Geo-Planar Indexing (GPI) - An efficient indexing scheme for fast retrieval of raster-based geospatial data in mobile GIS applications

Yu Kai Geoffrey Shea, Jiannong Cao

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

The core objective of mobile GIS applications is to provide current vicinity geospatial information for moving clients. The success of a mobile GIS application depends mainly on the efficiency of the geospatial data delivery method used and how well the base map image can be retrieved from the geospatial database. This paper describes the derivation of an efficient indexing scheme, Geo-Planar Indexing (GPI), for fast retrieval of raster-based geospatial data under the standard RDBMS environment without using expensive R-Tree spatial access method in GIS working environments. A cost model comparison between R-Tree and GPI is conducted. A performance comparison between R-Tree and GPI was carried out to measure the retrieval times for different test locations and retrieval strategies. The empirical test result revealed that the GPI method outperforms the R-Tree access method when handling different geospatial data densities, irrespective of the mobile device platform. The performance efficiency for high, medium, and low data density was 1.3, 1.9, and 4.3, respectively.
Original languageEnglish
Title of host publication2012 5th International Congress on Image and Signal Processing, CISP 2012
Pages1047-1052
Number of pages6
DOIs
Publication statusPublished - 1 Dec 2012
Event2012 5th International Congress on Image and Signal Processing, CISP 2012 - Chongqing, China
Duration: 16 Oct 201218 Oct 2012

Conference

Conference2012 5th International Congress on Image and Signal Processing, CISP 2012
Country/TerritoryChina
CityChongqing
Period16/10/1218/10/12

Keywords

  • Dynamic mobile geospatial database
  • Geo-Planar Indexing
  • GPI
  • Mobile GIS

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing

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