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false4DOIDB.GFZ 10.5880/GFZ.2.6.2019.003 Pittore, Massimiliano Massimiliano Pittore 0000-0003-4940-3444 GFZ German Research Centre for Geosciences, Potsdam, Germany Wieland, Marc Marc Wieland 0000-0002-1155-723X GFZ German Research Centre for Geosciences, Potsdam, Germany Haas, Michael Michael Haas GFZ German Research Centre for Geosciences, Potsdam, Germany Silva, Vitor Vitor Silva GEM Foundation, Pavia, Italy GFZ Data Services 2019 Earthquake Risk taxonomy RRVS GEM EMCA Central Asia EARTH SCIENCE > HUMAN DIMENSIONS > NATURAL HAZARDS > EARTHQUAKES geological process > seismic activity risk > natural risk safety > risk assessment > disaster preparedness safety > risk assessment > natural risk analysis safety > risk assessment > risk exposure Pittore, Massimiliano Massimiliano Pittore 0000-0003-4940-3444 GFZ German Research Centre for Geosciences, Potsdam, Germany Pittore, Massimiliano Massimiliano Pittore 0000-0003-4940-3444 GFZ German Research Centre for Geosciences, Potsdam, Germany Pittore, Massimiliano Massimiliano Pittore 0000-0003-4940-3444 GFZ German Research Centre for Geosciences, Potsdam, Germany Wieland, Marc Marc Wieland 0000-0002-1155-723X GFZ German Research Centre for Geosciences, Potsdam, Germany Wieland, Marc Marc Wieland 0000-0002-1155-723X GFZ German Research Centre for Geosciences, Potsdam, Germany Haas, Michael Michael Haas GFZ German Research Centre for Geosciences, Potsdam, Germany Haas, Michael Michael Haas GFZ German Research Centre for Geosciences, Potsdam, Germany Silva, Vitor Vitor Silva GEM Foundation, Pavia, Italy Pittore Massimiliano GFZ German Research Centre for Geosciences, Potsdam, Germany 2019-02-05 2012-01-01/2016-10-01 Dataset 10.1177/8755293020951582 10.5880/GFZ.2.6.2019.006 1.0 CC BY 4.0 Multi-resolution exposure model for seismic risk assessment in the Kyrgyz Republic. The model has been developed according to the methodology outlined in Pittore, Haas and Silva (2019) "Multi-resolution Probabilistic Modelling of Residential Exposure and Vulnerability for Seismic Risk Applications", Earthquake Spectra. The model is aggregated over a Central Voronoidal Tessellation (CVT) composed of 1'175 geo-cells covering the territory of the Kyrgyz Republic. The model integrates around 6'000 building observations (see related dataset Pittore et al. 2019).

The following specific modelling parameters have been employed: Two exposure models are provided, with prior strength pw 10 and 100. Both models have epsilon=0.001 (see publication indicated in the metadata for details on the modelling process). For each geo-cell the model includes the expected number of buildings , total occupancy and replacement cost for each of the 15 building types defined in the EMCA taxonomy (see Pittore et al, 2019b), plus the buildings that are belonging to other, non specified typologies (described by building type OTH). Each geo-cell also includes the area of the geo-cell itself in squared km.

The data package contains three components:
1) exposure models in .csv
2) exposure models in .xml - the file is encoded in NRML 0.5 format and is compatible with the GEM openquake processing engine
3) shapefile of the tessellation that aggregates the exposure model. The field "cell_id" is the linkage with the exposure models
Time span of the overall RRVS surveys 69.4309 79.9339 39.126 42.9526