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<article language="en">
	<journal>
		<journal_title>Natural Hazards and Earth System Science</journal_title>
		<journal_url>www.nat-hazards-earth-syst-sci.net</journal_url>
		<issn>1561-8633</issn>
		<eissn>1684-9981</eissn>
		<volume_number>8</volume_number>
		<issue_number>3</issue_number>
		<publication_year>2008</publication_year>
	</journal>
	<doi>10.5194/nhess-8-409-2008</doi>
	<article_url>http://www.nat-hazards-earth-syst-sci.net/8/409/2008/</article_url>
	<abstract_html>http://www.nat-hazards-earth-syst-sci.net/8/409/2008/nhess-8-409-2008.html</abstract_html>
	<fulltext_pdf>http://www.nat-hazards-earth-syst-sci.net/8/409/2008/nhess-8-409-2008.pdf</fulltext_pdf>
	<start_page>409</start_page>
	<end_page>420</end_page>
	<publication_date>2008-05-06</publication_date>
	<article_title content_type="html">A conceptual vulnerability and risk framework as outline to identify capabilities of remote sensing</article_title>
	<authors>
		<author numeration="1" affiliations="1,2">
			<name>H. Taubenböck</name>
		</author>
		<author numeration="2" affiliations="1">
			<name>J. Post</name>
		</author>
		<author numeration="3" affiliations="1">
			<name>A. Roth</name>
		</author>
		<author numeration="4" affiliations="1">
			<name>K. Zosseder</name>
		</author>
		<author numeration="5" affiliations="1">
			<name>G. Strunz</name>
		</author>
		<author numeration="6" affiliations="1,2">
			<name>S. Dech</name>
		</author>
	</authors>
	<affiliations>
		<affiliation numeration="1" content_type="html">German Remote Sensing Data Center (DFD), German Aerospace Center (DLR), 82234 Wessling, Germany</affiliation>
		<affiliation numeration="2" content_type="html">Julius-Maximilians-University Würzburg, Geographic Institute, Am Hubland, 97074 Würzburg, Germany</affiliation>
	</affiliations>
	<abstract content_type="html">This study aims at creating a holistic conceptual approach systematizing the
interrelation of (natural) hazards, vulnerability and risk. A general hierarchical
risk meta-framework presents potentially affected components of a given system, such
as its physical, demographic, social, economic, political or ecological spheres,
depending on the particular hazard. Based on this general meta-framework,
measurable indicators are specified for the system &quot;urban area&quot; as an example. This
framework is used as an outline to identify the capabilities of remote sensing to
contribute to the assessment of risk. Various indicators contributing to the outline
utilizing diverse remote sensing data and methods are presented. Examples such as
built-up density, main infrastructure or population distribution identify the
capabilities of remote sensing within the holistic perspective of the framework.
It is shown how indexing enables a multilayer analysis of the complex and
small-scale urban landscape to take different types of spatial indicators into
account to simulate concurrence. The result is an assessment of the spatial
distribution of risks within an urban area in the case of an earthquake and its
secondary threats, using an inductive method. The results show the principal
capabilities of remote sensing to contribute to the identification of physical
and demographic aspects of vulnerability, as well as provide indicators for the
spatial distribution of natural hazards. Aspects of social, economic or political
indicators represent limitations of remote sensing for an assessment complying with the holistic risk framework.</abstract>
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</article>

