气候变化领域集成服务门户(CCPortal): Study on Spatio-Temporal Indexing Model of Geohazard Monitoring Data Based on Data Stream Clustering Algorithm

CCPortal

DOI	10.3390/ijgi13030093
	Study on Spatio-Temporal Indexing Model of Geohazard Monitoring Data Based on Data Stream Clustering Algorithm
	Li, Jiahao; Song, Weiwei; Chen, Jianglong; Wei, Qunlan; Wang, Jinxia
发表日期	2024
EISSN	2220-9964
起始页码	13
结束页码	3
卷号	13 期号:3
英文摘要	Yunnan Province, residing in the eastern segment of the Qinghai-Tibet Plateau and the western part of the Yunnan-Guizhou Plateau, faces significant challenges due to its intricate geological structures and frequent geohazards. These pose monumental risks to community safety and infrastructure. Unfortunately, conventional spatial indexing methods struggle with the enormous influx of geohazard data, exhibiting inadequacies in efficient spatio-temporal querying and failing to meet the swift response imperatives for real-time geohazard monitoring and early warning mechanisms. In response to these challenges, this study proffers a cutting-edge spatio-temporal indexing model, the BCHR-index, undergirded by data stream clustering algorithms. The operational schema of the BCHR-index model is bifurcated into two stages: real-time and offline. The real-time phase proficiently uses micro-clusters shaped by the CluStream algorithm in unison with a B+ tree to construct indices in memory, thereby satisfying the exigent response necessities for geohazard data streams. Conversely, the offline stage employs the CluStream algorithm and the Hilbert curve to manage heterogeneously distributed spatial objects. Paired with a B+ tree, this framework promotes efficient spatio-temporal querying of geohazard data. The empirical results indicate that the indexing model implemented in this study affords millisecond-level responses when faced with query requests from real-time geohazard data streams. Moreover, in aspects of spatial query efficiency and data-insertion performance, it demonstrates superior results compared to the R-tree and Hilbert-R tree models.
英文关键词	BCHR tree; CluStream; B plus tree; Hilbert curve; Hilbert-R tree; HBase
语种	英语
WOS研究方向	Computer Science ; Physical Geography ; Remote Sensing
WOS类目	Computer Science, Information Systems ; Geography, Physical ; Remote Sensing
WOS记录号	WOS:001192751400001
来源期刊	ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/297740
作者单位	Kunming University of Science & Technology
推荐引用方式 GB/T 7714	Li, Jiahao,Song, Weiwei,Chen, Jianglong,et al. Study on Spatio-Temporal Indexing Model of Geohazard Monitoring Data Based on Data Stream Clustering Algorithm[J],2024,13(3).
APA	Li, Jiahao,Song, Weiwei,Chen, Jianglong,Wei, Qunlan,&Wang, Jinxia.(2024).Study on Spatio-Temporal Indexing Model of Geohazard Monitoring Data Based on Data Stream Clustering Algorithm.ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,13(3).
MLA	Li, Jiahao,et al."Study on Spatio-Temporal Indexing Model of Geohazard Monitoring Data Based on Data Stream Clustering Algorithm".ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 13.3(2024).