QRB-tree Indexing: Optimized Spatial Index Expanding upon the QR-tree Index

Support for region queries is crucial in geographic information systems, which process exact queries through spatial indexing to filter features and subsequently refine the selection. Although the filtering step has been extensively studied, the refinement step has received little attention. This re...

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Autores principales:	Jieqing Yu, Yi Wei, Qi Chu, Lixin Wu
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	spatial indexing QRB-tree index QR-tree index region query rough query exact query Geography (General) G1-922
Acceso en línea:	https://doaj.org/article/d55bde1c8eef430f8d1562728a4aee27
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id	oai:doaj.org-article:d55bde1c8eef430f8d1562728a4aee27
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spelling	oai:doaj.org-article:d55bde1c8eef430f8d1562728a4aee272021-11-25T17:52:46ZQRB-tree Indexing: Optimized Spatial Index Expanding upon the QR-tree Index10.3390/ijgi101107272220-9964https://doaj.org/article/d55bde1c8eef430f8d1562728a4aee272021-10-01T00:00:00Zhttps://www.mdpi.com/2220-9964/10/11/727https://doaj.org/toc/2220-9964Support for region queries is crucial in geographic information systems, which process exact queries through spatial indexing to filter features and subsequently refine the selection. Although the filtering step has been extensively studied, the refinement step has received little attention. This research builds upon the QR-tree index, which decomposes space into hierarchical grids, registers features to the grids, and builds an R-tree for each grid, to develop a new QRB-tree index with two levels of optimization. In the first level, a bucket is introduced in every grid in the QR-tree index to accelerate the loading and search steps of a query region for the grids within the query region. In the second level, the number of candidate features to be eliminated is reduced by limiting the features to those registered to the grids covering the corners of the query region. Subsequently, an approach for determining the maximal grid level, which significantly affects the performance of the QR-tree index, is proposed. Direct comparisons of time costs with the QR-tree index and geohash index show that the QRB-tree index outperforms the other two approaches for rough queries in large query regions and exact queries in all cases.Jieqing YuYi WeiQi ChuLixin WuMDPI AGarticlespatial indexingQRB-tree indexQR-tree indexregion queryrough queryexact queryGeography (General)G1-922ENISPRS International Journal of Geo-Information, Vol 10, Iss 727, p 727 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	spatial indexing QRB-tree index QR-tree index region query rough query exact query Geography (General) G1-922
spellingShingle	spatial indexing QRB-tree index QR-tree index region query rough query exact query Geography (General) G1-922 Jieqing Yu Yi Wei Qi Chu Lixin Wu QRB-tree Indexing: Optimized Spatial Index Expanding upon the QR-tree Index
description	Support for region queries is crucial in geographic information systems, which process exact queries through spatial indexing to filter features and subsequently refine the selection. Although the filtering step has been extensively studied, the refinement step has received little attention. This research builds upon the QR-tree index, which decomposes space into hierarchical grids, registers features to the grids, and builds an R-tree for each grid, to develop a new QRB-tree index with two levels of optimization. In the first level, a bucket is introduced in every grid in the QR-tree index to accelerate the loading and search steps of a query region for the grids within the query region. In the second level, the number of candidate features to be eliminated is reduced by limiting the features to those registered to the grids covering the corners of the query region. Subsequently, an approach for determining the maximal grid level, which significantly affects the performance of the QR-tree index, is proposed. Direct comparisons of time costs with the QR-tree index and geohash index show that the QRB-tree index outperforms the other two approaches for rough queries in large query regions and exact queries in all cases.
format	article
author	Jieqing Yu Yi Wei Qi Chu Lixin Wu
author_facet	Jieqing Yu Yi Wei Qi Chu Lixin Wu
author_sort	Jieqing Yu
title	QRB-tree Indexing: Optimized Spatial Index Expanding upon the QR-tree Index
title_short	QRB-tree Indexing: Optimized Spatial Index Expanding upon the QR-tree Index
title_full	QRB-tree Indexing: Optimized Spatial Index Expanding upon the QR-tree Index
title_fullStr	QRB-tree Indexing: Optimized Spatial Index Expanding upon the QR-tree Index
title_full_unstemmed	QRB-tree Indexing: Optimized Spatial Index Expanding upon the QR-tree Index
title_sort	qrb-tree indexing: optimized spatial index expanding upon the qr-tree index
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/d55bde1c8eef430f8d1562728a4aee27
work_keys_str_mv	AT jieqingyu qrbtreeindexingoptimizedspatialindexexpandingupontheqrtreeindex AT yiwei qrbtreeindexingoptimizedspatialindexexpandingupontheqrtreeindex AT qichu qrbtreeindexingoptimizedspatialindexexpandingupontheqrtreeindex AT lixinwu qrbtreeindexingoptimizedspatialindexexpandingupontheqrtreeindex
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QRB-tree Indexing: Optimized Spatial Index Expanding upon the QR-tree Index

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