X. Tan, L. Di, M. Deng, A. Chen, Z. Sun, C. Huang, Y. Shao, X. Ye

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations


Flooding caused serious losses in China in the past two decades; therefore, responding to and mitigating the impact of flooding is a task of critical importance. The traditional flood response process is usually very time-consuming and labor-intensive. The Service-Oriented Architecture ï1/4SOAï1/4‰-based flood response is a method with low efficiency due to the large volume of geospatial data transfer, and this method cannot meet the real-time requirement of a rapid response to flooding. This paper presents an Agent- and Cloud-supported geospatial service aggregation to obtain a more efficient geospatial service system for the response to flooding. The architecture of this method is designed and deployed on the Cloud environment, and the flooding response prototype system is built on the Amazon AWS Cloud to demonstrate that the proposed method can avoid transferring large volumes of geospatial data or Big Spatial Data. Consequently, this method is able to achieve better performance than that of the SOA-based method.

Original languageEnglish (US)
Pages (from-to)13-18
Number of pages6
JournalISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Issue number4W2
StatePublished - Jul 10 2015
Externally publishedYes
Event1st International Symposium on Spatiotemporal Computing, ISSC 2015 - Fairfax, United States
Duration: Jul 13 2015Jul 15 2015

All Science Journal Classification (ASJC) codes

  • Earth and Planetary Sciences (miscellaneous)
  • Environmental Science (miscellaneous)
  • Instrumentation


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