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ABSTRACT
Efficiently querying multiple spatial datasets is a challenging task in geoscience. The majority of spatial processing techniques use minimum bounding box (MBB) to approximate neighbouring spatial objects and and place them adjacent in the spatial index. However, due to the existence of redundant space in MBB of these methods, this problem can significantly reduce the query efficiency. In this paper, we propose a novel two-stage adaptive method of clipping the bounding box in spatial query, called IB-CBB (Intersection Based Clipped Bounding Boxes). The first stage employs a clipped bounding box, which records the redundant spatial spaces within the bounding box of the spatial index by calculating the clip points. As a result, the computational complexity of indexed child nodes in the query process is reduced. The second stage optimizes the above query algorithm by judging the intersection of the query box and the MBB of index node, significantly reducing the query time. Experiments demonstrate that IB-CBB outperforms the baseline method in terms of reducing the computational time.
Author contributions
Conceptualization, Wei Xiong; methodology, Ye Wu, Ruiqing li; software, Jingzhi Cao and Ruiqing li; formal analysis, Wei Xiong, Jingzhi Cao and Ruiqing Li; resources, Jingzhi Cao, Ruiqing li, Wei Xiong; writing – original draft preparation, Jingzhi Cao, Ye Wu; writing – review and editing, Wei Xiong; visualization, Ye Wu, Jingzhi Cao; project administration, Jingzhi Cao; funding acquisition, Wei Xiong. All authors have read and agreed to the published version of the manuscript.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
Benchmark Dataset:https://www.mathematik.uni-marburg.de/seeger/rrstar/index.html