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Remote Sens. 2015, 7(8), 9610-9631; doi:10.3390/rs70809610

A Sharable and Efficient Metadata Model for Heterogeneous Earth Observation Data Retrieval in Multi-Scale Flood Mapping

1
State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Luoyu Road 129, Wuhan 430079, China
2
Collaborative Innovation Center of Geospatial Technology, Wuhan University, Luoyu Road 129, Wuhan 430079, China
*
Author to whom correspondence should be addressed.
Academic Editors: Guy J.-P. Schumann and Prasad S. Thenkabail
Received: 14 May 2015 / Revised: 20 July 2015 / Accepted: 21 July 2015 / Published: 29 July 2015
(This article belongs to the Special Issue Remote Sensing in Flood Monitoring and Management)
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Abstract

Remote sensing plays an important role in flood mapping and is helping advance flood monitoring and management. Multi-scale flood mapping is necessary for dividing floods into several stages for comprehensive management. However, existing data systems are typically heterogeneous owing to the use of different access protocols and archiving metadata models. In this paper, we proposed a sharable and efficient metadata model (APEOPM) for constructing an Earth observation (EO) data system to retrieve remote sensing data for flood mapping. The proposed model contains two sub-models, an access protocol model and an enhanced encoding model. The access protocol model helps unify heterogeneous access protocols and can achieve intelligent access via a semantic enhancement method. The enhanced encoding model helps unify a heterogeneous archiving metadata model. Wuhan city, one of the most important cities in the Yangtze River Economic Belt in China, is selected as a study area for testing the retrieval of heterogeneous EO data and flood mapping. The past torrential rain period from 25 March 2015 to 10 April 2015 is chosen as the temporal range in this study. To aid in comprehensive management, mapping is conducted at different spatial and temporal scales. In addition, the efficiency of data retrieval is analyzed, and validation between the flood maps and actual precipitation was conducted. The results show that the flood map coincided with the actual precipitation. View Full-Text
Keywords: multi-scale flood mapping; system of systems (SoS); sensor observation service (SOS); one-stop access; semantic enhancement; Wuhan city; hundreds of lakes multi-scale flood mapping; system of systems (SoS); sensor observation service (SOS); one-stop access; semantic enhancement; Wuhan city; hundreds of lakes
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Chen, N.; Zhou, L.; Chen, Z. A Sharable and Efficient Metadata Model for Heterogeneous Earth Observation Data Retrieval in Multi-Scale Flood Mapping. Remote Sens. 2015, 7, 9610-9631.

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