Non-intersecting leaf insertion algorithm for tree structure models. Issue 2 (6th April 2018)

• Record Type: Journal Article
• Authors: Åkerblom, Markku; Raumonen, Pasi; Casella, Eric; Disney, Mathias I.; Danson, F. Mark; Gaulton, Rachel; Schofield, Lucy A.; Kaasalainen, Mikko
• Is Part Of: Interface focus. Volume 8:Issue 2(2018)
• Publication Date: 2018-04-06
• Subjects: leaf insertion -- leaf distribution -- quantitative structure model -- laser scanning -- tree reconstruction; Physical sciences -- Periodicals; Life sciences -- Periodicals; 500
• DOI: 10.1098/rsfs.2017.0045
• Languages: English
• ISSNs: 2042-8898

Abstract

Abstract : We present an algorithm and an implementation to insert broadleaves or needleleaves into a quantitative structure model according to an arbitrary distribution, and a data structure to store the required information efficiently. A structure model contains the geometry and branching structure of a tree. The purpose of this work is to offer a tool for making more realistic simulations of tree models with leaves, particularly for tree models developed from terrestrial laser scanning (TLS) measurements. We demonstrate leaf insertion using cylinder-based structure models, but the associated software implementation is written in a way that enables the easy use of other types of structure models. Distributions controlling leaf location, size and angles as well as the shape of individual leaves are user definable, allowing any type of distribution. The leaf generation process consist of two stages, the first of which generates individual leaf geometry following the input distributions, while in the other stage intersections are prevented by carrying out transformations when required. Initial testing was carried out on English oak trees to demonstrate the approach and to assess the required computational resources. Depending on the size and complexity of the tree, leaf generation takes between 6 and 18 min. Various leaf area density distributions were defined, and the resulting leaf covers were compared with manual leaf harvesting measurements. The results are not conclusive, but they show great potential for the method. In the future, if our method is demonstrated to work well for TLS data from multiple tree types, the approach is likely to be very useful for three-dimensional structure and radiative transfer simulation applications, including remote sensing, ecology and forestry, among others.