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A Task-oriented Disaster Information Correlation Method : Volume Ii-4/W2, Issue 1 (10/07/2015)

By Linyao, Q.

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Book Id: WPLBN0004013996
Format Type: PDF Article :
File Size: Pages 8
Reproduction Date: 2015

Title: A Task-oriented Disaster Information Correlation Method : Volume Ii-4/W2, Issue 1 (10/07/2015)  
Author: Linyao, Q.
Volume: Vol. II-4/W2, Issue 1
Language: English
Subject: Science, Isprs, Annals
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Qing, Z., Zhiqiang, D., & Linyao, Q. (2015). A Task-oriented Disaster Information Correlation Method : Volume Ii-4/W2, Issue 1 (10/07/2015). Retrieved from

Description: State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 430079 Wuhan, China. With the rapid development of sensor networks and Earth observation technology, a large quantity of disaster-related data is available, such as remotely sensed data, historic data, case data, simulated data, and disaster products. However, the efficiency of current data management and service systems has become increasingly difficult due to the task variety and heterogeneous data. For emergency task-oriented applications, the data searches primarily rely on artificial experience based on simple metadata indices, the high time consumption and low accuracy of which cannot satisfy the speed and veracity requirements for disaster products. In this paper, a task-oriented correlation method is proposed for efficient disaster data management and intelligent service with the objectives of 1) putting forward disaster task ontology and data ontology to unify the different semantics of multi-source information, 2) identifying the semantic mapping from emergency tasks to multiple data sources on the basis of uniform description in 1), and 3) linking task-related data automatically and calculating the correlation between each data set and a certain task. The method goes beyond traditional static management of disaster data and establishes a basis for intelligent retrieval and active dissemination of disaster information. The case study presented in this paper illustrates the use of the method on an example flood emergency relief task.



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