Document Detail


Remote sensing-based neural network mapping of tsunami damage in Aceh, Indonesia.
MedLine Citation:
PMID:  17714164     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
In addition to the loss of human life, the tsunami event of 26 December 2004 caused extensive damage to coastal areas. The scale of the disaster was such that remote sensing may be the only way to determine its effects on the landscape. This paper presents the results of a neural network-based mapping of part of the region of Aceh, Sumatra. Before-and-after satellite imagery, combined with a novel neural network methodology, enabled a characterisation of landscape change. The neural network technique used a threshold of acceptance for identification, in combination with a bootstrapped identification method for identifying problem pixels. Map analysis allowed identification of urban areas that were inaccessible by road, and which aid agencies could therefore only reach by air or sea. The methods used provide a rapid and effective mapping ability and would be a useful tool for aid agencies, insurance underwriters and environmental monitoring.
Authors:
Matthew J Aitkenhead; Parivash Lumsdon; David R Miller
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Disasters     Volume:  31     ISSN:  0361-3666     ISO Abbreviation:  Disasters     Publication Date:  2007 Sep 
Date Detail:
Created Date:  2007-08-23     Completed Date:  2007-12-06     Revised Date:  2008-11-21    
Medline Journal Info:
Nlm Unique ID:  7702072     Medline TA:  Disasters     Country:  England    
Other Details:
Languages:  eng     Pagination:  217-26     Citation Subset:  IM    
Affiliation:
Department of Plant and Soil Science, University of Aberdeen, St Machar Drive, Aberdeen, Scotland. m.aitkenhead@abdn.ac.uk
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MeSH Terms
Descriptor/Qualifier:
Disasters*
Geographic Information Systems / instrumentation*
Geography
Humans
Image Processing, Computer-Assisted / instrumentation*
Indonesia
Neural Networks (Computer)*
Satellite Communications
Systems Integration
Urban Population

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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