Estimating Leaf Bulk Density Distribution in a Tree Canopy Using Terrestrial LiDAR and a Straightforward Calibration Procedure
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...
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MDPI AG
2015-06-01
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Series: | Remote Sensing |
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Online Access: | http://www.mdpi.com/2072-4292/7/6/7995 |
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author | François Pimont Jean-Luc Dupuy Eric Rigolot Vincent Prat Alexandre Piboule |
author_facet | François Pimont Jean-Luc Dupuy Eric Rigolot Vincent Prat Alexandre Piboule |
author_sort | François Pimont |
collection | DOAJ |
description | 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. |
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issn | 2072-4292 |
language | English |
last_indexed | 2024-12-20T22:56:36Z |
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spelling | doaj.art-7102e120f8404a96933470fcc8fb020b2022-12-21T19:24:06ZengMDPI AGRemote Sensing2072-42922015-06-01767995801810.3390/rs70607995rs70607995Estimating Leaf Bulk Density Distribution in a Tree Canopy Using Terrestrial LiDAR and a Straightforward Calibration ProcedureFrançois Pimont0Jean-Luc Dupuy1Eric Rigolot2Vincent Prat3Alexandre Piboule4Institut National de la Recherche Agronomique, UR 629, Ecologie des Forêts Méditerranéennes, Domaine Saint Paul, Site Agroparc, F-84914 Avignon Cedex 9, FranceInstitut National de la Recherche Agronomique, UR 629, Ecologie des Forêts Méditerranéennes, Domaine Saint Paul, Site Agroparc, F-84914 Avignon Cedex 9, FranceInstitut National de la Recherche Agronomique, UR 629, Ecologie des Forêts Méditerranéennes, Domaine Saint Paul, Site Agroparc, F-84914 Avignon Cedex 9, FranceInstitut National de la Recherche Agronomique, UR 629, Ecologie des Forêts Méditerranéennes, Domaine Saint Paul, Site Agroparc, F-84914 Avignon Cedex 9, FranceOffice National des Forêts, Département RDI-Pôle Nancy 11 Rue de l'île de Corse, F-54000 Nancy, FranceLeaf 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.http://www.mdpi.com/2072-4292/7/6/7995forest fuelQuercus pubescensphase-shift LiDARmixed pixelsfilteringLiDAR wavelength |
spellingShingle | François Pimont Jean-Luc Dupuy Eric Rigolot Vincent Prat Alexandre Piboule Estimating Leaf Bulk Density Distribution in a Tree Canopy Using Terrestrial LiDAR and a Straightforward Calibration Procedure Remote Sensing forest fuel Quercus pubescens phase-shift LiDAR mixed pixels filtering LiDAR wavelength |
title | Estimating Leaf Bulk Density Distribution in a Tree Canopy Using Terrestrial LiDAR and a Straightforward Calibration Procedure |
title_full | Estimating Leaf Bulk Density Distribution in a Tree Canopy Using Terrestrial LiDAR and a Straightforward Calibration Procedure |
title_fullStr | Estimating Leaf Bulk Density Distribution in a Tree Canopy Using Terrestrial LiDAR and a Straightforward Calibration Procedure |
title_full_unstemmed | Estimating Leaf Bulk Density Distribution in a Tree Canopy Using Terrestrial LiDAR and a Straightforward Calibration Procedure |
title_short | Estimating Leaf Bulk Density Distribution in a Tree Canopy Using Terrestrial LiDAR and a Straightforward Calibration Procedure |
title_sort | estimating leaf bulk density distribution in a tree canopy using terrestrial lidar and a straightforward calibration procedure |
topic | forest fuel Quercus pubescens phase-shift LiDAR mixed pixels filtering LiDAR wavelength |
url | http://www.mdpi.com/2072-4292/7/6/7995 |
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