
• Li, W., Q. Guo, M. K. Jakubowski, and M. Kelly. 2012. “A new method for segmenting individual trees from the lidar point cloud.” Photogrammetric Engineering and Remote Sensing 78 (1): 75–84.
   Web of Science ®Google Scholar
• Lin, W., Y. Meng, Z. Qiu, S. Zhang, and J. Wu. 2017. “Measurement and calculation of crown projection area and crown volume of individual trees based on 3D laser-scanned point-cloud data.” International Journal of Remote Sensing 38 (4): 1083–1100.
   Web of Science ®Google Scholar
• Marinelli, D., C. Paris, and L. Bruzzone. 2018. “A novel approach to 3-D change detection in multitemporal LiDAR data acquired in forest areas.” IEEE Transactions on Geoscience and Remote Sensing 56 (6): 3030–3046.
   Web of Science ®Google Scholar
• Markom, M. A., A. H. Adom, E. S. M. M. Tan, S. A. A. Shukor, N. A. Rahim, and A. Y. M. Shakaff. 2016.  “A mapping mobile robot using RP LiDAR scanner.” In IEEE International Symposium on Robotics & Intelligent Sensors, Tokyo, Japan, 87–92.
   Google Scholar
• Means, J. E., S. A. Acker, B. J. Fitt, M. Renslow, and C. J. Hendrix. 2000. “Predicting forest stand characteristics with airborne scanning LiDAR.” Photogrammetric Engineering and Remote Sensing 66 (11): 1367–1371.
   Web of Science ®Google Scholar
• Moffat, A. J. 2002. “The state of British forests at the beginning of the 21st century.” International Forestry Review 4 (3): 171–183.
   Web of Science ®Google Scholar
• Næsset, E., and K. O. Bjerknes. 2001. “Estimating tree heights and number of stems in young forests using airborne laser scanner data.” Remote Sensing of Environment 78 (3): 328–340.
   Web of Science ®Google Scholar
• Paris, C., D. Kelbe, J. van Aardt, and L. Bruzzone. 2017. “A novel automatic method for the fusion of ALS and TLS LiDAR data for robust assessment of tree crown structure.” IEEE Transactions on Geoscience and Remote Sensing 55 (7): 3679–3693.
   Web of Science ®Google Scholar
• Popescu, S. C., and K. Zhao. 2008. “A voxel-based LiDAR method for estimating crown base height for deciduous and pine trees.” Remote Sensing of Environment 112 (3): 767–781.
   Web of Science ®Google Scholar
• Ren, Z., L. Wang, and L. Bi. 2019. “Robust GICP-based 3D LiDAR SLAM for underground mining environment.” Sensors 19 (13): 2915.
   Web of Science ®Google Scholar
• Richter, R., M. Behrens, and J. Döllner. 2013. “Object class segmentation of massive 3D point clouds of urban areas using point cloud topology.” International Journal of Remote Sensing 34 (23): 8408–8424.
   Web of Science ®Google Scholar
• Rosell, J. R., J. Llorens, R. Sanz, J. Arnó, M. Ribes-Dasi, J. Masip, A. Escolà, F. Camp, F. Solanelles, and F. Gràcia. 2009. “Obtaining the three-dimensional structure of tree orchards from remote 2D terrestrial LiDAR scanning.” Agricultural & Forest Meteorology 149 (9): 1505–1515.
   Web of Science ®Google Scholar
• Savchenko, A. V. 2017. “Maximum-likelihood approximate nearest neighbor method in real-time image recognition.” Pattern Recognition 61: 459–469.
   Web of Science ®Google Scholar
• Shi, X., T. Liu, and X. Han. 2020. “Improved iterative closest point (ICP) 3D point cloud registration algorithm based on point cloud filtering and adaptive fireworks for coarse registration.” International Journal of Remote Sensing 41 (8): 3197–3220.
   Web of Science ®Google Scholar
• Soja, M. J., H. Persson, and L. M. H. Ulander. 2017. “Estimation of forest height and canopy density from a single InSAR correlation coefficient.” IEEE Geoscience & Remote Sensing Letters 12 (3): 646–650.
   Web of Science ®Google Scholar
• Su, Y. T., J. Bethel, and S. Hu. 2016. “Octree-based segmentation for terrestrial LiDAR point cloud data in industrial applications.” Isprs Journal of Photogrammetry & Remote Sensing 113: 59–74.
   Web of Science ®Google Scholar
• Tao, S., F. Wu, Q. Guo, Y. Wang, and J. Fang. 2015. “Segmenting tree crowns from terrestrial and mobile LiDAR data by exploring ecological theories.” Isprs Journal of Photogrammetry & Remote Sensing 110: 66–76.
   Web of Science ®Google Scholar
• Tao, S., Q. Guo, L. Li, B. Xue, M. Kelly, W. Li, G. Xu, and Y. Su. 2014. “Airborne LiDAR-derived volume metrics for aboveground biomass estimation: a comparative assessment for conifer stands.” Agricultural & Forest Meteorology 198: 24–32.
   Web of Science ®Google Scholar
• Velas, M., M. Spanel, M. Hradis, and A. Herout. 2018. “CNN for IMU assisted odometry estimation using velodyne LiDAR.” In IEEE International Conference on Autonomous Robot Systems & Competitions, Torres Vedras, Portugal, 71–77.
   Google Scholar
• Winker, K. 2009. “Reuniting phenotype and genotype in biodiversity research.” Bioscience 59 (8): 657–665.
   Web of Science ®Google Scholar
• Wu, B., B. Yu, W. Yue, S. Shu, W. Tan, C. Hu, Y. Huang, J. Wu, and H. Liu. 2013. “A voxel-based method for automated identification and morphological parameters estimation of individual street trees from mobile laser scanning data.” Remote Sensing 5 (2): 584–611.
   Web of Science ®Google Scholar
• Yan, Z., L. Sun, T. Duckett, and N. Bellotto. 2018. “Multisensor online transfer learning for 3D LiDAR-based human detection with a mobile robot.” 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, 7635-7640.
   Google Scholar
• Yang, B., Z. Wei, Q. Li, and J. Li. 2012. “Automated extraction of street-scene objects from mobile LiDAR point clouds.” International Journal of Remote Sensing 33 (17–18): 5839–5861.
   Web of Science ®Google Scholar
• Yin, L., J. Andrews, and T. Heaton. 2018. “Reducing process delays for real-time earthquake parameter estimation–an application of KD tree to large databases for earthquake early warning.” Computers & Geosciences 114: 22–29.
   Web of Science ®Google Scholar
• Zabala, A., and X. Pons. 2011. “Effects of lossy compression on remote sensing image classification of forest areas.” International Journal of Applied Earth Observation & Geoinformation 13 (1): 43–51.
   Web of Science ®Google Scholar
• Zhang, C., L. Yong, Y. Chen, S. Zhang, G. Luzhen, S. Wang, and W. Li. 2019. “A rubber-tapping robot forest navigation and information collection system based on 2D LiDAR and a gyroscope.” Sensors 19 (9): 2136.
   Web of Science ®Google Scholar
• Zhong, L., L. Cheng, H. Xu, Y. Wu, Y. Chen, and M. Li. 2017. “Segmentation of individual trees from TLS and MLS data.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 10 (2): 774–787.
   Web of Science ®Google Scholar