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ISPRS Int. J. Geo-Inf. 2017, 6(6), 165; doi:10.3390/ijgi6060165

A High Performance, Spatiotemporal Statistical Analysis System Based on a Spatiotemporal Cloud Platform

Yunnan Provincial Geomatics Centre, Kunming 650034, Yunnan, China
Department of Geoinformation Science, Kunming University of Science and Technology, Kunming 650504, Yunnan, China
Department of Geography, Eastern China Normal University, Shanghai 200062, China
School of Remote Sensing Information and Engineering, Wuhan University, Wuhan 430071, Hubei, China
Beijing Yunhe Spatiotemporal Tehnology Co. Ltd, Beijing 100080, China
Authors to whom correspondence should be addressed.
Academic Editors: Ozgun Akcay and Wolfgang Kainz
Received: 9 February 2017 / Revised: 17 May 2017 / Accepted: 24 May 2017 / Published: 6 June 2017
View Full-Text   |   Download PDF [5248 KB, uploaded 6 June 2017]   |  


With the increase in size and complexity of spatiotemporal data, traditional methods for performing statistical analysis are insufficient for meeting real-time requirements for mining information from Big Data, due to both data- and computing-intensive factors. To solve the Big Data challenges in geostatistics and to support decision-making, a high performance, spatiotemporal statistical analysis system (Geostatistics-Hadoop) is proposed in this paper. The proposed system has several features: (1) Hadoop is enhanced to handle spatial data in a native format and execute a number of parallelized spatial analysis algorithms to solve practical geospatial analysis problems; (2) the Oozie-based workflow system is utilized to ease the operation and sharing of spatial analysis services; and (3) a private cloud platform based on Eucalyptus is leveraged to provide on-the-fly and elastic computing resources. Experimental results show that Geostatistics-Hadoop efficiently conducts rapid information mining and analysis of big spatiotemporal data sets, with the support of elastic computing resources from a cloud platform. The adoption of cloud computing and the Hadoop cluster to parallelize statistical calculations significantly improves the performance of Big Data analyses. View Full-Text
Keywords: spatiotemporal cloud platform; high-performance spatiotemporal statistical analysis system; Hadoop spatiotemporal cloud platform; high-performance spatiotemporal statistical analysis system; Hadoop

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Jin, B.; Song, W.; Zhao, K.; Wei, X.; Hu, F.; Jiang, Y. A High Performance, Spatiotemporal Statistical Analysis System Based on a Spatiotemporal Cloud Platform. ISPRS Int. J. Geo-Inf. 2017, 6, 165.

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