Error-bounded and Number-bounded Approximate Spatial Query for Interactive Visualization

Abstract: In the big data era, an enormous amount of spatial and spatiotemporal data are generated every day. However, spatial query result sets that satisfy a query condition are very large, sometimes over hundreds or thousands of terabytes. Interactive visualization of big geospatial data calls for continuous query requests, and large query results prevent visual efficiency. Furthermore, traditional methods based on random sampling or line simplification are not suitable for spatial data visualization with bounded errors and bound vertex numbers. In this paper, we propose a vertex sampling method—the Balanced Douglas Peucker (B-DP) algorithm—to build hierarchical structures, where the order and weights of vertices are preserved in binary trees. Then, we develop query processing algorithms with bounded errors and bounded numbers, where the vertices are retrieved by binary trees’ breadth-first-searching (BFS) with a maximum-error-first (MEF) queue. Finally, we conduct an experimental study with OpenStreetMap (OSM) data to determine the effectiveness of our query method in interactive visualization. The results show that the proposed approach can markedly reduce the query results’ size and maintain high accuracy, and its performance is robust against the data volume.

Standort
Deutsche Nationalbibliothek Frankfurt am Main
Umfang
Online-Ressource
Sprache
Englisch

Erschienen in
Error-bounded and Number-bounded Approximate Spatial Query for Interactive Visualization ; volume:10 ; number:1 ; year:2018 ; pages:491-503 ; extent:13
Open Geosciences ; 10, Heft 1 (2018), 491-503 (gesamt 13)

Urheber
Qiu, Agen
Zhang, Zhiran
Qian, Xinlin
He, Wangjun

DOI
10.1515/geo-2018-0039
URN
urn:nbn:de:101:1-2501051532146.698074086187
Rechteinformation
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Letzte Aktualisierung
15.08.2025, 07:37 MESZ

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Beteiligte

  • Qiu, Agen
  • Zhang, Zhiran
  • Qian, Xinlin
  • He, Wangjun

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