Building a spatiotemporal index for Earth Observation Big Data

被引:21
|
作者
Xia, Jizhe [1 ,2 ,4 ]
Yang, Chaowei [3 ]
Li, Qingquan [1 ,2 ,4 ]
机构
[1] Shenzhen Univ, Sch Architecture & Urban Planning, Shenzhen Key Lab Spatial Informat Smart Sensing &, Shenzhen, Peoples R China
[2] Shenzhen Univ, Res Inst Smart Cities, Shenzhen, Peoples R China
[3] George Mason Univ, NSF Spatiotemporal Innovat Ctr, Fairfax, VA 22030 USA
[4] Shenzhen Univ, Key Lab Geoenvironm Monitoring Coastal Zone, Natl Adm Surveying Mapping & GeoInformat, Shenzhen, Peoples R China
基金
中国国家自然科学基金;
关键词
GEOSS; Spatial data infrastructure; Data indexing; Information retrieval; Earth observation big data; GEOSS CLEARINGHOUSE; PRINCIPLES;
D O I
10.1016/j.jag.2018.04.012
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
With the rapid advancement of Earth Observation systems, Earth Observation data has been collected and accumulated at an unprecedented fast rate. Earth Observation Big Data emerged with new opportunities for human to better understand the Earth systems, but also pose a tremendous challenge for efficiently transforming Big Data into Earth Observation Big Value. Targeting on this challenge, a well-organized data index is a key to enhance the "Data-Value" transformation by accelerating the access to data. Although various data indexing approaches have been proposed with different optimization objectives, literature shows that there are still apparent limitations for Earth Observation data indexing. This paper aims to build a spatiotemporal indexing for Earth Observation Big Data. Specifically, a) to support various Earth Observation Data Infrastructures, we adopt an indexing framework to efficiently retrieve data with various textual, spatial and temporal requirements; b) a distributed indexing structure is designed to improve the index scalability; c) data access pattern is integrated to the indexing algorithm for both spatial and workload balancing. The results show that our indexing approach outperforms traditional indexing approaches and accelerates the access to Earth Observation data. We envision that data indexing will become a key technology that drives fundamental Earth Observation advancements in the Big Data era.
引用
收藏
页码:245 / 252
页数:8
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