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  • Forschungsdaten  (11)
  • Scenario-based multi-risk assessment in the Andes region  (10)
  • EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 EARTHQUAKES 〉 EARTHQUAKE MAGNITUDE/INTENSITY
  • 1
    Publikationsdatum: 2021-10-07
    Beschreibung: Abstract
    Beschreibung: This data publication is composed by two main folders: (1) “Focus_map_construction” and (2) “CVT_models”. The first one contains the individual raster inputs (tsunami inundation and population distribution) that are combined to construct two different focus maps for the cities of Lima and Callao (Peru). The reader can find a more complete description about the focus map concept in Pittore (2015). These raster focus maps are used as inputs to generate variable-resolution CVT (Central Voronoi Tessellation) geocells following the method presented in Pittore et al., (2020). They are vector-based data (ESRI shapefiles) that are stored in the second folder. These resultant CVT-geocells are used by Gomez-Zapata et al., (2021) as spatial aggregation boundaries to represent the residential building portfolio for the cities of Lima and Callao (Peru).
    Schlagwort(e): spatial aggregation areas ; CVT ; Central Voronoi Tessalations ; focus map ; geocells ; raster ; RIESGOS ; Scenario-based multi-risk assessment in the Andes region ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 EARTHQUAKES ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 TSUNAMIS
    Materialart: Dataset , Dataset
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  • 2
    Publikationsdatum: 2021-10-26
    Beschreibung: Abstract
    Beschreibung: This repository is composed of two main folders: (1) “Exposure_fuzzy_scores” and (2) “Inter-scheme_mapping”. The first one contains an ipython notebook with a complete description of two earthquake building schemes: SARA and HAZUS in terms of faceted attributes contained in the GEM V.2.0 taxonomy. Both schemes have already been proposed for exposure modelling at the third administrative division “commune” in Chile in earlier works. They are inputs for the use of a Python script (contained in the second folder) to calculate an inter-scheme compatibility matrix, that uses SARA as the source and HAZUS as the target schemes. These models and data are supplement material to Gomez-Zapata et al. (2021).
    Beschreibung: Other
    Beschreibung: Licence Statement: Data: Creative Commons Attribution 4.0 International License (CC BY 4.0) Code: Apache License, Version 2.0 (January 2004) Copyright © 2021 Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Potsdam, Germany Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at https://www.apache.org/licenses/LICENSE-2.0. Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
    Schlagwort(e): exposure modelling ; building schemes ; compatibility matrix ; faceted taxonomy ; RIESGOS ; Scenario-based multi-risk assessment in the Andes region
    Materialart: Software , Software
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  • 3
    Publikationsdatum: 2022-02-15
    Beschreibung: Abstract
    Beschreibung: This data repository contains the spatial distribution of the direct financial loss computed expected for the residential building stock of Metropolitan Lima (Peru) after the occurrence of six decoupled earthquake and tsunami risk scenarios (Gomez-Zapata et al., 2021a; Harig and Rakowsky, 2021). These risk scenarios were independently calculated making use of the DEUS (Damage Exposure Update Service) available in https://github.com/gfzriesgos/deus. The reader can find documentation about this programme in (Brinckmann et al, 2021) where the input files required by DEUS and outputs are comprehensively described. Besides the spatially distributed hazard intensity measures (IM), other inputs required by DEUS to computed the decoupled risk loss estimates comprise: spatially aggregated building exposure models classified in every hazard-dependent scheme. Each class must be accompanied by their respective fragility functions, and financial consequence model (with loss ratios per involved damage state). The collection of inputs is presented in Gomez-Zapata et al. (2021b). The risk estimates are computed for each spatial aggregation areas of the exposure model. For such a purpose, the initial damage state of the buildings is upgraded from undamaged (D0) to any progressive damage state permissible by the fragility functions. The resultant outputs are spatially explicit .JSON files that use the same spatial aggregation boundaries of the initial building exposure models. An aggregated direct financial loss estimate is reported for each cell after every hazard scenario. It is reported one seismic risk loss distribution outcome for each of the 2000 seismic ground motion fields (GMF) per earthquake magnitude (Gomez-Zapata et al., 2021a). Therefore, 1000 seismic risk estimates from uncorrelated GMF are stored in “Clip_Mwi_uncorrelated” and 1000 seismic risk estimates from spatially cross-correlated GMF (using the model proposed by Markhvida et al. (2018)) are stored in “Clip_ Mwi_correlated”. It is worth noting that the prefix “clip” of these folders refers to the fact that, all of the seismic risk estimates were clipped with respect to the geocells were direct tsunami risk losses were obtained. This spatial compatibility in the losses obtained for similar areas and Mw allowed the construction of the boxplots that are presented in Figure 16 in Gomez-Zapata et al., (2021). The reader should note that folder “All_exposure_models_Clip_8.8_uncorrelated_and_correlated” also contains another folder entitled “SARA_entire_Lima_Mw8.8” where the two realisations (with and without correlation model) selected to produce Figure 10 in Gomez-Zapata et al., (2021) are stored. Moreover, the data to produce Figure 9 (boxplots comparing the variability in the seismic risk loss estimates for this specific Mw 8.8, are presented in the following .CSV file: “Lima_Mw_8.8_direct_finantial_loss_distributions_all_spatial_aggregations_Corr_and_NoCorr.csv”. Naturally, 1000 values emulating the 1000 realisations are the values that compose the variability expressed in that figure. Since that is a preliminary study (preprint version), the reader is invited to track the latest version of the actually published (if so) journal paper and check the actual the definitive numeration of the aforementioned figures.
    Schlagwort(e): tsunami risk ; earthquake risk ; risk scenario ; physical vulnerability ; loss ; deterministic risk ; fragility function ; RIESGOS ; Scenario-based multi-risk assessment in the Andes region ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 EARTHQUAKES ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 TSUNAMIS ; EARTH SCIENCE SERVICES 〉 HAZARDS MANAGEMENT
    Materialart: Dataset , Dataset
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  • 4
    Publikationsdatum: 2022-11-23
    Beschreibung: Abstract
    Beschreibung: The dataset contains a set of structural and non-structural attributes collected using the GFZ RRVS (Remote Rapid Visual Screening) methodology. It is composed by 604 randomly distributed buildings in the urban area of Valparaiso and Viña del Mar (Chile). The survey has been carried out between November and December 2018 using a Remote Rapid Visual Screening system developed by GFZ and employing omnidirectional images from Google StreetView (vintage: December 2018) and footprints from OpenStreetMap (OSM). The buildings were inspected by local structural engineers from the Chilean Research Centre for Integrated Disaster Risk Management (CIGIDEN) while collecting their attribute values in terms of the GEM v.2.0 taxonomy
    Schlagwort(e): taxonomy ; RRVS ; GEM ; risk exposure ; attributes ; survey ; Valparaiso ; RIESGOS ; Scenario-based multi-risk assessment in the Andes region
    Materialart: Dataset , Dataset
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  • 5
    Publikationsdatum: 2022-11-23
    Beschreibung: Abstract
    Beschreibung: This data publication is composed by two main folders: (1) “Top-down_exposure_modelling_Lima” and (2) “Vulnerability_models_Lima/”. The first one contains a complete collection of data models used to represent the residential building portfolio of Lima and Callao (Peru) using a top-down approach (census-based desktop study). Therein, the reader can find a comprehensive description of the procedure of how the exposure models were constructed. This includes python scripts and postprocessed geodatasets to represent these building stock into predefined and separate classes for earthquake and tsunami physical vulnerabilities. The second folder contains sets of fragility functions for these building classes and the assumed economic consequence model. These models are suplement material of a submitted paper (Gomez-Zapata et al., 2021b). Please note it is an unpublished preprint version at the time of writing this document. The reader is strongly advised to look for the definitive version once (if so) it is accepted and published.
    Schlagwort(e): exposure modelling ; physical vulnerability ; consequence model ; fragility function ; earthquake vulnerability ; tsnami vulnerability ; occupancy types ; residential building ; RIESGOS ; Scenario-based multi-risk assessment in the Andes region ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 EARTHQUAKES ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 TSUNAMIS
    Materialart: Dataset , Dataset
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  • 6
    Publikationsdatum: 2023-12-07
    Beschreibung: Abstract
    Beschreibung: 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.
    Beschreibung: Other
    Beschreibung: 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
    Schlagwort(e): 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
    Materialart: Dataset
    Format: 1 Files
    Format: application/octet-stream
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  • 7
    Publikationsdatum: 2024-04-29
    Beschreibung: Abstract
    Beschreibung: This version of Quakeledger (V.1.0) is a Python3 program that can also be used as a WPS (Web Processing Service). It returns the available earthquake events contained within a given local database (so called catalogue) that must be customised beforehand (e.g. historical, expert and/or stochastic events). This is a rewrite from: https://github.com/GFZ-Centre-for-Early-Warning/quakeledger and https://github.com/bpross-52n/quakeledger. In these original codes, an earthquake catalogue had to be initially provided in .CSV format. The main difference with this version is that, this code is refactored and uses a SQLITE database. The user can find the parser code in: “quakeledger/assistance/import_csv_in_sqlite.py”
    Beschreibung: Other
    Beschreibung: License: BSD 3-Clause Copyright © 2021 Early Warning and Impact Assessment Group at Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences Quakeledger is free software: you can redistribute it and/or modify it under the terms of the BSD 3-Clause License. Quakeledger is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the BSD 3-Clause License for more details. You should have received a copy of the BSD 3-Clause License along with this program. If not, see 〈https://opensource.org/licenses〉
    Schlagwort(e): Earthquake catalogue ; provider ; script ; python ; RIESGOS ; Scenario-based multi-risk assessment in the Andes region ; EARTH SCIENCE SERVICES 〉 DATA ANALYSIS AND VISUALIZATION ; EARTH SCIENCE SERVICES 〉 DATA MANAGEMENT/DATA HANDLING ; EARTH SCIENCE SERVICES 〉 WEB SERVICES ; EARTH SCIENCE SERVICES 〉 WEB SERVICES 〉 DATA PROCESSING SERVICES
    Materialart: Software , Software
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  • 8
    Publikationsdatum: 2024-04-29
    Beschreibung: Abstract
    Beschreibung: This folder contains the scripts, input and output files required to calculate the inter-scheme conversion matrices for building types and the implicit damage states of their respective fragility models for two selected vulnerability schemes: one for earthquakes and the other for tsunamis. They were used in previous studies to characterize the residential building stock of Lima. The outcomes generated in this data repository are valuable inputs to then calculate the disaggregated and cumulative damage and losses expected for cascading hazard scenarios.
    Beschreibung: Other
    Beschreibung: In recent decades, the risk to society due to natural hazards has increased globally. To counteract this trend, effective risk management is necessary, for which reliable information is essential. Most existing natural hazard and risk information systems address only single components of a complex risk assessment chain, such as, for instance, focusing on specific hazards or simple loss measures. Complex interactions, such as cascading effects, are typically not considered, as well as many of the underlying sources of uncertainty. This can lead to inadequate or even miss-leading risk management strategies, thus hindering efficient prevention and mitigation measures, and ultimately undermining the resilience of societies. Therefore, experts from different disciplines work together in the joint project RIESGOS 2.0 (Scenario-based multi-risk assessment in the Andes region) and develop innovative scientific methods for the evaluation of complex multi-risk situations with the aim to transfer the results as web services into a demonstrator for a multi-risk information system.
    Schlagwort(e): machine learning ; vulnerability ; multi-hazard ; earthquake fragility ; tsunami fragility ; cumulative damage ; Bayesian approach ; RIESGOS ; Scenario-based multi-risk assessment in the Andes region ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 EARTHQUAKES ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 TSUNAMIS
    Materialart: Dataset , Dataset
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  • 9
    Publikationsdatum: 2024-04-29
    Beschreibung: Abstract
    Beschreibung: This version of Shakyground (V.1.0) comprise several Python3 scripts and returns the median values of spatially-distributed ground motion fields for a selected area and a given synthetic earthquake rupture. These values are simulated by means of a set of GMPEs (Ground Motion Prediction Equations) developed by several experts for specific tectonic areas. The outputs can be provided in community standard formats (.xml). A simple ipython notebook to visualise these results is also included.
    Beschreibung: TechnicalInfo
    Beschreibung: License: BSD 3-Clause Copyright © 2021 Early Warning and Impact Assessment Group at Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences Shakyground is free software: you can redistribute it and/or modify it under the terms of the BSD 3-Clause License. Shakyground is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the BSD 3-Clause License for more details. You should have received a copy of the BSD 3-Clause License along with this program. If not, see 〈https://opensource.org/licenses〉.
    Schlagwort(e): python ; ground motion ; RIESGOS ; Scenario-based multi-risk assessment in the Andes region ; EARTH SCIENCE SERVICES 〉 DATA ANALYSIS AND VISUALIZATION ; EARTH SCIENCE SERVICES 〉 DATA MANAGEMENT/DATA HANDLING
    Materialart: Software , Software
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  • 10
    Publikationsdatum: 2024-04-29
    Beschreibung: Abstract
    Beschreibung: Assetmaster and Modelprop are WPS (Web Processing Services) software components written in Python 3. They are implementing two of the several steps of a multi-hazard scenario-based decentralized risk assessment for the RIESGOS project. The reader can find more details in https://github.com/riesgos. Assetmaster provides as output a structural exposure model defined in terms of risk-oriented building classes (for a reference geographical region) in GeoJSON format. The simple service is based on an underlying exposure model in GeoPackage format (.gpkg). Modelprop provides as output for each defined building class the correspondent fragility function. The python code implementing the service can also be run locally in your computer to assess the physical vulnerability of a given building portfolio computing the direct financial losses associated to hazard and multi-hazard scenarios making use of the DEUS program. It is available in: https://github.com/gfzriesgos/deus/.
    Beschreibung: TechnicalInfo
    Beschreibung: Copyright [2019] Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
    Schlagwort(e): RIESGOS ; Scenario-based multi-risk assessment in the Andes region ; python ; EARTH SCIENCE SERVICES 〉 DATA ANALYSIS AND VISUALIZATION ; EARTH SCIENCE SERVICES 〉 WEB SERVICES
    Materialart: Software , Software
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