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Open AccessArticle

An Effective NoSQL-Based Vector Map Tile Management Approach

1, 2,* and 3,4
Faculty of Information Engineering, China University of Geosciences, Wuhan 430074, China
Institute of Remote Sensing & GIS, Peking University, Beijing 100871, China
Institute of Tourism, Beijing Union University, Beijing 100101, China
State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Author to whom correspondence should be addressed.
Academic Editors: Bert Veenendaal, Maria Antonia Brovelli, Serena Coetzee, Peter Mooney and Wolfgang Kainz
ISPRS Int. J. Geo-Inf. 2016, 5(11), 215;
Received: 15 August 2016 / Revised: 4 November 2016 / Accepted: 5 November 2016 / Published: 12 November 2016
(This article belongs to the Special Issue Web/Cloud Based Mapping and Geoinformation)
PDF [5989 KB, uploaded 12 November 2016]


Within a digital map service environment, the rapid growth of Spatial Big-Data is driving new requirements for effective mechanisms for massive online vector map tile processing. The emergence of Not Only SQL (NoSQL) databases has resulted in a new data storage and management model for scalable spatial data deployments and fast tracking. They better suit the scenario of high-volume, low-latency network map services than traditional standalone high-performance computer (HPC) or relational databases. In this paper, we propose a flexible storage framework that provides feasible methods for tiled map data parallel clipping and retrieval operations within a distributed NoSQL database environment. We illustrate the parallel vector tile generation and querying algorithms with the MapReduce programming model. Three different processing approaches, including local caching, distributed file storage, and the NoSQL-based method, are compared by analyzing the concurrent load and calculation time. An online geological vector tile map service prototype was developed to embed our processing framework in the China Geological Survey Information Grid. Experimental results show that our NoSQL-based parallel tile management framework can support applications that process huge volumes of vector tile data and improve performance of the tiled map service. View Full-Text
Keywords: digital map; map tile; NoSQL; MapReduce; cloud computing digital map; map tile; NoSQL; MapReduce; cloud computing

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Wan, L.; Huang, Z.; Peng, X. An Effective NoSQL-Based Vector Map Tile Management Approach. ISPRS Int. J. Geo-Inf. 2016, 5, 215.

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