Enhanced Measurements of Leaf Area Density with T-LiDAR: Evaluating and Calibrating the Effects of Vegetation Heterogeneity and Scanner Properties

Maxime Soma,François Pimont,Sylvie Durrieu,Jean-Luc Dupuy

doi:10.3390/rs10101580

Maxime Soma, François Pimont + Show 2 more

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https://doi.org/10.3390/rs10101580

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Abstract

Reliable measurements of the 3D distribution of Leaf Area Density (LAD) in forest canopy are crucial for describing and modelling microclimatic and eco-physiological processes involved in forest ecosystems functioning. To overcome the obvious limitations of direct measurements, several indirect methods have been developed, including methods based on Terrestrial LiDAR scanning (TLS). This work focused on various LAD estimators used in voxel-based approaches. LAD estimates were compared to reference measurements at branch scale in laboratory, which offered the opportunity to investigate in controlled conditions the sensitivity of estimations to various factors such as voxel size, distance to scanner, leaf morphology (species), type of scanner and type of estimator. We found that all approaches to retrieve LAD estimates were highly sensitive to voxel size whatever the species or scanner and to distance to the FARO scanner. We provided evidence that these biases were caused by vegetation heterogeneity and variations in the effective footprint of the scanner. We were able to identify calibration functions that could be readily applied when vegetation and scanner are similar to those of the present study. For different vegetation and scanner, we recommend replicating our method, which can be applied at reasonable cost. While acknowledging that the test conditions in the laboratory were very different from those of the measurements taken in the forest (especially in terms of occlusion), this study revealed existence of strong biases, including spatial biases. Because the distance between scanner and vegetation varies in field scanning, these biases should occur in a similar manner in the field and should be accounted for in voxel-based methods but also in gap-fraction methods.

Highlights

Capturing the three-dimensional (3D) structure and the spatial heterogeneity of vegetation canopies is crucial for characterizing ecosystems mass and energy fluxes. 3D leaf distribution has become a critical parameter for modelling radiative transfers [1] and for eco-physiological models incorporating photosynthesis and transpiration processes [2,3]
This study aims to (i) disentangle the different sources of bias and to evaluate their magnitude, (ii) focus on the specific biases associated with voxel size and distance to scanner and (ii) propose generic calibration models to retrieve correct Leaf Area Density (LAD) estimates from Terrestrial LiDAR scanning (TLS) measurements
We compare the raw LAD to the actual LAD and investigate how the relationship was affected by the voxel size, for short distance measurements

Summary

Introduction

Capturing the three-dimensional (3D) structure and the spatial heterogeneity of vegetation canopies is crucial for characterizing ecosystems mass and energy fluxes. 3D leaf distribution has become a critical parameter for modelling radiative transfers [1] and for eco-physiological models incorporating photosynthesis and transpiration processes [2,3]. Foliage density or Leaf Area Density (LAD, m2/m3), defined as the one-sided area of leaves per unit volume [6], can theoretically be retrieved from direct measurement of the surface area of leafy elements in reference volumes of interest. Such an approach is not practical and remains volume limited, as it is extremely time consuming and has obvious destructive consequences on vegetation. These methods do not provide the 3D foliage distribution and require empirical corrections to account for clumping [9]

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