Abstract

Canopy density measures such as the Leaf Area Index (LAI) have become standardized mapping products derived from airborne and terrestrial Light Detection And Ranging (aLiDAR and tLiDAR, respectively) data. A specific application of LiDAR point clouds is their integration into radiative transfer models (RTM) of varying complexity. Using, e.g., ray tracing, this allows flexible simulations of sub-canopy light condition and the simulation of various sensors such as virtual hemispherical images or waveform LiDAR on a virtual forest plot. However, the direct use of LiDAR data in RTMs shows some limitations in the handling of noise, the derivation of surface areas per LiDAR point and the discrimination of solid and porous canopy elements. In order to address these issues, a strategy upgrading tLiDAR and Digital Hemispherical Photographs (DHP) into plausible 3D architectural canopy models is suggested. The presented reconstruction workflow creates an almost unbiased virtual 3D representation of branch and leaf surface distributions, minimizing systematic errors due to the object–sensor relationship. The models are calibrated and validated using DHPs. Using the 3D models for simulations, their capabilities for the description of leaf density distributions and the simulation of aLiDAR and DHP signatures are shown. At an experimental test site, the suitability of the models, in order to systematically simulate and evaluate aLiDAR based LAI predictions under various scan settings is proven. This strategy makes it possible to show the importance of laser point sampling density, but also the diversity of scan angles and their quantitative effect onto error margins.

Highlights

  • Detailed knowledge about leaf and plant surface distributions in forests and urban environments is of importance for the understanding of a wide range of ecosystem functions

  • The branch model was derived from the tLiDAR input data by an adapted procedure based on the L-Architect approach [35] and a calibration and validation based on Digital Hemispherical Photographs (DHP)

  • An overview of the the L-Architect approach [35] and a calibration and validation based on DHPs

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Summary

Introduction

Detailed knowledge about leaf and plant surface distributions in forests and urban environments is of importance for the understanding of a wide range of ecosystem functions. It defines the distribution of biomass [1] and characterizes ecological habitats [2]. E.g., the magnitude of evapotranspiration, it leads to microclimatic modulations [3]. In order to describe processes that are influenced by canopy densities, the Leaf Area Index (LAI), defined as one half of the total green leaf area per unit ground area [4], is an important key parameter. The true LAI per ground unit includes the full three-dimensional distribution of leaves.

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