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LOCALIS: Locally-adaptive Line Simplification for GPU-based Geographic Vector Data Visualization

Amiraghdam, Alireza; Diehl, Alexandra; Pajarola, R (2020). LOCALIS: Locally-adaptive Line Simplification for GPU-based Geographic Vector Data Visualization. Computer Graphics Forum, 39(3):443-453.

Abstract

Visualization of large vector line data is a core task in geographic and cartographic systems. Vector maps are often displayed at different cartographic generalization levels, traditionally by using several discrete levels-of-detail (LODs). This limits the generalization levels to a fixed and predefined set of LODs, and generally does not support smooth LOD transitions. How- ever, fast GPUs and novel line rendering techniques can be exploited to integrate dynamic vector map LOD management into GPU-based algorithms for locally-adaptive line simplification and real-time rendering. We propose a new technique that inter- actively visualizes large line vector datasets at variable LODs. It is based on the Douglas-Peucker line simplification principle, generating an exhaustive set of line segments whose specific subsets represent the lines at any variable LOD. At run time, an appropriate and view-dependent error metric supports screen-space adaptive LOD levels and the display of the correct subset of line segments accordingly. Our implementation shows that we can simplify and display large line datasets interactively. We can successfully apply line style patterns, dynamic LOD selection lenses, and anti-aliasing techniques to our line rendering.

Additional indexing

Contributors:Computer Graphics Forum
Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Scopus Subject Areas:Physical Sciences > Computer Graphics and Computer-Aided Design
Uncontrolled Keywords:visualization, geographic information systems, vector maps, simplification, level-of-detail
Scope:Discipline-based scholarship (basic research)
Language:English
Date:June 2020
Deposited On:18 Dec 2020 05:15
Last Modified:09 Mar 2025 04:35
Publisher:Wiley-Blackwell Publishing, Inc.
ISSN:0167-7055
OA Status:Closed
Publisher DOI:https://doi.org/10.1111/cgf.13993
Other Identification Number:merlin-id:20183

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