Layer Stacking: A Novel Algorithm for Individual Forest Tree Segmentation from LiDAR Point Clouds

REFERENCES

• Bucksch, A., Lindenbergh, R., Abd Rahman, M.Z., and Menenti, M. 2014. “Breast height diameter estimation from high-density airborne LiDAR data.” IEEEGeoscience and Remote Sensing Letters, Vol. 11(No. 6): pp. 1056–1060.
   Web of Science ®Google Scholar
• Chen, Q. 2007. “Airborne LiDAR data processing and information extraction.” Photogrammetric Engineering and Remote Sensing, Vol. 73(No. 2): pp. 109.
   Web of Science ®Google Scholar
• Chen, Q., Baldocchi, D., Gong, P., and Kelly, M. 2006. “Isolating individual trees in a savanna woodland using small footprint LiDAR data.” Photogrammetric Engineering & Remote Sensing, Vol. 72(No. 8): pp. 923–932.
   Web of Science ®Google Scholar
• Cook, B.D., Nelson, R.F., Middleton, E.M., Morton, D.C., McCorkel, J.T., Masek, J.G., Ranson, K.J., Ly, L., and Montesano, P.M. 2013. “NASA Goddard's LiDAR, hyperspectral and thermal (G-LiHT) airborne imager.” Remote Sensing, Vol. 5(No. 8): pp. 4045–4066.
   Web of Science ®Google Scholar
• Duncanson, L.I., Cook, B.D., Hurtt, G.C., and Dubayah, R.O. 2014. “An efficient, multi-layered crown delineation algorithm for mapping individual tree structure across multiple ecosystems.” Remote Sensing of Environment, Vol. 154: pp. 378–386.
   Web of Science ®Google Scholar
• Ester, M., Kriegel, H.P., Sander, J., and Xu, X. 1996. “A density-based algorithm for discovering clusters in large spatial databases with noise.” Knowledge Discovery in Databases, Vol. 96(No. 34): pp. 226–231.
   Google Scholar
• Gupta, S., Weinacker, H., and Koch, B. 2010. “Comparative analysis of clustering-based approaches for 3-d single tree detection using airborne fullwave LiDAR data.” Remote Sensing, Vol. 2(No. 4): pp. 968–989.
   Web of Science ®Google Scholar
• Hartigan, J.A., and Wong, M.A. 1979. “Algorithm AS 136: a k-means clustering algorithm.” Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 28(No. 1): pp. 100–108.
   Google Scholar
• Kaartinen, H., Hyyppä, J., Yu, X., Vastaranta, M., Hyyppä, H., Kukko, A., Holopainen, M., et al. 2012. “An international comparison of individual tree detection and extraction using airborne laser scanning.” Remote Sensing, Vol. 4(No. 4): pp. 950–974.
   Web of Science ®Google Scholar
• Koch, B., Heyder, U., and Weinacker, H. 2006. “Detection of individual tree crowns in airborne LiDAR data.” Photogrammetric Engineering & Remote Sensing, Vol. 72(No. 4): pp. 357–363.
   Web of Science ®Google Scholar
• Koch, B., Kattenborn, T., Straub, C., and Vauhkonen, J. 2014. “Segmentation of forest to tree objects.” In Forestry Applications of Airborne Laser Scanning, edited by M. Maltamo, E. Næsset, and J. Vauhkonen. Dordrecht, The Netherlands: Springer.
   Google Scholar
• Kwak, D.A., Lee, W.K., Lee, J.H., Biging, G.S., and Gong, P. 2007. “Detection of individual trees and estimation of tree height using LiDAR data.” Journal of Forest Research, Vol. 12(No. 6): pp. 425–434.
   Web of Science ®Google Scholar
• Lee, H., Slatton, K.C., Roth, B.E., and Cropper Jr., W.P. 2010. “Adaptive clustering of airborne LiDAR data to segment individual tree crowns in managed pine forests.” International Journal of Remote Sensing, Vol. 31(No. 1): pp. 117–139.
   Web of Science ®Google Scholar
• Li, W., Guo, Q., Jakubowski, M. K., and Kelly, M. 2012. “A new method for segmenting individual trees from the LiDAR point cloud.” Photogrammetric Engineering & Remote Sensing, Vol. 78(No. 1): pp. 75–84.
   Web of Science ®Google Scholar
• Lindberg, E., Holmgren, J., Olofsson, K., Wallerman, J., and Olsson, H. 2010. “Estimation of tree lists from airborne laser scanning by combining single-tree and area-based methods.” International Journal of Remote Sensing, Vol. 31(No. 5): pp. 1175–1192.
   Web of Science ®Google Scholar
• Maltamo, M., Eerikäinen, K., Pitkänen, J., Hyyppä, J., and Vehmas, M. 2004. “Estimation of timber volume and stem density based on scanning laser altimetry and expected tree size distribution functions.” Remote Sensing of Environment, Vol. 90(No. 3): pp. 319–330.
   Web of Science ®Google Scholar
• McGaughey, R. 2015. Fusion/LDV: Software for LiDAR Data Analysis and Visualization, 3.50. Seattle, WA: USDA Forest Service - Pacific Northwest Research Station.
   Google Scholar
• Means, J.E., Acker, S.A., Fitt, B.J., Renslow, M., Emerson, L., and Hendrix, C.J. 2000. “Predicting forest stand characteristics with airborne scanning LiDAR.” Photogrammetric Engineering and Remote Sensing, Vol. 66(No. 11): pp. 1367–1372.
   Web of Science ®Google Scholar
• Morsdorf, F., Meier, E., Allgöwer, B., and Nüesch, D. 2003. “Clustering in airborne laser scanning raw data for segmentation of single trees.” International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. 34(Part 3): pp. W13.
   Google Scholar
• Næsset, E. 2002. “Predicting forest stand characteristics with airborne scanning laser using a practical 2-stage procedure and field data.” Remote Sensing of Environment, Vol. 80(No. 1): pp. 88–99.
   Web of Science ®Google Scholar
• Persson, A., Holmgren, J., and Söderman, U. 2002. “Detecting and measuring individual trees using an airborne laser scanner.” Photogrammetric Engineering and Remote Sensing, Vol. 68(No. 9): pp. 925–932.
   Web of Science ®Google Scholar
• Popescu, S.C., Randolph, H.W., and Ross, F.N. 2002. “Estimating plot-level tree heights with LiDAR: local filtering with a canopy-height based variable window size.” Computers and Electronics in Agriculture, Vol. 37(No. 1): pp. 71–95.
   Web of Science ®Google Scholar
• Popescu, S.C., and Wynne, R.H. 2004. “Seeing the trees in the forest: using LiDAR and multispectral data fusion with local filtering and variable window size for estimating tree height.” Photogrammetric Engineering & Remote Sensing, Vol. 70(No. 5): pp. 589–604.
   Web of Science ®Google Scholar
• Rahman, M.Z.A., and Gorte, B.G.H. 2009. “Tree crown delineation from high resolution airborne LiDAR based on densities of high points.” In International Archives of the Photogrammetry, Remote Sensing, and Information Sciences XXXVIII (3/W8), Proceedings ISPRS Workshop Laserscanning 2009. Paris, France: ISPRS.
   Google Scholar
• Reitberger, J., Schnörr, C., Krzystek, P., and Stilla, U. 2009. “3D segmentation of single trees exploiting full waveform LIDAR data.” ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 64(No. 6): pp. 561–574.
   Web of Science ®Google Scholar
• Soille, P. 2009. “Segmentation.” In Morphological Image Analysis: Principles and Applications. New York, NY: Springer-Verlag.
   Google Scholar
• Vastaranta, M., Holopainen, M., Haapanen, R., Yu, X., Melkas, T., Hyyppä, J., and Hyyppä, H. 2009. “Comparison between an area-based and individual tree detection method for low- pulse density ALS-based forest inventory.” In Proceedings of Laser Scanning, edited by F. Bretar, M. Pierrot-Deseilligny, and G. Vosselman, pp. 147–151. Paris, France: pp. 1–2.
   Google Scholar
• Vauhkonen, J., Ene, L., Gupta, S., Heinzel, J., Holmgren, J., Pitkänen, J., Solberg, S., et al. 2011. “Comparative testing of single-tree detection algorithms under different types of forest.” Forestry, Vol. 85: pp. 27–40.
   Web of Science ®Google Scholar
• Wulder, M., Niemann, K.O., and Goodenough, D.G. 2000. “Local maximum filtering for the extraction of tree locations and basal area from high spatial resolution imagery.” Remote Sensing of Environment, Vol. 73(No. 1): pp. 103–114.
   Web of Science ®Google Scholar
• Yu, X., Hyyppä, J., Holopainen, M., and Vastaranta, M. 2010. “Comparison of area-based and individual tree-based methods for predicting plot-level forest attributes.” Remote Sensing, Vol. 2(No. 6): pp. 1481–1495.
   Web of Science ®Google Scholar