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Article

An Efficient Graph-Based Spatio-Temporal Indexing Method for Task-Oriented Multi-Modal Scene Data Organization

by
Bin Feng
1,
Qing Zhu
1,*,
Mingwei Liu
1,
Yun Li
1,
Junxiao Zhang
1,
Xiao Fu
1,
Yan Zhou
2,*,
Maosu Li
1,
Huagui He
3 and
Weijun Yang
3
1
Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 610031, China
2
School of Resource and Environment, University of Electric Science and Technology, Chengdu 611731, China
3
Guangzhou Urban Planning & Design Survey Research Institute, Guangzhou 510060, China
*
Authors to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2018, 7(9), 371; https://doi.org/10.3390/ijgi7090371
Submission received: 13 July 2018 / Revised: 2 September 2018 / Accepted: 4 September 2018 / Published: 8 September 2018
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Abstract

Task-oriented scene data in big data and cloud environments of a smart city that must be time-critically processed are dynamic and associated with increasing complexities and heterogeneities. Existing hybrid tree-based external indexing methods are input/output (I/O)-intensive, query schema-fixed, and difficult when representing the complex relationships of real-time multi-modal scene data; specifically, queries are limited to a certain spatio-temporal range or a small number of selected attributes. This paper proposes a new spatio-temporal indexing method for task-oriented multi-modal scene data organization. First, a hybrid spatio-temporal index architecture is proposed based on the analysis of the characteristics of scene data and the driving forces behind the scene tasks. Second, a graph-based spatio-temporal relation indexing approach, named the spatio-temporal relation graph (STR-graph), is constructed for this architecture. The global graph-based index, internal and external operation mechanisms, and optimization strategy of the STR-graph index are introduced in detail. Finally, index efficiency comparison experiments are conducted, and the results show that the STR-graph performs excellently in index generation and can efficiently address the diverse requirements of different visualization tasks for data scheduling; specifically, the STR-graph is more efficient when addressing complex and uncertain spatio-temporal relation queries.
Keywords: multi-modal scene data; graph-based index; spatio-temporal relation query; visualization task; data organization multi-modal scene data; graph-based index; spatio-temporal relation query; visualization task; data organization

Share and Cite

MDPI and ACS Style

Feng, B.; Zhu, Q.; Liu, M.; Li, Y.; Zhang, J.; Fu, X.; Zhou, Y.; Li, M.; He, H.; Yang, W. An Efficient Graph-Based Spatio-Temporal Indexing Method for Task-Oriented Multi-Modal Scene Data Organization. ISPRS Int. J. Geo-Inf. 2018, 7, 371. https://doi.org/10.3390/ijgi7090371

AMA Style

Feng B, Zhu Q, Liu M, Li Y, Zhang J, Fu X, Zhou Y, Li M, He H, Yang W. An Efficient Graph-Based Spatio-Temporal Indexing Method for Task-Oriented Multi-Modal Scene Data Organization. ISPRS International Journal of Geo-Information. 2018; 7(9):371. https://doi.org/10.3390/ijgi7090371

Chicago/Turabian Style

Feng, Bin, Qing Zhu, Mingwei Liu, Yun Li, Junxiao Zhang, Xiao Fu, Yan Zhou, Maosu Li, Huagui He, and Weijun Yang. 2018. "An Efficient Graph-Based Spatio-Temporal Indexing Method for Task-Oriented Multi-Modal Scene Data Organization" ISPRS International Journal of Geo-Information 7, no. 9: 371. https://doi.org/10.3390/ijgi7090371

APA Style

Feng, B., Zhu, Q., Liu, M., Li, Y., Zhang, J., Fu, X., Zhou, Y., Li, M., He, H., & Yang, W. (2018). An Efficient Graph-Based Spatio-Temporal Indexing Method for Task-Oriented Multi-Modal Scene Data Organization. ISPRS International Journal of Geo-Information, 7(9), 371. https://doi.org/10.3390/ijgi7090371

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