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  • 1
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    Spatial representation of direct loss estimates on the residential building stock of Lima (Peru) from decoupled earthquake and tsunami scenarios on variable resolutions exposure models (2021)
    GFZ Data Services
    Details
    Publication Date: 2022-02-15
    Description: Abstract
    Description: 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.
    Keywords: 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
    Type: Dataset , Dataset
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    DATA GFZ
  • 2
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    Residential building exposure and physical vulnerability models for ground-shaking and tsunami risk in Lima and Callao (Peru) (2021)
    GFZ Data Services
    Details
    Publication Date: 2022-11-23
    Description: Abstract
    Description: 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.
    Keywords: 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
    Type: Dataset , Dataset
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    DATA GFZ
  • 3
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    TERENO (Northeast), Soil moisture station Sassen BF1, Germany (2018)
    GFZ Data Services
    Details
    Publication Date: 2023-03-17
    Description: Abstract
    Description: The Sassen BF1 soil moisture station is part of an agrometeorological test site and aims at supplying environmental data for algorithm development in remote sensing and environmental modelling, with a focus on soil moisture and evapotranspiration.The site is intensively used for practical tests of remote sensing data integration in agricultural land management practices. First measurement infrastructure was installed by DLR in 1999 and instrumentation was intensified in 2011 and later as the site became part of the TERENO-NE observatory. The soil moisture station station Sassen BF1 was installed in 2012. It is located next to a pylon on a crest of an undulating field. The station is equipped with sensor for measuring the following variables: ScemeSpadeSoilMoisture_Spade_2_Temperature, ScemeSpadeSoilMoisture_Spade_6_Temperature, ScemeSpadeSoilMoisture_Spade_1, ScemeSpadeSoilMoisture_Spade_2, ScemeSpadeSoilMoisture_Spade_3, ScemeSpadeSoilMoisture_Spade_4, ScemeSpadeSoilMoisture_Spade_5 and ScemeSpadeSoilMoisture_Spade_6. The current version of this dataset is 1.5. This version includes two additional years of data (from-year to-year)and a revised version of the data flags. New authors were added for this new version: Alice Künzel (GFZ Potsdam), Christian Budach (GFZ Potsdam), Nils Brinckmann (GFZ Potsdam), Max Wegener (DLR Neustrelitz) and Klemens Schmidt (DLR Neustrelitz).A detailed overview on all changes is provided in the station description file. Older versions are available in the 'previous_versions' subfolder via the Data Download link. A first version of this data was provided under http://doi.org/ containing the measured data only. The dataset is also available through the TERENO Data Discovery Portal. The datafile will be extended once per year as more data is acquired at the stations and the metadatafile will be updated. New columns for new variables will be added as necessary. In case of changes in data processing, which will result in changes of historical data, an new Version of this dataset will be published using a new doi. New data will be added after a delay of several months to allow manual interference with the quality control process. During October 2020 a Bug in the published data was detected and a new version of the datasets was released from beginning until mid 2020. Data processing was done using DMRP version: 1.8.4. Metadataprocessing was done using DMETA version: 1.2.0.
    Description: Other
    Description: The DEMMIN test site is located within the central monitoring sites of the TERENO Northeastern German Lowland Observatory. It covers 900 km² and exhibits mostly glacial formed lowlands with terminal moraines in the southern part, containing the highest elevation of 83m a.s.l. The region between the rivers Tollense and Peene consists of flat ground moraines, whereas undulation ground moraines determine the landscape character north of the river Peene. The lowest elevation is located near the town Loitz with 0.5m a.s.l. The region is characterized by intense agricultural use and the three rivers Tollense and Trebel which confluence into the Peene River at the Hanseatic city Demmin. The present climate is characterized by a long-term (19812010) mean temperature of 8.7 °C and mean precipitation of 584 mm/year, measured at the Teterow weather station by Deutscher Wetterdienst (DWD). The Northeastern German Lowland Observatory is situated in a region shaped by recurring glacial and periglacial processes since at least half a million years. Within this period, three major glaciations covered the entire region, the last time this happened approximately 25 15 k ago (Weichselian glaciation).Since that time, a young morainic landscape developed characterized by many lakes and river systems that are connected to the shallow ground water table. The test site is instrumented with more than 40 environmental measurement stations (DLR, GFZ). Additionally, 63 soil moisture stations were installed by GFZ, a lysimeter-hexagon (DLR, FZJ) near to the village Rustow and is part of the SOILCan project. A crane completes the measurement technique currently available in the test site installed by GFZ/DLR in 2011. Data is automatically collected via a telemetry network by DLR. The quality control of all environmental data transferred via Telemetry network of DLR is carried out by DLR by visual control and, since 2012, by automatic processing by GFZ. The delivered dataset contains the measured data and quality flags indicating the validity of each measured value and detected reasons for exclusion. The TERENO (TERrestrial ENvironmental Observatories) is an initiative of the Helmholtz Centers (Forschungszentrum Jülich FZJ, Helmholtz Centre for Environmental Research UFZ, Karlsruhe Institute of Technology KIT, Helmholtz Zentrum München - German Center for Environmental Health HMGU, German Research Centre for Geosciences - GFZ, and German Aerospace Center DLR) (http://www.tereno.net/overview-de). TERENO Northeastern German Lowland Observatory.TERENO (TERrestrial ENvironmental Observatories) spans an Earth observation network across Germany that extends from the North German lowlands to the Bavarian Alps. This unique large-scale project aims to catalogue the longterm ecological, social and economic impact of global change at regional level. Further specific goals of the TERENO remote sensing research group at GFZ are (1) supplying environmental data for algorithm development in remote sensing and environmental modelling, with a focus on soil moisture and evapotranspiration, and (2) practical tests of remote sensing data integration in agricultural land management practices.
    Keywords: scientific and technical information ; agricultural management ; agroindustry ; in situ ; point ; abiotic environment ; terrestrial environment ; TERENO ; TERENO Northeast ; TERENO Nordost ; DEMMIN ; Durable Environmental Multidisciplinary Monitoring Information Network ; TERrestrial ENvironmental Observatories ; GFZ ; GeoForschungsZentrum ; climate 〉 climatic factor 〉 air temperature ; climate 〉 microclimate ; climate 〉 weather 〉 weather condition ; EARTH SCIENCE 〉 AGRICULTURE 〉 SOILS 〉 SOIL MOISTURE/WATER CONTENT ; EARTH SCIENCE 〉 AGRICULTURE 〉 SOILS 〉 SOIL TEMPERATURE ; EARTH SCIENCE SERVICES 〉 DATA ANALYSIS AND VISUALIZATION 〉 CALIBRATION/VALIDATION ; EARTH SCIENCE SERVICES 〉 DATA MANAGEMENT/DATA HANDLING 〉 ARCHIVING ; EARTH SCIENCE SERVICES 〉 DATA MANAGEMENT/DATA HANDLING 〉 DATA DELIVERY ; EARTH SCIENCE SERVICES 〉 DATA MANAGEMENT/DATA HANDLING 〉 DATA INTEROPERABILITY ; EARTH SCIENCE SERVICES 〉 DATA MANAGEMENT/DATA HANDLING 〉 DATA INTEROPERABILITY 〉 DATA REFORMATTING ; EARTH SCIENCE SERVICES 〉 DATA MANAGEMENT/DATA HANDLING 〉 DATA NETWORKING/DATA TRANSFER TOOLS ; EARTH SCIENCE SERVICES 〉 DATA MANAGEMENT/DATA HANDLING 〉 TRANSFORMATION/CONVERSION ; EARTH SCIENCE SERVICES 〉 METADATA HANDLING 〉 AUTHORING TOOLS ; EARTH SCIENCE SERVICES 〉 METADATA HANDLING 〉 METADATA TRANSFORMATION/CONVERSION ; pedosphere 〉 soil 〉 soil water 〉 soil moisture 〉 soil moisture regime ; physical property 〉 temperature ; ScemeSpadeSoilMoisture_Spade_1 ; ScemeSpadeSoilMoisture_Spade_2 ; ScemeSpadeSoilMoisture_Spade_2_Temperature ; ScemeSpadeSoilMoisture_Spade_3 ; ScemeSpadeSoilMoisture_Spade_4 ; ScemeSpadeSoilMoisture_Spade_5 ; ScemeSpadeSoilMoisture_Spade_6 ; ScemeSpadeSoilMoisture_Spade_6_Temperature
    Type: Dataset , Dataset
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    DATA GFZ
  • 4
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    Seismic ground motion fields for six deterministic earthquake scenarios (Mw 8.5-9.0) for Lima (Peru) (2021)
    GFZ Data Services
    Details
    Publication Date: 2024-04-29
    Description: Abstract
    Description: This repository contains spatially distributed ground motion fields (GMF) for six determinist subduction earthquake scenarios for Metropolitan Lima and Callao (Peru). They have moment magnitudes between Mw 8.5 to 9.0 and emulate the historical earthquake that occurred in 1746 and caused extensive damage to that area. 1000 ground motion realisations in .XML format are generated using a single ground motion prediction equation per earthquake rupture with uncorrelated and cross-correlated residuals.
    Keywords: RIESGOS ; Scenario-based multi-risk assessment in the Andes region ; ground motion ; seismic ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 EARTHQUAKES ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 TSUNAMIS
    Type: Dataset , Dataset
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    DATA GFZ
  • 5
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    Quakeledger: a web service to serve earthquake scenarios (2021)
    GFZ Data Services
    Details
    Publication Date: 2024-04-29
    Description: Abstract
    Description: 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”
    Description: Other
    Description: 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〉
    Keywords: 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
    Type: Software , Software
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    DATA GFZ
  • 6
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    Shakyground: a web service to serve GMPE-based ground motion fields (2021)
    GFZ Data Services
    Details
    Publication Date: 2024-04-29
    Description: Abstract
    Description: 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.
    Description: TechnicalInfo
    Description: 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〉.
    Keywords: 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
    Type: Software , Software
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    DATA GFZ
  • 7
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    Assetmaster and Modelprop: web services to serve building exposure models and fragility functions for physical vulnerability to natural-hazards (2021)
    GFZ Data Services
    Details
    Publication Date: 2024-04-29
    Description: Abstract
    Description: 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/.
    Description: TechnicalInfo
    Description: 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.
    Keywords: RIESGOS ; Scenario-based multi-risk assessment in the Andes region ; python ; EARTH SCIENCE SERVICES 〉 DATA ANALYSIS AND VISUALIZATION ; EARTH SCIENCE SERVICES 〉 WEB SERVICES
    Type: Software , Software
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    DATA GFZ
  • 8
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    DEUS: Damage-Exposure-Update-Service (2021)
    GFZ Data Services
    Details
    Publication Date: 2024-04-29
    Description: Abstract
    Description: The software component DEUS (Damage-Exposure-Update-Service) is a Python3 script to evaluate/ update the physical damage and the structural vulnerability of a given building stock classified in terms of hazard-dependent classes (i.e. exposure model). This is obtained by estimating the damage evolution of the building stock given their initial damage state; the location of the scenario-based IM; and the use of selected fragility functions that must be compatible with the predefined building classes and IM. It can be run locally on your computer as well as a WPS (Web Processing Service). This version can handle single or consecutive deterministic hazard scenarios with spatially distributed Intensity Measures (IM). For single hazard scenarios, the process requires a single execution. In the case of consecutive deterministic hazard scenarios, the executions are proportional to the number of consecutive risk scenario (events) of interest.
    Description: Other
    Description: 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.
    Keywords: 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 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 VOLCANIC ERUPTIONS
    Type: Software , Software
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    DATA GFZ
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