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  • 1.
    Ringdahl, Ola
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hohnloser, Peter
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hellström, Thomas
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Holmgren, Johan
    Dept. of Forest Resource Management, Swedish University of Agricultural Sciences.
    Lindroos, Ola
    Department of Forest Biomaterials and Technology, Swedish University of Agricultural Sciences.
    Enhanced Algorithms for Estimating Tree Trunk Diameter Using 2D Laser Scanner2013In: Remote Sensing, ISSN 2072-4292, E-ISSN 2072-4292, Vol. 5, no 10, p. 4839-4856Article in journal (Refereed)
    Abstract [en]

    Accurate vehicle localization in forest environments is still an unresolved problem. Global navigation satellite systems (GNSS) have well known limitations in dense forest, and have to be combined with for instance laser based SLAM algorithms to provide satisfying accuracy. Such algorithms typically require accurate detection of trees, and estimation of tree center locations in laser data. Both these operations depend on accurate estimations of tree trunk diameter. Diameter estimations are important also for several other forestry automation and remote sensing applications. This paper evaluates several existing algorithms for diameter estimation using 2D laser scanner data. Enhanced algorithms, compensating for beam width and using multiple scans, were also developed and evaluated. The best existing algorithms overestimated tree trunk diameter by ca. 40%. Our enhanced algorithms, compensating for laser beam width, reduced this error to less than 12%.

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