Next Article in Journal
Belgium through the Lens of Rail Travel Requests: Does Geography Still Matter?
Next Article in Special Issue
One-Page Multimedia Interactive Map
Previous Article in Journal
Efficient Geo-Computational Algorithms for Constructing Space-Time Prisms in Road Networks
Previous Article in Special Issue
Generating Orthorectified Multi-Perspective 2.5D Maps to Facilitate Web GIS-Based Visualization and Exploitation of Massive 3D City Models
Article Menu
Issue 11 (November) cover image

Export Article

Open AccessArticle
ISPRS Int. J. Geo-Inf. 2016, 5(11), 215; doi:10.3390/ijgi5110215

An Effective NoSQL-Based Vector Map Tile Management Approach

1
,
2,* and 3,4
1
Faculty of Information Engineering, China University of Geosciences, Wuhan 430074, China
2
Institute of Remote Sensing & GIS, Peking University, Beijing 100871, China
3
Institute of Tourism, Beijing Union University, Beijing 100101, China
4
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
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)

Abstract

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
Figures

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).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

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

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
ISPRS Int. J. Geo-Inf. EISSN 2220-9964 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top