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  • 1
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    How robust are landslide susceptibility estimates? (2020)
    Ozturk, Ugur ; Pittore, Massimiliano ; Behling, Robert ; [et al.]
    Springer Berlin Heidelberg
    Details
    Publication Date: 2023-06-16
    Description: Much of contemporary landslide research is concerned with predicting and mapping susceptibility to slope failure. Many studies rely on generalised linear models with environmental predictors that are trained with data collected from within and outside of the margins of mapped landslides. Whether and how the performance of these models depends on sample size, location, or time remains largely untested. We address this question by exploring the sensitivity of a multivariate logistic regression—one of the most widely used susceptibility models—to data sampled from different portions of landslides in two independent inventories (i.e. a historic and a multi-temporal) covering parts of the eastern rim of the Fergana Basin, Kyrgyzstan. We find that considering only areas on lower parts of landslides, and hence most likely their deposits, can improve the model performance by 〉10% over the reference case that uses the entire landslide areas, especially for landslides of intermediate size. Hence, using landslide toe areas may suffice for this particular model and come in useful where landslide scars are vague or hidden in this part of Central Asia. The model performance marginally varied after progressively updating and adding more landslides data through time. We conclude that landslide susceptibility estimates for the study area remain largely insensitive to changes in data over about a decade. Spatial or temporal stratified sampling contributes only minor variations to model performance. Our findings call for more extensive testing of the concept of dynamic susceptibility and its interpretation in data-driven models, especially within the broader framework of landslide risk assessment under environmental and land-use change.
    Description: Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347
    Keywords: ddc:551.3 ; Landslide susceptibility ; Logistic regression ; Southern Kyrgyzstan ; Landslide inventory ; Remote sensing
    Language: English
    Type: doc-type:article
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    CITATION GEO-LEO
  • 2
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    Impact Forecasting to Support Emergency Management of Natural Hazards (2020)
    AGU (American Geophysical Union) | Wiley
    Details
    Publication Date: 2023-02-08
    Description: Forecasting and early warning systems are important investments to protect lives, properties and livelihood. While early warning systems are frequently used to predict the magnitude, location and timing of potentially damaging events, these systems rarely provide impact estimates, such as the expected amount and distribution of physical damage, human consequences, disruption of services or financial loss. Complementing early warning systems with impact forecasts has a two‐fold advantage: it would provide decision makers with richer information to take informed decisions about emergency measures, and focus the attention of different disciplines on a common target. This would allow capitalizing on synergies between different disciplines and boosting the development of multi‐hazard early warning systems. This review discusses the state‐of‐the‐art in impact forecasting for a wide range of natural hazards. We outline the added value of impact‐based warnings compared to hazard forecasting for the emergency phase, indicate challenges and pitfalls, and synthesize the review results across hazard types most relevant for Europe. Plain language summary Forecasting and early warning systems are important investments to protect lives, properties and livelihood. While such systems are frequently used to predict the magnitude, location and timing of potentially damaging events, they rarely provide impact estimates, such as the expected physical damage, human consequences, disruption of services or financial loss. Extending hazard forecast systems to include impact estimates promises many benefits for the emergency phase, for instance, for organising evacuations. We review and compare the state‐of‐the‐art of impact forcasting across a wide range of natural hazards, and outline opportunities and key challenges for research and development of impact forecasting.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
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    PAPER (OCEANREP)
  • 3
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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
  • 4
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    Probabilistic inter-scheme compatibility matrices for buildings. An application using existing vulnerability models for earthquakes and tsunami from synthetic datasets constructed using the AeDEs form through expert-based heuristics (2022)
    GFZ Data Services
    Details
    Publication Date: 2024-04-29
    Description: Abstract
    Description: 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.
    Description: Other
    Description: 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.
    Keywords: 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
    Type: Dataset , Dataset
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    DATA GFZ
  • 5
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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
  • 6
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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
  • 7
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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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