E3S Web Conf.
Volume 29, 2018XVIIth Conference of PhD Students and Young Scientists
|Number of page(s)||13|
|Published online||31 January 2018|
Using raster and vector data to identify objects for classify in flood risk. A case study: Raciborz
University of Warsaw, PolandFaculty of Geography and Regional Studies, 26/28 Krakowskie Przedmieście St., 00-927 Warsaw, Poland
2 Space Research Centre of Polish Academy of Sciences, 18A Bartycka St., 00-716 Warsaw, Poland
* Corresponding author: email@example.com
The severe flood of 1997, which seriously affected Polish, Czech and German territories, gave impetus to research into the management of flood-prone areas. The material losses caused by the “Flood of the Millennium” totalled billions of Polish zloty. The extent of the disaster and of infrastructure repair costs changed the attitude of many branches of the economy, and of science. This is the direct result of consideration of the introduction of changes into spatial management and crisis management. At the same time, it focused the interest of many who were trained in analysing the vulnerability of land-use features to natural disasters such as floods. Research into the spatial distribution of geographic environmental features susceptible to flood in the Odra valley was conducted at the Faculty of Geography and Regional Studies of the University of Warsaw using Geographic Information Systems (GIS).
This study seeks to examine the possibility of adapting vector and raster data and using them for land-use classification in the context of risk of flood and inundation damage. The analysed area of the city and surrounding area of Raciborz, on the upper Odra River, is a case study for identifying objects and lands susceptible to natural hazards based on publicly available satellite databases of the highest resolution, which is a very important factor in the quality of further risk analyses for applied use.
The objective of the research was to create a 10×10-m-pixel raster network using raster data made available by ESA (Copernicus Land Monitoring Service) and vector data from Open Street Map.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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