Utilizing a Discrete Global Grid System for Handling Point Clouds with Varying Locations, Times, and Levels of Detail
Bibliographic Data
| ID | 14701435 |
|---|---|
| Authors | Neeraj Sirdeshmukh (MSc Geomatics / Delft University of Technology / Delft / Zuid-Holland / Netherlands, corresponding author), E Verbree (0000-0002-6892-6702, Delft University of Technology), Peter van Oosterom (0000-0003-3874-4737, Section GIS Technology / Delft University of Technology / Delft / Zuid-Holland / Netherlands), Stella Psomadaki (Regional Innovation Centre Europe / Fugro / Leidschendam / Zuid-Holland / Netherlands), Martin Kodde (Ingenieursbureau Geodelta B.V. / Delft / Zuid-Holland / Netherlands) |
| Year | 2019 |
| Volume | 54 |
| Issue | 1 |
| Pages | 4-15 |
| Publication date | 2019-03-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Cartographica The International Journal for Geographic Information and Geovisualization (JOURNAL) |
| Journal identifiers | ISSN: 0317-7173 • E-ISSN: 1911-9925 |
| Publisher | University of Toronto Press Inc. (UTPress) (PUBLISHER) |
| DOI | 10.3138/cart.54.1.2018-0009 |
| OpenAlex | W2909812584 |
| Language | EN |
| Citations received | 6 |
| References cited | 10 |
Discrete global grid systems (DGGSs) have emerged in recent years as a new specification for working with global heterogeneous data sets in a Digital Earth framework. Point clouds originating from different sources usually have varying initial characteristics. This research aims to analyze to what extent a DGGS can be used to handle point clouds having varying coordinate systems, acquired at different levels of detail (densities), and at different times in the creation of a global map of point clouds. DGGSs, which are currently limited to a 2D (surface) space, are extended into 3D and 4D spaces to fully harness the multidimensional nature of point clouds. A continuous spatial indexing strategy, based on a space-filling curve, is then developed on an ellipsoidal model of the Earth and used to efficiently cluster and retrieve DGGS-based point clouds stored in a database. Finally, the queried points are visualized in a Web browser. The hierarchical, multi-resolution nature of a DGGS is exploited to achieve a variable-scale smooth-zoom visualization. The challenges and opportunities of point cloud integration in a DGGS are presented
Cloud computing · Computational science · Computer vision · Coordinate system · Data mining · Distributed computing · Geodesy · Geography · Geometry · Grid · Point (geometry · Point cloud · Visualization · Zoom · 3D Modeling in Geospatial Applications · Computer Graphics and Visualization Techniques · Computer Science · Mathematics · Remote Sensing and LiDAR Applications · Geology
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| Citations per year | 1 |
|---|---|
| Citation span | 2020 - 2023 (4) |
| Highly cited | No |