EGIFF - Developing advanced GI methods for early warning in mass movement scenarios

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in Buch/Sammelband/GutachtenBeigetragen

Beitragende

  • Martin Breunig - , Universität Osnabrück (Autor:in)
  • Björn Schillberg - , Universität Osnabrück (Autor:in)
  • Paul Vincent Kuper - , Universität Osnabrück (Autor:in)
  • Markus Jahn - , Universität Osnabrück (Autor:in)
  • Wolfgang Reinhardt - , Universität der Bundeswehr München (Autor:in)
  • Eva Nuhn - , Universität der Bundeswehr München (Autor:in)
  • Stephan Mäs - , Professur für Geoinformatik (Autor:in)
  • Conrad Boley - , Universität der Bundeswehr München (Autor:in)
  • Franz-Xaver Trauner - , Universität der Bundeswehr München (Autor:in)
  • Joachim Wiesel - , Universität Karlsruhe (Autor:in)
  • Daniela Richter - , Universität Karlsruhe (Autor:in)
  • Andreas Abecker - , Universität Karlsruhe (Autor:in)
  • Dominik Gallus - , Universität Karlsruhe (Autor:in)
  • Wassilios Kazakos - , disy Informationssysteme GmbH (Autor:in)
  • Andreas Bartels - , disy Informationssysteme GmbH (Autor:in)

Abstract

There is a strong demand for analyzing mass movement scenarios and developing early warning systems to save lives and properties. However, hitherto the preparation of information and the analysis of hazards are still particularly critical links in the early warning chain. The responsible decision makers are usually confronted with huge amounts of structured and unstructured data. Thus the question arises, how they may be provided with a reliable and manageable amount of information to create the warning decision and to take preventive measures. In this article, objectives, concepts and results are presented, examining methods of an information system for the early recognition of geological hazards in mass movement scenarios. The simulation of landslides is executed on the basis of geotechnical, mechanically founded models. By coupling the simulation with GIS and advanced geo-databases, a better understanding of the corresponding geo-scientific processes is achieved. Additionally, the analysis of structured and unstructured data executed by statistical and linguistic methods, respectively, improves risk assessment and supports the early warning decision. Finally, a service-based 3D/4D geo-database manages selected data of a mass movement scenario.

Details

OriginalspracheEnglisch
TitelGeotechnologien Science Report
Seiten49-72
Seitenumfang23
Band13
PublikationsstatusVeröffentlicht - 2009
Peer-Review-StatusNein

Externe IDs

ORCID /0000-0002-9016-1996/work/157769339