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Assessing volunteered geographic information for rapid flood damage estimation

Urheber*innen

Poser,  K.
External Organizations;

/persons/resource/kreib

Kreibich,  Heidi
5.4 Hydrology, 5.0 Earth Surface Processes, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/dransch

Dransch,  Doris
1.5 Geoinformatics, 1.0 Geodesy and Remote Sensing, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

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Zitation

Poser, K., Kreibich, H., Dransch, D. (2009): Assessing volunteered geographic information for rapid flood damage estimation. - In: Haunert, J.-H., Kieler, B., Milde, J. (Eds.), Proceedings of the 12th AGILE International Conference on Geographic Information Science - Advances in GIScience; 2.-5. Juni 2009.


https://gfzpublic.gfz-potsdam.de/pubman/item/item_239400
Zusammenfassung
For disaster management, a broad overview of the situation, resulting impairments and damages is required. For this overview, information from many different sources has to be acquired and integrated. Observations from the affected population can be an important source of information. New Internet technologies facilitate fast and easy data collection from the public. A major obstacle for using this information is its unknown quality. The aim of this research is to develop methods to assess the quality of observations from the affected population for rapid loss estimation after flood events. In a first step, data about flood events and associated losses collected in telephone interviews are assessed for their reliability and fitness for use for flood loss modelling. First results show that water level can be estimated by observers with a similar accuracy as it can be modelled by hydraulic models. Flow velocity, however, is very difficult to estimate and the estimates differ significantly from modelled values. The results of this analysis will be used in a second step to develop an automated procedure for quality assessment of observations from the public to be used in a prototypical implementation of web-based data collection for flood events.