AGENT- AND CLOUD-SUPPORTED GEOSPATIAL SERVICE AGGREGATION FOR FLOOD RESPONSE

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 (SOA)-based f...

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Main Authors: X. Tan, L. Di, M. Deng, A. Chen, Z. Sun, C. Huang, Y. Shao, X. Ye
Format: Article
Language:English
Published: Copernicus Publications 2015-07-01
Series:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-4-W2/13/2015/isprsannals-II-4-W2-13-2015.pdf
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author X. Tan
L. Di
M. Deng
A. Chen
Z. Sun
C. Huang
Y. Shao
X. Ye
author_facet X. Tan
L. Di
M. Deng
A. Chen
Z. Sun
C. Huang
Y. Shao
X. Ye
author_sort X. Tan
collection DOAJ
description 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 (SOA)-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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spelling doaj.art-b5ed65a6e8b94428886ddf1ab875f6652022-12-21T20:47:48ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502015-07-01II-4/W2131810.5194/isprsannals-II-4-W2-13-2015AGENT- AND CLOUD-SUPPORTED GEOSPATIAL SERVICE AGGREGATION FOR FLOOD RESPONSEX. Tan0L. Di1M. Deng2A. Chen3Z. Sun4C. Huang5Y. Shao6X. Ye7International School of Software, Wuhan University, 430079, Wuhan, ChinaDepartment of Geography and GeoInformation Science, George Mason University, Fairfax, VA 22030, USADepartment of Geography and GeoInformation Science, George Mason University, Fairfax, VA 22030, USANOAA/NGS, 1315 East-West Highway, Silver Spring, MD 20910-3282, Department of Geography, Kent State University, Kent, OH, 44242, USADepartment of Geography and GeoInformation Science, George Mason University, Fairfax, VA 22030, USAInternational School of Software, Wuhan University, 430079, Wuhan, ChinaInternational School of Software, Wuhan University, 430079, Wuhan, ChinaNOAA/NGS, 1315 East-West Highway, Silver Spring, MD 20910-3282, Department of Geography, Kent State University, Kent, OH, 44242, USAFlooding 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 (SOA)-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.http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-4-W2/13/2015/isprsannals-II-4-W2-13-2015.pdf
spellingShingle X. Tan
L. Di
M. Deng
A. Chen
Z. Sun
C. Huang
Y. Shao
X. Ye
AGENT- AND CLOUD-SUPPORTED GEOSPATIAL SERVICE AGGREGATION FOR FLOOD RESPONSE
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title AGENT- AND CLOUD-SUPPORTED GEOSPATIAL SERVICE AGGREGATION FOR FLOOD RESPONSE
title_full AGENT- AND CLOUD-SUPPORTED GEOSPATIAL SERVICE AGGREGATION FOR FLOOD RESPONSE
title_fullStr AGENT- AND CLOUD-SUPPORTED GEOSPATIAL SERVICE AGGREGATION FOR FLOOD RESPONSE
title_full_unstemmed AGENT- AND CLOUD-SUPPORTED GEOSPATIAL SERVICE AGGREGATION FOR FLOOD RESPONSE
title_short AGENT- AND CLOUD-SUPPORTED GEOSPATIAL SERVICE AGGREGATION FOR FLOOD RESPONSE
title_sort agent and cloud supported geospatial service aggregation for flood response
url http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-4-W2/13/2015/isprsannals-II-4-W2-13-2015.pdf
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