EHRE data extract for Ahrweiler

Extract from the European High-Resolution Exposure (EHRE) model (Nievas et al., 2023) for the district of Ahrweiler, Germany. While EHRE consists of a combination of building footprints and aggregated numbers of buildings in high-resolution tiles, this extract contains only the files associated with the individual building footprints, grouped per occupancy case: residential, commercial and industrial. The building footprints stem from the processing of OpenStreetMap by means of OpenBuildingMap (OBM). All CSV files in this extract follow the OpenQuake exposure format. All details on the EHRE model can be found in: Nievas, C.I., Kriegerowski, M., Delattre, F., Garcia Ospina, N., Prehn, K., Cotton, F. (2023): The European High-Resolution Exposure (EHRE) Model, Scientific TechnicalReport STR; 23/05, Potsdam: GFZ German Research Centre for Geosciences. https://doi.org/10.48440/gfz.b103-23055 The EHRE software is available from: https://git.gfz-potsdam.de/ehre. Filename Description Content deu_297_commercial_obm.csv EHRE commercial buildings by individual OBM footprints Location (lon, lat), structural classes (with probabilities), replacement costs, occupancy deu_XXX_residential_obm.csv 74 tables with EHRE residential buildings by individual OBM footprints Location (lon, lat), structural classes (with probabilities), replacement costs, occupancy deu_industrial_filler_XXX_ industrial_obm.csv 2 tables with EHRE industrial buildings by individual OBM footprints Location (lon, lat), structural classes (with probabilities), replacement costs, occupancy License & Disclaimer The data are provided with a CC BY SA 4.0 license. Please refer to the terms of the license text for further information on the conditions of use. The data are distributed without any warranty and without the implied warranty of fitness for a particular purpose. The creators of the data assume no liability for its use in application by second or third parties, or for further public dissemination of the data in a way that allows for parameters to be attributed to individual buildings. The creators strongly advise against dissemination of derivative data that may provide information that can be uniquely and unambiguously attributed to individual buildings as well. Alternative strategies, such as aggregation of results at a geographical scale that prevents the identification of individual buildings, are instead recommended.