CoteFournierEgli2011

Référence

Cote, J.-F., Fournier, R.A. and Egli, R. (2011) An architectural model of trees to estimate forest structural attributes using terrestrial LiDAR. Environmental Modelling and Software, 26(6):761-777. (Scopus )

Résumé

Terrestrial lidar (TLiDAR) has been used increasingly over recent years to assess tree architecture and to extract metrics of forest canopies. Analysis of TLiDAR data remains a difficult task mainly due to the effects of object occlusion and wind on the quality of the retrieved results. We propose to link TLiDAR and tree structure attributes by means of an architectural model. The proposed methodology uses TLiDAR scans combined with allometric relationships to define the total amount of foliage in the crown and to build the tree branching structure. It uses the range (distance) and intensity information of the TLiDAR scans (i) to extract the stem and main branches of the tree, (ii) to reconstruct the fine branching structure at locations where the presence of foliage is very likely, and (iii) to use the availability of light as a criterion to add foliage in the center of the crown where TLiDAR information is sparse or absent due to occlusion effects. An optimization algorithm guides the model towards a realistic tree structure that fits the information gathered from TLiDAR scans and field inventory. The robustness and validity of the proposed model is assessed on five trees belonging to four different conifer species from natural forest environments. This approach addresses the data limitation of TLiDAR scans and aims to extract forest architectural metrics at different structural levels. © 2010.

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@ARTICLE { CoteFournierEgli2011,
    AUTHOR = { Cote, J.-F. and Fournier, R.A. and Egli, R. },
    TITLE = { An architectural model of trees to estimate forest structural attributes using terrestrial LiDAR },
    JOURNAL = { Environmental Modelling and Software },
    YEAR = { 2011 },
    VOLUME = { 26 },
    PAGES = { 761-777 },
    NUMBER = { 6 },
    ABSTRACT = { Terrestrial lidar (TLiDAR) has been used increasingly over recent years to assess tree architecture and to extract metrics of forest canopies. Analysis of TLiDAR data remains a difficult task mainly due to the effects of object occlusion and wind on the quality of the retrieved results. We propose to link TLiDAR and tree structure attributes by means of an architectural model. The proposed methodology uses TLiDAR scans combined with allometric relationships to define the total amount of foliage in the crown and to build the tree branching structure. It uses the range (distance) and intensity information of the TLiDAR scans (i) to extract the stem and main branches of the tree, (ii) to reconstruct the fine branching structure at locations where the presence of foliage is very likely, and (iii) to use the availability of light as a criterion to add foliage in the center of the crown where TLiDAR information is sparse or absent due to occlusion effects. An optimization algorithm guides the model towards a realistic tree structure that fits the information gathered from TLiDAR scans and field inventory. The robustness and validity of the proposed model is assessed on five trees belonging to four different conifer species from natural forest environments. This approach addresses the data limitation of TLiDAR scans and aims to extract forest architectural metrics at different structural levels. © 2010. },
    COMMENT = { Cited By (since 1996): 2 Export Date: 6 August 2012 Source: Scopus CODEN: EMSOF doi: 10.1016/j.envsoft.2010.12.008 },
    ISSN = { 13648152 (ISSN) },
    KEYWORDS = { Optimization, Remote sensing, Terrestrial LiDAR, Tree Architectural Model, Tree structure, Allometric relationship, Architectural models, Branching structures, Conifer species, Data limitations, Field inventories, Forest canopies, Forest structural attributes, Intensity information, Natural forests, Object occlusion, Occlusion effect, Optimization algorithms, Terrestrial LiDAR, Tree Architectural Model, Tree structure, Tree structures, Forestry, Optical radar, Remote sensing, Structural optimization, allometry, coniferous tree, forest canopy, forestry modeling, lidar, optimization, remote sensing, Forest Canopy, Forestry, Mathematical Models, Optical Instruments, Optimization, Radar, Remote Sensing, Trees, Coniferophyta },
    OWNER = { Luc },
    TIMESTAMP = { 2012.08.06 },
    URL = { http://www.scopus.com/inward/record.url?eid=2-s2.0-79951726255&partnerID=40&md5=2b4973c6e57e9c86c56f58db2a5cc632 },
}

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