Estimating Leaf Bulk Density Distribution in a Tree Canopy Using Terrestrial LiDAR and a Straightforward Calibration Procedure

Remote Sensing

François Pimont²  Jean-Luc Dupuy²  Eric Rigolot²  Vincent Prat²  Alexandre Piboule¹  Nicolas Baghdadi³ 

[1] Office National des Forêts, Département RDI-Pôle Nancy 11 Rue de l’île de Corse, F-54000 Nancy, France; E-Mail:;Institut National de la Recherche Agronomique, UR 629, Ecologie des Forêts Méditerranéennes, Domaine Saint Paul, Site Agroparc, F-84914 Avignon Cedex 9, France; E-Mails:Institut National de la Recherche Agronomique, UR 629, Ecologie des Forêts Méditerranéennes, Domaine Saint Paul, Site Agroparc, F-84914 Avignon Cedex 9, France;

关键词: forest fuel;    Quercus pubescens;    phase-shift LiDAR;    mixed pixels;    filtering;    LiDAR wavelength;   

DOI  :  10.3390/rs70607995

来源: mdpi

【 摘 要 】

Leaf biomass distribution is a key factor for modeling energy and carbon fluxes in forest canopies and for assessing fire behavior. We propose a new method to estimate 3D leaf bulk density distribution, based on a calibration of indices derived from T-LiDAR. We applied the method to four contrasted plots in a mature Quercus pubescens forest. Leaf bulk densities were measured inside 0.7 m-diameter spheres, referred to as Calibration Volumes. Indices were derived from LiDAR point clouds and calibrated over the Calibration Volume bulk densities. Several indices were proposed and tested to account for noise resulting from mixed pixels and other theoretical considerations. The best index and its calibration parameter were then used to estimate leaf bulk densities at the grid nodes of each plot. These LiDAR-derived bulk density distributions were used to estimate bulk density vertical profiles and loads and above four meters compared well with those assessed by the classical inventory-based approach. Below four meters, the LiDAR-based approach overestimated bulk densities since no distinction was made between wood and leaf returns. The results of our method are promising since they demonstrate the possibility to assess bulk density on small plots at a reasonable operational cost.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.