Roussel2018

Référence

Roussel, J.-R. (2018) Quantification théorique des effets du paramétrage du système d'acquisition sur les variables descriptives du nuage de points LiDAR. Thèse de doctorat, Université Laval. (URL )

Résumé

The mapping of the forest resource is currently achieved through inventories made across large territories using methods of automatic or semi-automatic measurements at broad scales. Notably, the development of airborne LiDAR (light detection and ranging) has opened the way for new perspectives in this context. Despite its proven suitability as a tool for inventories and mapping, the study of the scientific literature on airborne LiDAR shows that methods for processing the acquired information remain limited, and are usually valid only for a given region of interest and for a given acquisition device. Indeed, modifying the acquisition device generates variation in the structure of the point cloud that often restrict the range of application of resource evaluation models. With the aim of moving towards models for resourcemapping that are less dependent on the characteristics of both the study area and the of acquisition device, it is important to understand the source of such variation and how to correct it. We investigated, how variations in the settings of the data acquisition systems may generate some variation in the structure of the obtained point clouds. These questions were treated using simple theoretical and mathematical models and we showed, to a certain extent, that it is possible to correct the LiDAR data, and thus to normalise measurements to simulate homogeneous acquisitions with a “standard” and unique acquisition device. The challenge pursued in this thesis is to propose and initiate, for the future, data processing methods relying on better established standards in order to build more accurate and more versatile tools for the large-scalemapping of forest resources.

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@PHDTHESIS { Roussel2018,
    TITLE = { Quantification théorique des effets du paramétrage du système d'acquisition sur les variables descriptives du nuage de points LiDAR },
    AUTHOR = { Roussel, J.-R. },
    SCHOOL = { Université Laval },
    YEAR = { 2018 },
    NOTE = { CEFTMS, Achim, A. and Beland, M. },
    ABSTRACT = { The mapping of the forest resource is currently achieved through inventories made across large territories using methods of automatic or semi-automatic measurements at broad scales. Notably, the development of airborne LiDAR (light detection and ranging) has opened the way for new perspectives in this context. Despite its proven suitability as a tool for inventories and mapping, the study of the scientific literature on airborne LiDAR shows that methods for processing the acquired information remain limited, and are usually valid only for a given region of interest and for a given acquisition device. Indeed, modifying the acquisition device generates variation in the structure of the point cloud that often restrict the range of application of resource evaluation models. With the aim of moving towards models for resourcemapping that are less dependent on the characteristics of both the study area and the of acquisition device, it is important to understand the source of such variation and how to correct it. We investigated, how variations in the settings of the data acquisition systems may generate some variation in the structure of the obtained point clouds. These questions were treated using simple theoretical and mathematical models and we showed, to a certain extent, that it is possible to correct the LiDAR data, and thus to normalise measurements to simulate homogeneous acquisitions with a “standard” and unique acquisition device. The challenge pursued in this thesis is to propose and initiate, for the future, data processing methods relying on better established standards in order to build more accurate and more versatile tools for the large-scalemapping of forest resources. },
    URL = { https://corpus.ulaval.ca/jspui/handle/20.500.11794/29758 },
    TIMESTAMP = { 2019-10-10 },
}

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