BelandBaldocchiWidlowskiEtAl2014

Référence

Beland, M., Baldocchi, D.D., Widlowski, J.-L., Fournier, R.A. and Verstraete, M.M. (2014) On seeing the wood from the leaves and the role of voxel size in determining leaf area distribution of forests with terrestrial LiDAR. Agricultural and Forest Meteorology, 184:82-97. (Scopus )

Résumé

Terrestrial LiDAR scanners have been shown to hold great potential for estimating and mapping three dimensional (3-D) leaf area distribution in forested environments. This is made possible by the capacity of LiDAR scanners to record the 3-D position of every laser pulse intercepted by plant material. The laser pulses emitted by a LiDAR scanner can be regarded as light probes whose transmission and interception may be used to derive leaf area density at different spatial scales using the Beer-Lambert law or Warren Wilson's contact frequency method among others. Segmenting the canopy into cubic volumes -or voxels- provides a convenient means to compute light transmission statistics and describe the spatial distribution of foliage area in tree crowns. In this paper, we investigate the optimal voxel dimensions for estimating the spatial distribution of within crown leaf area density. We analyzed LiDAR measurements from two field sites, located in Mali and in California, with trees having different leaf sizes during periods with and without leaves.We found that there is a range of voxel sizes, which satisfy three important conditions. The first condition is related to clumping and requires voxels small enough to exclude large gaps between crowns and branches. The second condition requires a voxel size large enough for the conditions postulated by the Poisson law to be valid, i.e., a turbid medium with randomly positioned leaves. And, the third condition relates to the appropriate voxel size to pinpoint the location of those volumes within the canopy which were insufficiently sampled by the LiDAR instrument to derive reliable statistics (occlusion effects). Here, we show that these requirements are a function of leaf size, branching structure, and the predominance of occlusion effects. The results presented provide guiding principles for using voxel volumes in the retrieval of leaf area distributions from terrestrial LiDAR measurements. © 2013 The Authors.

Format EndNote

Vous pouvez importer cette référence dans EndNote.

Format BibTeX-CSV

Vous pouvez importer cette référence en format BibTeX-CSV.

Format BibTeX

Vous pouvez copier l'entrée BibTeX de cette référence ci-bas, ou l'importer directement dans un logiciel tel que JabRef .

@ARTICLE { BelandBaldocchiWidlowskiEtAl2014,
    AUTHOR = { Beland, M. and Baldocchi, D.D. and Widlowski, J.-L. and Fournier, R.A. and Verstraete, M.M. },
    TITLE = { On seeing the wood from the leaves and the role of voxel size in determining leaf area distribution of forests with terrestrial LiDAR },
    JOURNAL = { Agricultural and Forest Meteorology },
    YEAR = { 2014 },
    VOLUME = { 184 },
    PAGES = { 82--97 },
    ABSTRACT = { Terrestrial LiDAR scanners have been shown to hold great potential for estimating and mapping three dimensional (3-D) leaf area distribution in forested environments. This is made possible by the capacity of LiDAR scanners to record the 3-D position of every laser pulse intercepted by plant material. The laser pulses emitted by a LiDAR scanner can be regarded as light probes whose transmission and interception may be used to derive leaf area density at different spatial scales using the Beer-Lambert law or Warren Wilson's contact frequency method among others. Segmenting the canopy into cubic volumes -or voxels- provides a convenient means to compute light transmission statistics and describe the spatial distribution of foliage area in tree crowns. In this paper, we investigate the optimal voxel dimensions for estimating the spatial distribution of within crown leaf area density. We analyzed LiDAR measurements from two field sites, located in Mali and in California, with trees having different leaf sizes during periods with and without leaves.We found that there is a range of voxel sizes, which satisfy three important conditions. The first condition is related to clumping and requires voxels small enough to exclude large gaps between crowns and branches. The second condition requires a voxel size large enough for the conditions postulated by the Poisson law to be valid, i.e., a turbid medium with randomly positioned leaves. And, the third condition relates to the appropriate voxel size to pinpoint the location of those volumes within the canopy which were insufficiently sampled by the LiDAR instrument to derive reliable statistics (occlusion effects). Here, we show that these requirements are a function of leaf size, branching structure, and the predominance of occlusion effects. The results presented provide guiding principles for using voxel volumes in the retrieval of leaf area distributions from terrestrial LiDAR measurements. © 2013 The Authors. },
    COMMENT = { Export Date: 4 November 2013 Source: Scopus CODEN: AFMEE doi: 10.1016/j.agrformet.2013.09.005 },
    ISSN = { 01681923 (ISSN) },
    KEYWORDS = { 3-D leaf area distribution, Forest canopy structure, Leaf area density, Leaf area index, Terrestrial LiDAR, Voxel },
    OWNER = { Luc },
    TIMESTAMP = { 2013.11.04 },
    URL = { http://www.scopus.com/inward/record.url?eid=2-s2.0-84885446356&partnerID=40&md5=2093f60bdfb799e901da91d27e2090fb },
}

********************************************************** ***************** Facebook Twitter *********************** **********************************************************

Abonnez-vous à
l'Infolettre du CEF!

********************************************************** ************* Colloque **************************** **********************************************************

1er au 3 mai 2019
UQAC

********************************************************** ************* R à Québec 2019**************************** **********************************************************

********************************************************** ********************* Traits **************************** **********************************************************

********************************************************** ************* Écoles d'été et formation **************************** **********************************************************

Écoles d'été et formations

Cours intensif sur l'analyse des pistes 
6-10 mai 2019, Université de Sherbrooke
Cours intensif : Taxonomie et méthodes d’échantillonnage en tourbières 
6-17 mai 2019, Université Laval
Dendrochronological Fieldweek 2019 
16-21 mai 2019, Station FERLD
Traits Fonctionnels des Organismes - École thématique internationale
19-24 mai 2019, Porquerolles, France
Cours aux cycles supérieurs: Terrain avancé en géographie 
10-15 juin 2019, FERLD, Abitibi-Témiscamingue
École d'été « Drones et télédétection environnementale » 
13-14 juin 2019, Sherbrooke
Ecole d'été en Biologie et Ecologie intégratives 
6-12 juillet 2019, Pyrénées françaises
École d'été en modélisation de la biodiversité 
19-23 août 2019, Orford
Cours aux cycles supérieurs: Aménagement des écosystèmes forestiers 
19-30 août 2019, Station FERLD

********************************************************** ***************** Pub - Carapace ****************** **********************************************************

********************************************************** ***************** Pub - Budworm ****************** **********************************************************

********************************************************** ***************** Pub - Colibri **************************** **********************************************************

********************************************************** ********** Pub 6 - Au coeur de l'arbre *********** **********************************************************

...Une exposition
virtuelle sur l'arbre!

********************************************************** ***************** Boîte à trucs *************** **********************************************************

CEF-Référence
La référence vedette !

Jérémie Alluard (2016) Les statistiques au moments de la rédaction 

  • Ce document a pour but de guider les étudiants à intégrer de manière appropriée une analyse statistique dans leur rapport de recherche.

Voir les autres...