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  • 1
    Publication Date: 2021-11-17
    Description: Abstract
    Description: Multi-resolution exposure model for seismic risk assessment in Tajikistan. The model has been developed according to the methodology outlined in Pittore, Haas and Silva (2020) "Multi-resolution Probabilistic Modelling of Residential Exposure and Vulnerability for Seismic Risk Applications", Earthquake Spectra (submitted). The model is aggregated over a Central Voronoidal Tessellation (CVT) composed of geo-cells covering the territory of Tajikistan (provided as a separate file). The model integrates around 1'000 building observations (see related dataset Pittore et al. 2019a). The following specific modelling parameters have been employed: Prior strength=10, 100 Epsilon=0.001 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
    Keywords: Earthquake Risk ; taxonomy ; RRVS ; GEM ; EMCA ; Central Asia ; geological process 〉 seismic activity ; risk 〉 natural risk ; safety 〉 risk assessment 〉 disaster preparedness ; safety 〉 risk assessment 〉 natural risk analysis ; safety 〉 risk assessment 〉 risk exposure
    Type: Dataset , Dataset
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  • 2
    Publication Date: 2021-11-17
    Description: Abstract
    Description: 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
    Keywords: 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
    Type: Dataset , Dataset
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  • 3
    Publication Date: 2021-11-17
    Description: Abstract
    Description: Multi-resolution exposure model for seismic risk assessment in Uzbekistan. 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 geo-cells covering the territory of Uzbekistan (provided as a separate file). The model prior is based on empirical observations in Kyrgyzstan and Tajikistan as well as user-elicited knowledge. 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
    Keywords: 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
    Type: Dataset , Dataset
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  • 4
    Publication Date: 2021-11-17
    Description: Abstract
    Description: Multi-resolution exposure model for seismic risk assessment in Kazakhstan. 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 geo-cells covering the territory of Kazakhstan (provided as a separate file). The model prior is based on user-elicited knowledge. 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
    Keywords: 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
    Type: Dataset , Dataset
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  • 5
    Publication Date: 2021-11-17
    Description: Abstract
    Description: Multi-resolution exposure model for seismic risk assessment in Turkmenistan. 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 geo-cells covering the territory of Turkmenistan (provided as a separate file). The model prior is based on user-elicited knowledge. 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
    Keywords: Earthquake Risk ; taxonomy ; RRVS ; GEM ; EMCA ; Central Asia ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 EARTHQUAKES
    Type: Dataset , Dataset
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  • 6
    Publication Date: 2021-11-17
    Description: Abstract
    Description: The datasets in this collection include input and output components of the seismic exposure model developed within the framework of the Earthquake Model Central Asia and used for seismic risk assessment. In particular the collection includes: - A dataset of around 7’000 individual building observations in Kyrgyzstan and Tajikistan collected using the Remote Rapid Visual Survey (RRVS) methodology developed at GFZ, along with the class schema used to map the individual taxonomic observations into vulnerability-related building classes. These are used to develop suitable prior distribution and to constrain locally the resulting exposure models - The seismic exposure models for the following central Asian countries: Kazakhstan , Kyrgyz Republic, Tajikistan, Turkmenistan and Uzbekistan, aggregated over a set of heterogeneous tessellations (geo-cells) The methodology employed for the development of the exposure models is described in Pittore, M., Haas, M., and Silva, V. (2020) “Multi-resolution Probabilistic Modelling of Residential Exposure and Vulnerability for Seismic Risk Applications”, Earthquake Spectra. Two versions of the models obtained with two different parameter settings are included. The models are provided in .csv and in .xml (nrml 0.5) format, for compatiliby with the OpenQuake hazard and risk assessment engine.
    Keywords: 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
    Type: Dataset , Dataset
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  • 7
    Publication Date: 2021-11-17
    Description: Abstract
    Description: The dataset contains a set of structural and non-structural attributes collected using the GFZ RRVS methodology in Kyrgyzstan and Tajikistan, within the framework of the projects EMCA (Earthquake Model Central Asia), funded by GEM, and "Assessing Seismic Risk in the Kyrgyz Republic", funded by the World Bank. The survey has been carried out between 2012 and 2016 using a Remote Rapid Visual Screening system developed by GFZ and employing omnidirectional images and footprints from OpenStreetMap. The attributes are encoded according to the GEM taxonomy v2.0 (see https://taxonomy.openquake.org). The following attributes are defined (not all are observable in the RRVS survey): code, description: lon, longitude in fraction of degrees lat, latitude in fraction of degrees object_id, unique id of the building surveyed MAT_TYPE,Material Type MAT_TECH,Material Technology MAT_PROP,Material Property LLRS,Type of Lateral Load-Resisting System LLRS_DUCT,System Ductility HEIGHT,Height YR_BUILT,Date of Construction or Retrofit OCCUPY,Building Occupancy Class - General OCCUPY_DT,Building Occupancy Class - Detail POSITION,Building Position within a Block PLAN_SHAPE,Shape of the Building Plan STR_IRREG,Regular or Irregular STR_IRREG_DT,Plan Irregularity or Vertical Irregularity STR_IRREG_TYPE,Type of Irregularity NONSTRCEXW,Exterior walls ROOF_SHAPE,Roof Shape ROOFCOVMAT,Roof Covering ROOFSYSMAT,Roof System Material ROOFSYSTYP,Roof System Type ROOF_CONN,Roof Connections FLOOR_MAT,Floor Material FLOOR_TYPE,Floor System Type FLOOR_CONN,Floor Connections For each building an EMCA vulnerability class has been assigned following the fuzzy scoring methodology described in Pittore et al., 2018. The related class definition schema (as a .json document) is included in the data package.
    Keywords: 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
    Type: Dataset , Dataset
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  • 8
    Publication Date: 2023-12-07
    Description: Abstract
    Description: Version History11 Sep 2019: Release of Version 1.1 with the following changes: (1) new licence: CC BY SA 4.0, modification of the title: removal of file name and version); (2) addition of ORIDs when available; (3) actualisation of affiliations for some authors The metadata of the first version 1.0 is available in the download folder.. Data and file names remain unchanged.Area Source model for Central AsiaThe area sources for Central Asia within the EMCA model are defined by mainly considering the pattern of crustal seismicity down to 50 km depth. Although tectonic and geological information, such as the position and strike distribution of known faults, have also been taken into account when available. Large area sources (see, for example source_id 1, 2, 5, 45 and 52, source ids are identified by parameter “source_id” in the related shapefile) are defined where the seismicity is scarce and there are no tectonic or geological features that would justify a further subdivision. Smaller area sources (e.g., source_id values 36 and 53) have been designed where the seismicity can be assigned to known fault zones.In order to obtain a robust estimation of the necessary parameters for PSHA derived by the statistical analysis of the seismicity, due to the scarcity of data in some of the areas covered by the model, super zones are introduced. These super zones are defined by combining area sources based on similarities in their tectonic regime, and taking into account local expert’s judgments. The super zones are used to estimate: (1) the completeness time of the earthquake catalogue, (2) the depth distribution of seismicity, (3) the tectonic regime through focal mechanisms analysis, (4) the maximum magnitude and (5) the b values via the GR relationship.The earthquake catalogue for focal mechanism is extracted from the Harvard Global Centroid Moment Tensor Catalog (Ekström and Nettles, 2013). For the focal mechanism classification, the Boore et al. (1997) convention is used. This means that an event is considered to be strike-slip if the absolute value of the rake angle is 〈=30 or 〉=150 degrees, normal if the rake angle is 〈-30 or 〉-150 and reverse (thrust) if the rake angle is 〉30 or 〈150 degrees. The distribution of source mechanisms and their weights are estimated for the super zones.For area sources, the maximum magnitude is usually taken from the historical seismicity, but due to some uncertainties in the magnitudes of the largest events, the opinions of the local experts are also included in assigning the maximum magnitude to each super zone. Super zones 2 and 3, which belongs to stable regions, are each assigned a maximum magnitude of 6, after Mooney et al. (2012), which concludes after analyses and observation of modern datasets that at least an event of magnitude 6 can occur anywhere in the world. For hazard calculations, each area source is assigned the maximum magnitude of their respective super zone.For processing the GR parameters (a and b values) for the area sources, the completeness analysis results estimated for the super zones are assigned to the respective smaller area sources. If the individual area source has at least 20 events, the GR parameters are then estimated for the area source. Otherwise, the b value is adopted from the respective super zone to which the smaller area source belongs, and the a value is estimated based on the Weichert (1980) method. This ensures the stability in the b value as well as the variation of activity rate for different sources.The hypocentral depth distribution is estimated from the seismicity inside each super zone. The depth distribution is considered for maximum up to three values. Based on the number of events, the weights are assigned to each distribution. These depth distributions, along with corresponding weights, are further assigned to the area sources within the same super zones.
    Description: Other
    Description: Distribution file: "EMCA_seismozonesv1.0_shp.zip"Version: v1.0Release date: 2015-07-30Format: ESRI ShapefileGeometry type: polygonsNumber of features: 63Spatial Reference System: +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defsDistribution file: "EMCA_seismozonesv1.0_nrml.zip"Version: v1.0Release date: 2015-07-30Format: NRML (XML) Format compatible with the GEM OpenQuake platform (http://www.globalquakemodel.org/openquake/about/platform/)Feature attributes:src_id : Id of the seismic sourcesrc_name : Name of the seismic sourcetect_reg: Tectonic regime of the seismic sourceupp_seismo : Upper level of the the seismogenic depth (km)low_seismo : Lower level of the seismogenic depth (km)mag_scal_r: Magnitude scaling relationshiprup_asp_ra: Rupture aspect ratiomfd_type : Magnitude frequency distribution typemin_mag: Minimum magnitude of the magnitude frequency relationshipmax_mag: Maximum magnitude of the magnitude frequency relationshipa_value: a value of the magnitude frequency relationshipb_balue : b value of the magnitude frequency relationshipnum_npd: number of nodal plane distributionweight_1 : weight of 1st nodal plane distributionstrike_1: Strike of the seismic source (degrees)rake_1: rake of the seismic source (degrees)dip_1: dip of the seismic source (degrees)num_hdd: number of hypocentral depth distributionhdd_d_1: Depth of 1st hypocentral depth distribution (km)hdd_w_1: Weight of 1st hypocentral depth distribution
    Keywords: seismogenic sources ; central asia ; EMCA ; GEM ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 EARTHQUAKES 〉 EARTHQUAKE OCCURRENCES ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 EARTHQUAKES 〉 EARTHQUAKE MAGNITUDE/INTENSITY ; EARTH SCIENCE SERVICES 〉 DATA MANAGEMENT/DATA HANDLING 〉 CATALOGING
    Type: Dataset
    Format: 1 Files
    Format: application/octet-stream
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