RIS ID
98096
Link to publisher version (URL)
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Abstract
A forest canopy is a complex system with a highly structural multi-scale architecture. Physical based radiative transfer (RT) modelling has been shown to be an effective tool for retrieval of vegetation canopy biochemical/physical characteristics from optical remote sensing data. A high spatial resolution RT through a forest canopy requires several geometrical and structural parameters of trees and understory to be specified with an appropriate accuracy. Following attributes on forest canopy are required: i) basic tree allometric parameters (i.e., tree height, stem diameter and length, crown length and projection,simplified crown shape, etc.),ii)parameters describing distribution of green biomass (foliage) (e.g., leaf area index (LAI), leaf angle distribution (LAD) or average leaf angle (ALA), clumping of leaves and density of clumps, air gaps and defoliation, etc.), and iii) parameters describing distribution of woody biomass (branches and twigs) (e.g., number, position and angular orientation of the first order branches-branches growing directly from stem, twigarea index (TAI), twig angle distributi on (TAD)). At very high spatial resolution (airborne image data), an insufficiently characterized structure of the forest canopy can result in inaccurate RT simulations. Direct destructive methods of measuring canopy structure are unfeasible at large-scales, therefore, in this paper we review the non-in vasive Light Detection and Ranging (LIDAR) approaches. We also present some results on tree structure parameters acquired by a commercially available ground-based LIDAR scanner employed in scanning the matured Norway spruce trees.
Publication Details
Yanez, L., Homolova, L., Malenovky, Z. & Schaepman, M. (2008). Geometrical and structural parameterization of forest canopy radiative transfer by LIDAR measurements. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7 (pp. 45-50). China: International Society of Photogrammetry and Remote Sensing (ISPRS).