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TitleLe GeoHashTree, une structure de données multirésolution pour la gestion des nuages de points
AuthorSabo, N; Beaulieu, A; Bélanger, D; Belzile, Y; Piché, B
SourceGeomatics Canada, Technical Note 4, 2014, 17 pages, (Open Access)
PublisherNatural Resources Canada
Mediaon-line; digital
RelatedThis publication is a translation of Sabo, N; Beaulieu, A; Bélanger, D; Belzile, Y; Piché, B; (2014). The GeoHashTree: a multi-resolution data structure for the management of point clouds, Geomatics Canada, Technical Note no. 4E
File formatpdf
Subjectsgeophysics; remote sensing; satellite imagery; data base management systems; LiDAR; GeoHashTree; digital elevation models
Illustrationsdiagrams; flow charts; plots
ProgramGeobase 2.0, Elevation Grid
Released2014 03 27
AbstractOver a number of years, LiDAR has become one of the major elevation data acquisition technologies. However, the management of LiDAR data is extremely complex due to the phenomenal amount of data generated by the technology. To facilitate LiDAR data management, this article proposes a GeoHashTree, which is a multi-resolution data structure for managing different types of point clouds. GeoHashTree is a hierarchical structure which can present irregular data with various levels of abstraction. In addition to facilitating the management of point clouds, the structure minimizes data storage space considerably, while also facilitating data access and handling. In this article we present this structure. In addition to introducing the GeoHashTree, the article also describes a prototype based on the structure.
Summary(Plain Language Summary, not published)
Elevation data sources are invaluable information for many applications. For example in floodplains studies, study of geological activities and exploitation of mineral resources. Since a number of years, acquisition technologies for elevation data have become increasingly efficient. Although these technologies generate data of high accuracy, one should notice the huge amount of data generated which poses serious challenges in terms of management and operations. For example, technologies such as LiDAR is capable of generating more than a million points in a single second. To facilitate management and operation of large data such as LiDAR the National Altimetry Strategy project has developed a new data structure called GeoHashTree. This structure allows management of any typoe of point cloud while minimizing storage space and facilitating exploitation. This structure also allows integration of data at different resolutions, and presents the same data at different levels of abstraction.