Laser-scanned tree stem filtering for forest inventories measurements

Abstract

International audienceWith specific flora and fauna, regional landscapes and forests constitute an important part of the cultural heritage. Several natural environments have already been classified as national or regional parks. The UNESCO World Heritage covers 13% of the protected forests in the world. Thus, preserving those sites represents a crucial issue. Such a safeguarding involves a detailed knowledge of the sites and forestry management plans. The management of a natural forest is traditionally based on forest plot inventories in which several features of the trees are measured. The set of data collected during these inventories represents the starting point of forest monitoring, flora preservation and risks prevention. Traditionally, measurements are made manually by operators. However, during the last decade, terrestrial laser scanning has become a new and promising way of measuring such attributes. This instrument provides a fine three dimensional point cloud virtual representation of the scanned scene. Trees location, stem diameter, and stem taper can be extracted from these point clouds using pattern recognition algorithms. In this paper we present a novel two steps way to improve the quality of tree branching detection in a three dimensional point cloud acquired by terrestrial laser scanner. This method was developed in order to enhance the results of a previous study. Our approach is based on the combination of a simplification step (using particle simulation), followed by a shape detection (discrete arcs of circle detection). It identifies the lack of accuracy in tree stem diameter measurements at branching junctions for further more detailed analysis

SimpleTree —An Efficient Open Source Tool to Build Tree Models from TLS Clouds

“…Besides the DTM the output of Computree consists of a DBH estimator, a stem skeleton, a stem taper function and the height of each detected tree. Some of the algorithms implemented in Computree are described in detail in Othmani et al and Ravaglia et al [71,72]. The software framework allows developer-friendly implementation of methods due to its modular programming approach.…”

Estimation of Northern Hardwood Forest Inventory Attributes Using UAV Laser Scanning (ULS): Transferability of Laser Scanning Methods and Comparison of Automated Approaches at the Tree- and Stand-Level

“…where σ 2 is the mean-square error of the regression, Ht is the tree height (m), and CD is the crown diameter (m). Fitted DBH (hereafter, referred to as DBH fit ) from ULS-V-Pcloud trees was estimated using the cylinder-fitting algorithm that is available in Computree [34,78,88,108]. The algorithm (Figure 10) proceeds in five main steps: (i) extraction of a stem slice (Figure 10A); (ii) clustering of the stem slice into horizontal clusters (20 cm widths, Figure 10B); (iii) aggregation of clusters into logs, based on their relative vertical and horizontal positions (Figure 10C); (iv) fitting cylinders (50 cm height [109]) onto the log using nonlinear leastsquares estimation (Figure 10D); and (v) interpolation of tree DBH from the cylinders around 1.3 m above the ground surface (Figure 10E).…”

Tree Stem Diameter Estimation From Volumetric TLS Image Data

“…The stacked cylinder segments represent simplified sections of the stem, but are limited in modelling details of the crossectional shape of the stems [12,13]. A variety of other approaches has been developed, such as approaches using intensity profiles from horizontal panes [14,15], high resolution voxel grid tree models built with manual interaction [16], point clustering followed by circle fitting [17], medial axis transformation [18] and variations of cross section centre finding algorithms [19][20][21]. A number of the alternative approaches used Hough transforms of the image domain in order to detect circular shapes in cross sections.…”