2010
DOI: 10.1007/s12145-010-0075-y
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Tailoring spatial reference in early warning systems to administrative units

Abstract: This paper presents a novel approach for early warning systems to transform the spatial reference of dispersion models into addressable administrative units enabling an intelligible warning message reception and spatial awareness. The spatial reference along the entire information chain from sensor measurements via dispersion model to warning dissemination is discussed. Core concept behind this approach is the application of the EgenhoferModel for analysis of binary topologic relations. It is used to identify … Show more

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Cited by 5 publications
(3 citation statements)
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“…A standardised approach for warning dissemination has been proposed by Lendholt (2011). Effective targeted warning dissemination depends on a detailed description of the information needs of potential target groups.…”
Section: Warning Dissemination and Downstream Information Flowmentioning
confidence: 99%
“…A standardised approach for warning dissemination has been proposed by Lendholt (2011). Effective targeted warning dissemination depends on a detailed description of the information needs of potential target groups.…”
Section: Warning Dissemination and Downstream Information Flowmentioning
confidence: 99%
“…In contrast, addressing areas/regions with geocodes for territorial subdivisions, such as federal states and counties, provides a spatial reference that is directly usable for all message recipients. The mapping of spatial references to administrative units in EWS is examined in detail in [31]. Hierarchical administrative territories are structured according to historic cultural and ethnic landscapes or logistics districts that are commonly known and widely used.…”
Section: Spatial Reference In Early Warning Mes-sagesmentioning
confidence: 99%
“…This triggers a WPS that maps forecasts to territorial units provided by Spatial Data Infrastructure (SDI). See [31] for details. The second page (see Fig.…”
Section: Tsunami Early Warning Extensionmentioning
confidence: 99%