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N. Sirdeshmukh
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Discrete Global Grid Systems (DGGS) have emerged in recent years as a new specification for working with global heterogeneous datasets of different types, such as vector, raster, and quantitative datasets. There exists no research on using point clouds with a DGGS. This research aims to analyse the extent to which a DGGS can be used to handle LIDAR point clouds having varying coordinate systems, acquired at different levels of detail, and at different times in the creation of a global ‘map’ of point clouds. Various ways of mapping and modelling the Earth, indexing strategies for creating a continuous index of the surface of the Earth (including what is above and below it), performing analysis of 2D, 3D or 4D point clouds using DGGS, and the querying and visualization of massive point clouds is discussed. A DGGS is compared and contrasted with conventional coordinate systems. The advantages, opportunities, challenges, and limitations of point cloud integration in a DGGS are presented.
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Discrete Global Grid Systems (DGGS) have emerged in recent years as a new specification for working with global heterogeneous datasets of different types, such as vector, raster, and quantitative datasets. There exists no research on using point clouds with a DGGS. This research aims to analyse the extent to which a DGGS can be used to handle LIDAR point clouds having varying coordinate systems, acquired at different levels of detail, and at different times in the creation of a global ‘map’ of point clouds. Various ways of mapping and modelling the Earth, indexing strategies for creating a continuous index of the surface of the Earth (including what is above and below it), performing analysis of 2D, 3D or 4D point clouds using DGGS, and the querying and visualization of massive point clouds is discussed. A DGGS is compared and contrasted with conventional coordinate systems. The advantages, opportunities, challenges, and limitations of point cloud integration in a DGGS are presented.
Towards point cloud harmonization
Harmonization of point cloud datasets with varying coordinate reference systems
Student report
(2017)
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Neeraj Sirdeshmukh, Lydia Kotoula, Antria Christodoulou, Manuela Manolova, Laurens Oostwegel, Edward Verbree, P.J.M. van Oosterom, Stefan van der Spek
This paper has its focus on the accessibility, interoperability and quality of different point cloud datasets. The main objective of the project is to research the process of harmonizing point cloud datasets of different origins and to incorporate the integrated datasets in a web viewer that allows for visualization and analysis. As a case study, the Three-Country Point (TCP) where Germany, Belgium, and the Netherlands share a border is evaluated.
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This paper has its focus on the accessibility, interoperability and quality of different point cloud datasets. The main objective of the project is to research the process of harmonizing point cloud datasets of different origins and to incorporate the integrated datasets in a web viewer that allows for visualization and analysis. As a case study, the Three-Country Point (TCP) where Germany, Belgium, and the Netherlands share a border is evaluated.