Khomarudin, Rokhis M.

Ludwig, Ralf

Post, Joachim

Strunz, Günter

Zosseder, Kai

English

Institute of Transport Research:Publications

Geophysical Research Abstracts,Vol. 11, EGU2009-10459, 2009EGU General Assembly 2009© Author(s) 2009Derivation of Population Distribution Using Remote Sensing andStatistical Data as an Input for Tsunami Risk AssessmentR. Khomarudin (1,2,3), G. Strunz (1), J. Post (1), K. Zosseder (1), and R. Ludwig (3)(1) German Aerospace Center (DLR), Oberpfaffenhofen, Germany, (2) United Nation University Institute for Environmentand Human Security (UNU-EHS), Bonn, Germany, (3) Ludwig Maximillian University (LMU), Munich, GermanyInformation about people distribution is a crucial component in disaster risk management. Every disaster suchas flood, drought, tsunami, volcanic eruption, storm, earthquake etc. implies threats to people with respect toloss of live, injury, and suffer. The number of people affected during 1991 – 2005 is approximately 3.5 billionpeople (UN ESCAP note), and that means more than 50% of people on the world are affected by disasters.Therefore, the information on people distribution in the disaster or hazard zone is important in order to mitigatethe impact of natural disasters. Especially for tsunami, this information will help the government to better managethe evacuation of people and to estimate the number of people affected if there is tsunami event in their area.Normally, the available information on population distribution is based statistical data related to administrativeboundaries, e.g. village, municipal, district, province, or national level.This research focuses on the improvement of the spatial resolution of data on the people distribution covering thearea along the west coast Sumatera, South Coast of Java, and Bali. The results are used as an input for tsunami riskassessment in the framework of the GITEWS project. A combination of the number of people at village level withland use maps is under¬taken in this research. GIS and remote sensing techniques are used to improve the spatialdetail of statistical data on people distribution. The model is based on an analysis of people activities in a certainland use. To assign appropriate weighting factors, census data and potential of village (PODES) data are used.The results of this research are detailed people distribution maps (day and night time) for the Coast of Sumatera,South Coast of Java, and Coastal of Bali. The spatial improvement can be shown. Moreover, besides thespatial improvement, the results also provide information on the distribution during day and night time. To esti-mate the accuracy of this approach, sensitivity analyses have been performed, which show the quality of the results.Keywords: spatial improvement, people distribution, census, land use, risk assessment

Derivation of Population Distribution Using Remote Sensing and Statistical Data as an Input for Tsunami Risk Assessment

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