Share Email Print

Proceedings Paper

Derivation of population distribution for vulnerability assessment in flood-prone German cities using multisensoral remote sensing data
Author(s): Michael Wurm; Hannes Taubenböck; Susanne Krings; Jörn Birkmann; Achim Roth; Stefan Dech
Format Member Price Non-Member Price
PDF $17.00 $21.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Against the background of massive urban development, area-wide and up-to-date spatial information is in demand. However, for many reasons this detailed information on the entire urban area is often not available or just not valid anymore. In the event of a natural hazard - e.g. a river flood - it is a crucial piece of information for relief units to have knowledge about the quantity and the distribution of the affected population. In this paper we demonstrate the abilities of remotely sensed data towards vulnerability assessment or disaster management in case of such an event. By means of very high resolution optical satellite imagery and surface information derived by airborne laser scanning, we generate a precise, three-dimensional representation of the landcover and the urban morphology. An automatic, object-oriented approach detects single buildings and derives morphological information - e.g. building size, height and shape - for a further classification of each building into various building types. Subsequently, a top-down approach is applied to distribute the total population of the city or the district on each individual building. In combination with information of potentially affected areas, the methodology is applied on two German cities to estimate potentially affected population with a high level of accuracy.

Paper Details

Date Published: 7 October 2009
PDF: 12 pages
Proc. SPIE 7478, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology IX, 74781K (7 October 2009); doi: 10.1117/12.830318
Show Author Affiliations
Michael Wurm, German Aerospace Ctr. (Germany)
Julius-Maximilians-Univ Würzburg (Germany)
Hannes Taubenböck, German Aerospace Ctr. (Germany)
Julius-Maximilians-Univ Würzburg (Germany)
Susanne Krings, United Nations Univ. (Germany)
Jörn Birkmann, United Nations Univ. (Germany)
Achim Roth, German Aerospace Ctr. (Germany)
Stefan Dech, German Aerospace Ctr. (Germany)
Julius-Maximilians-Univ Würzburg (Germany)

Published in SPIE Proceedings Vol. 7478:
Remote Sensing for Environmental Monitoring, GIS Applications, and Geology IX
Ulrich Michel; Daniel L. Civco, Editor(s)

© SPIE. Terms of Use
Back to Top