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author:

Zhu, D. (Zhu, D..) [1] | huang, M. (huang, M..) [2] | Lin, Q. (Lin, Q..) [3] | Wang, Y. (Wang, Y..) [4] | Li, S. (Li, S..) [5] | Cheng, C. (Cheng, C..) [6]

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Scopus

Abstract:

With the increasing popularity of sensors and the rapid advancement of network infrastructure and communication technology, managing, retrieving, and applying ubiquitous location information (ULI) poses a significant challenge. This study introduces the concept of the geospatial grid region name (GGRN) and proposes a ULI management method based on the GGRN (UMMG). To evaluate the feasibility and retrieval efficiency of the UMMG, it was applied to mainstream databases and compared with their spatial expansion modules. The experimental results demonstrate that the UMMG effectively addresses the challenge of precise location cognition between humans and machines while also reducing the complexity of spatial database indexing, with an overall performance improvement of 43.00 % compared to Oracle Spatial and 33.30 % compared to PostgreSQL + PostGIS. © 2025 The Authors

Keyword:

Geospatial grid region name Geospatial region space Grid management Subdivision index big table Ubiquitous location information

Community:

  • [ 1 ] [Zhu D.]College of Computer and Data Science, Fuzhou University, Fuzhou, 350108, China
  • [ 2 ] [Zhu D.]Center for Data Science, Peking University, Beijing, 100871, China
  • [ 3 ] [Zhu D.]Department of Geography, Geomatics and Environment, University of Toronto, Mississauga, L5L 1C6, Canada
  • [ 4 ] [huang M.]School of Geography and Environment, Jiangxi Normal University, Nanchang, 330022, China
  • [ 5 ] [huang M.]State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, 430079, China
  • [ 6 ] [Lin Q.]College of Computer and Data Science, Fuzhou University, Fuzhou, 350108, China
  • [ 7 ] [Wang Y.]College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China
  • [ 8 ] [Li S.]Institute of Chinese Historical Geography, Fudan University, Shanghai, 200433, China
  • [ 9 ] [Cheng C.]Center for Data Science, Peking University, Beijing, 100871, China
  • [ 10 ] [Cheng C.]College of Engineering, Peking University, Beijing, 100871, China

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Source :

International Journal of Applied Earth Observation and Geoinformation

ISSN: 1569-8432

Year: 2025

Volume: 137

7 . 6 0 0

JCR@2023

CAS Journal Grade:2

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 0

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