4.7 Article

GeoFairy: Towards a one-stop and location based Service for Geospatial Information Retrieval

期刊

COMPUTERS ENVIRONMENT AND URBAN SYSTEMS
卷 62, 期 -, 页码 156-167

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.compenvurbsys.2016.11.007

关键词

One-stop service; LBS; Geospatial web service; Geospatial cloud; Geospatial mobile application

资金

  1. NSF EarthCube [ICER-1440294]
  2. U.S. Department of Energy [DE-NA0001123]
  3. OGC Testbed 12
  4. ICER
  5. Directorate For Geosciences [1440294] Funding Source: National Science Foundation

向作者/读者索取更多资源

It is still a great challenge to efficiently deliver dynamic and heterogeneous Earth observation (EO) information to users based on their real time locations. However, the rapidly evolving techniques create a chance to meet the challenge. This paper proposes a framework to realize a one-stop and location based service (LBS) for geospatial information (GI) retrieval on mobile platforms. The framework originally integrates a number of state-of-the-art techniques with geospatial data resources and let them cooperate together to provide a robust and highly available LBS. Cloud platform is used to deploy the server module. A location enabled load balancing algorithm is presented to balance the cloud instance VMs on behalf of LBS. A system named GeoFairy is implemented. It provides a one-stop service for gathering and delivering twelve kinds of GI on real time locations. Two Apps are built for the major mobile ecosystems: iOS and Android. Many tests, including a stress test, have been made via a number of mobile devices at various locations. The results demonstrate that GeoFairy is capable of one-stop delivering real-time GI to users and significantly reducing costs on information searching and retrieving. This feature is very helpful in many scenarios such as disaster responding and military actions. This research paves a way on both theoretical and practical aspects for researchers and developers to realize operational mobile applications for one stop and location based GI retrieval. (C) 2016 Elsevier Ltd. All rights reserved.

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