AGENT- and CLOUD-SUPPORTED GEOSPATIAL SERVICE AGGREGATION for FLOOD RESPONSE

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

doi:10.5194/isprsannals-II-4-W2-13-2015

AGENT- and CLOUD-SUPPORTED GEOSPATIAL SERVICE AGGREGATION for FLOOD RESPONSE

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

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

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 language	English (US)
Pages (from-to)	13-18
Number of pages	6
Journal	ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Volume	2
Issue number	4W2
DOIs	https://doi.org/10.5194/isprsannals-II-4-W2-13-2015
State	Published - Jul 10 2015
Externally published	Yes
Event	1st International Symposium on Spatiotemporal Computing, ISSC 2015 - Fairfax, United States Duration: Jul 13 2015 → Jul 15 2015

All Science Journal Classification (ASJC) codes

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

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10.5194/isprsannals-II-4-W2-13-2015

Cite this

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title = "AGENT- and CLOUD-SUPPORTED GEOSPATIAL SERVICE AGGREGATION for FLOOD RESPONSE",

abstract = "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 {\"i}1/4SOA{\"i}1/4‰-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.",

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

note = "Funding Information: The authors thank the editors and the reviewers for their outstanding comments and suggestions, which greatly helped to improve the technical quality of the manuscript. This work was supported in part by NSFC projects 51277167; “CAST Innovation Fund”: the Study of Agent and Cloud Based Spatial Big Data Service Chain.; 1st International Symposium on Spatiotemporal Computing, ISSC 2015 ; Conference date: 13-07-2015 Through 15-07-2015",

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T1 - AGENT- and CLOUD-SUPPORTED GEOSPATIAL SERVICE AGGREGATION for FLOOD RESPONSE

AU - Tan, X.

AU - Di, L.

AU - Deng, M.

AU - Chen, A.

AU - Sun, Z.

AU - Huang, C.

AU - Shao, Y.

AU - Ye, X.

N1 - Funding Information: The authors thank the editors and the reviewers for their outstanding comments and suggestions, which greatly helped to improve the technical quality of the manuscript. This work was supported in part by NSFC projects 51277167; “CAST Innovation Fund”: the Study of Agent and Cloud Based Spatial Big Data Service Chain.

PY - 2015/7/10

Y1 - 2015/7/10

N2 - 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.

AB - 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.

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AN - SCOPUS:85017506779

SN - 2194-9042

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JO - ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences

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Y2 - 13 July 2015 through 15 July 2015

ER -

AGENT- and CLOUD-SUPPORTED GEOSPATIAL SERVICE AGGREGATION for FLOOD RESPONSE

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