A method for 3D reconstruction of tree crown volume from photographs: assessment with 3D-digitized plants.

We developed a method for reconstructing tree crown volume from a set of eight photographs taken from the N, S, E, W, NE, NW, SE and SW. This photographic method of reconstruction includes three steps. First, canopy height and diameter are estimated from each image from the location of the topmost, rightmost and leftmost vegetated pixel; second, a rectangular bounding box around the tree is constructed from canopy dimensions derived in Step 1, and the bounding box is divided into an array of voxels; and third, each tree image is divided into a set of picture zones. The gap fraction of each picture zone is calculated from image processing. A vegetated picture zone corresponds to a gap fraction of less than 1. Each picture zone corresponds to a beam direction from the camera to the target tree, the equation of which is computed from the zone location on the picture and the camera parameters. For each vegetated picture zone, the ray-box intersection algorithm (Glassner 1989) is used to compute the sequence of voxels intersected by the beam. After processing all vegetated zones, voxels that have not been intersected by any beam are presumed to be empty and are removed from the bounding box. The estimation of crown volume can be refined by combining several photographs from different view angles. The method has been implemented in a software package called Tree Analyzer written in C++. The photographic method was tested with three-dimensional (3D) digitized plants of walnut, peach, mango and olive. The 3D-digitized plants were used to estimate crown volume directly and generate virtual perspective photographs with POV-Ray Version 3.5 (Persistence of Vision Development Team). The locations and view angles of the camera were manually controlled by input parameters. Good agreement between measured data and values inferred from the photographic method were found for canopy height, diameter and volume. The effects of voxel size, size of picture zoning, location of camera and number of pictures were also examined.

[1]  A.R.G. Lang,et al.  Leaf orientation of a cotton plant , 1973 .

[2]  M. Fuchs,et al.  Row structure and foliage geometry as determinants of the interception of light rays in a sorghum row canopy. , 1980 .

[3]  Seppo Kellomäki,et al.  Effect of grouping of foliage on the within-stand and within-crown light regime: Comparison of random and grouping canopy models , 1983 .

[4]  J. Norman,et al.  Radiative Transfer in an Array of Canopies1 , 1983 .

[5]  J. Lawton,et al.  Fractal dimension of vegetation and the distribution of arthropod body lengths , 1985, Nature.

[6]  J. D. Dulk The interpretation of remote sensing : a feasibility study , 1989 .

[7]  Andrew S. Glassner,et al.  An introduction to ray tracing , 1989 .

[8]  Przemyslaw Prusinkiewicz,et al.  The Algorithmic Beauty of Plants , 1990, The Virtual Laboratory.

[9]  Kenneth Falconer,et al.  Fractal Geometry: Mathematical Foundations and Applications , 1990 .

[10]  Peter Pfeifer,et al.  A Method for Estimation of Fractal Dimension of Tree Crowns , 1991, Forest Science.

[11]  Tiit Nilson,et al.  Radiative Transfer in Nonhomogeneous Plant Canopies , 1992 .

[12]  Hervé Sinoquet,et al.  Evaluation of structure description requirements for predicting gap fraction of vegetation canopies , 1993 .

[13]  J. Cihlar,et al.  Plant canopy gap-size analysis theory for improving optical measurements of leaf-area index. , 1995, Applied optics.

[14]  B. Courbaud,et al.  Polyhedral representation of crown shape. A geometric tool for growth modelling , 1995 .

[15]  Aldo Laurentini Surface reconstruction accuracy for active volume intersection , 1996, Pattern Recognit. Lett..

[16]  A. Cescatti Modelling the radiative transfer in discontinuous canopies of asymmetric crowns. I. Model structure and algorithms , 1997 .

[17]  Janne Heikkilä,et al.  A four-step camera calibration procedure with implicit image correction , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[18]  Aldo Laurentini,et al.  How Many 2D Silhouettes Does It Take to Reconstruct a 3D Object? , 1997, Comput. Vis. Image Underst..

[19]  R. Nelson Modeling forest canopy heights: The effects of canopy shape , 1997 .

[20]  Akira Osawa,et al.  Measurement of three‐dimensional structure of plants with a simple device and estimation of light capture of individual leaves , 1998 .

[21]  David Doley,et al.  Estimating tree crown dimensions using digital analysis of vertical photographs. , 2000 .

[22]  R. Hall,et al.  A comparison of digital and film fisheye photography for analysis of forest canopy structure and gap light transmission , 2001 .

[23]  P. Dutilleul,et al.  Inclusion of the fractal dimension of leafless plant structure in the Beer-Lambert law , 2001 .

[24]  Nobuya Mizoue,et al.  Fractal Analysis of Tree Crown Images in Relation to Crown Transparency , 2001 .

[25]  Frédéric Boudon,et al.  Représentation géométrique multi-échelles de l'architecture des plantes. (Multiscale geometric representation of plant architecture) , 2004 .

[26]  Steven M. Seitz,et al.  Photorealistic Scene Reconstruction by Voxel Coloring , 1997, International Journal of Computer Vision.

[27]  Kiriakos N. Kutulakos,et al.  A Theory of Shape by Space Carving , 2000, International Journal of Computer Vision.

[28]  Hervé Sinoquet,et al.  Three-dimensional reconstruction of partially 3D digitised peach tree canopies , 2004 .