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  • Data  (9)
  • GFZ German Research Center for Geosciences  (5)
  • TRR228 Database (TRR228DB)  (2)
  • -  (1)
  • The ScanArray consortium  (1)
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Keywords
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  • 1
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    Stress Map of Taiwan 2022 (2022)
    GFZ German Research Center for Geosciences
    Details
    Publication Date: 2022-01-11
    Description: Abstract
    Description: Stress maps show the orientation of the current maximum horizontal stress (SHmax) in the earth's crust. Assuming that the vertical stress (SV) is a principal stress, SHmax defines the orientation of the 3D stress tensor; the minimum horizontal stress Shmin is than perpendicular to SHmax. In stress maps SHmax orientations are represented as lines of different lengths. The length of the line is a measure of the quality of data and the symbol shows the stress indicator and the color the stress regime. The stress data are freely available and part of the World Stress Map (WSM) project. For more information about the data and criteria of data analysis and quality mapping are plotted along the WSM website at http://www.world-stress-map.org. The stress map of Taiwan 2022 is based on the WSM database release 2016. However, all data records have been checked and we added a large number of new data from earthquake focal mechanisms from the national earthquake catalog and from publications. The total number of data records has increased from n=401 in the WSM 2016 to n=6,498 (4,234 with A-C quality) in the stress map of Taiwan 2022 The update with earthquake focal mechanims is even larger since another 1313 earthquake focal mechanism data records beyond the scale of this map have been added to the WSM database. The digital version of the stress map is a layered pdf file generated with GMT (Wessel et al., 2019). It also provide estimates of the mean SHmax orientation on a regular 0.1° grid using the tool stress2grid (Ziegler and Heidbach, 2019). Two mean SHmax orientations are estimated with search radii of r=25 and 50 km, respectively, and with weights according to distance and data quality. The stress map and data are available on the landing page at https://doi.org/10.5880/WSM.Taiwan2022 where further information is provided. The earthquake focal mechanism that are used for this stress map are provided by the Taiwan Earthquake Research Center (TEC) available at the TEC Data Center (https://tec.earth.sinica.edu.tw).
    Description: Other
    Description: The World Stress Map (WSM) is a global compilation of information on the crustal present-day stress field. It is a collaborative project between academia and industry that aims to characterize the stress pattern and to understand the stress sources. It commenced in 1986 as a project of the International Lithosphere Program under the leadership of Mary-Lou Zoback. From 1995-2008 it was a project of the Heidelberg Academy of Sciences and Humanities headed first by Karl Fuchs and then by Friedemann Wenzel. Since 2009 the WSM is maintained at the GFZ German Research Centre for Geosciences and since 2012 the WSM is a member of the ICSU World Data System. All stress information is analysed and compiled in a standardized format and quality-ranked for reliability and comparability on a global scale.
    Type: Other , Other
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    DATA GFZ
  • 2
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    Dataset on effects of conservation with wildlife and agriculture on plant lignin and n-alkanes components in soils (2022)
    TRR228 Database (TRR228DB)
    Details
    Publication Date: 2022-03-09
    Description: Abstract
    Description: 1.Nature conservation is fostered through the expansion of protected areas. This is particularly evident in Sub-Saharan Africa (SSA), where conservation is intended to simultaneously promote the recovery of megafauna like elephants. Rising numbers of megaherbivores induce woody biomass losses but restore soil organic carbon (SOC). We hypothesized that increases of SOC under conservation with wildlife in SSA go directly along with increases in the preservation of plant residues in soil organic matter (SOM), traceable by plant biomarkers such as lignin and n-alkane. In contrast, intensification with agriculture leads to a reduction of them. To test this, we sampled topsoil (0-10 cm) and corresponding plant samples along different intensities of conservation and intensification in the Zambezi Region of Namibia, comprising a) conservation sites with low, medium and high elephant densities and b) adjacent intensification sites with rangeland and cropland. We found that lignin and n-alkane patterns of the above-ground vegetation were preserved in the soil. Confirming our hypothesis, increasing SOC contents with rising elephant densities went along with increasing accumulation of lignin-derived phenols. Under conservation, lignin concentrations were influenced by the input of woody debris into the soil, traced by carbon isotopes, clay, and total woody biomass. This could not be proved for n-alkanes. Under intensification, lignin derived phenols were lower than under conservation, but again, there was no clear pattern for n-alkanes. We showed that conservation with wildlife leads to an increase of SOC, which was accompanied by an accumulation of lignin-derived phenols in the soil organic matter. Increased input of woody debris, clay content and total biomass were important parameters for this lignin accumulation. In contrast, intensification with agriculture leads to a loss of lignin. Contrary, n- alkanes were not sensitive to detect effects of conservation or intensification. We conclude that increasing incorporation of woody residues into soil is a key mechanism controlling SOC accrual and to offset losses of aboveground biomass on SOC in sites under conservation with wildlife. The dataset contains raw data of lignin and n-alkanes and related soil properties. A third sheet contains a legend with information on abbreviations.
    Keywords: Ecology ; Environment ; Conservation ; Intensification ; Soil Organic Carbon ; Carbon Storage Dynamics ; Carbon Sequestration ; Biomarker ; Lignin ; n-Alkanes
    Type: Dataset , Microsoft excel file
    Format: MS Excel
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    DATA GFZ
  • 3
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    Stress Map of Great Britain and Ireland 2022 (2022)
    GFZ German Research Center for Geosciences
    Details
    Publication Date: 2022-03-10
    Description: Abstract
    Description: Stress maps show the orientation of the current maximum horizontal stress (SHmax) in the earth's crust. Assuming that the vertical stress (SV) is a principal stress, SHmax defines the orientation of the 3D stress tensor; the minimum horizontal stress Shmin is than perpendicular to SHmax. In stress maps SHmax orientations are represented as lines of different lengths. The length of the line is a measure of the quality of data and the symbol shows the stress indicator and the color the stress regime. The stress data are freely available and part of the World Stress Map (WSM) project. For more information about the data and criteria of data analysis and quality mapping are plotted along the WSM website at http://www.world-stress-map.org. The stress map of Great Britain and Ireland 2022 is based on the WSM database release 2016. All data records have been checked and we added a number of new data from earthquake focal mechanisms from the national earthquake catalog and borehole data. The number of data records has increased from n=377 in the WSM 2016 to n=474 in this map. Some locations and assigned quality of WSM 2016 data were corrected due to new information. The digital version of the map is a layered pdf generated with GMT (Wessel et al., 2019) using the topography of Tozer et al. (2019). We also provide on a regular 0.1° grid values of the mean SHmax orientation which have a standard deviation 〈 25°. The mean SHmax orientation is estimated using the tool stress2grid of Ziegler and Heidbach (2019). For this estimation we used only data records with A-C quality and applied weights according to data quality and distance to the grid points. The stress map is available at the landing page of the GFZ Data Services at http://doi.org/10.5880/WSM.GreatBritainIreland2022 where further information is provided.
    Description: Other
    Description: The World Stress Map (WSM) is a global compilation of information on the crustal present-day stress field. It is a collaborative project between academia and industry that aims to characterize the stress pattern and to understand the stress sources. It commenced in 1986 as a project of the International Lithosphere Program under the leadership of Mary-Lou Zoback. From 1995-2008 it was a project of the Heidelberg Academy of Sciences and Humanities headed first by Karl Fuchs and then by Friedemann Wenzel. Since 2009 the WSM is maintained at the GFZ German Research Centre for Geosciences and since 2012 the WSM is a member of the ICSU World Data System. All stress information is analysed and compiled in a standardized format and quality-ranked for reliability and comparability on a global scale.
    Keywords: crustal stress ; in situ stress ; tectonic stress ; crustal stress pattern ; geophysics ; tectonics ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 NEOTECTONICS ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 PLATE TECTONICS 〉 FAULT MOVEMENT ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 PLATE TECTONICS 〉 STRESS
    Type: Dataset , Dataset
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    DATA GFZ
  • 4
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    EMEC-2021 - The European-Mediterranean Earthquake Catalogue – Version 2021 (2023)
    GFZ German Research Center for Geosciences
    Details
    Publication Date: 2023-06-28
    Description: Abstract
    Description: This catalogue is the extended version of “The European-Mediterranean Earthquake Catalogue (EMEC) for the last millennium” (Grünthal and Wahlstrom, 2012, 2012a). It is an earthquake catalogue for tectonic events in the broader European Mediterranean area. It reached from the Azores (Mid-Atlantic Ridge) in the west, to Africa north of the Sahara in the south, the Arctic Sea in the north, and the regions of Levant, eastern Turkey, and the Caucasus in the west. This areal coverage gave the name to the catalogue: EMEC—The European-Mediterranean Earthquake Catalogue. It extends the previous version (Grünsthal and Wahlström, 2012), by the years 2007 to 2021 and thus contains tectonic events for the period AD 1000 to 2021 with a uniform magnitude Mw from the threshold of 3.5. The dataset contains 71271 entries.
    Keywords: earthquake catalogue ; magnitude harmonization ; europe ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 EARTHQUAKES 〉 EARTHQUAKE MAGNITUDE/INTENSITY ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 EARTHQUAKES 〉 EARTHQUAKE OCCURRENCES ; EARTH SCIENCE SERVICES 〉 DATA MANAGEMENT/DATA HANDLING 〉 CATALOGING ; EARTH SCIENCE SERVICES 〉 DATA MANAGEMENT/DATA HANDLING 〉 DATA DELIVERY ; EARTH SCIENCE SERVICES 〉 DATA MANAGEMENT/DATA HANDLING 〉 TRANSFORMATION/CONVERSION
    Type: Dataset , Dataset
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    DATA GFZ
  • 5
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    INQUA 2023 Abstract: Evidence of Late Cenozoic reactivation of an inhereted strike-slip fault system in the Longitudinal Valley of Northernmost Chile (2023)
    -
    Details
    Publication Date: 2023-10-24
    Description: Abstract
    Description: This publication correspond to an abstract accepted as an oral presentation in the XXI International INQUA Congress 2023, held in Rome, on 14–20 July 2023. The work was presented in the session 185 &039;Active faults evolution: revelations from different timescales&039;. The abstract is shown in the inquaroma2023.exordo.com platform printed in a PDF.
    Keywords: Geoscientific Information ; Neotectonics ; Cosmogenic Nuclides ; Geomorphology ; Tectonics ; Structural Geology
    Type: Text , Abstract
    Format: 178 Kilobytes
    Format: PDF
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    DATA GFZ
  • 6
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    Matlab Script FAST Calibration v.2.0 (2021)
    GFZ German Research Center for Geosciences
    Details
    Publication Date: 2023-12-04
    Description: Abstract
    Description: The 3D geomechanical-numerical modelling aims at a continuous description of the stress state in a subsurface volume. The model is fitted to the model-independent stress data records by adaptation of the displacement boundary conditions. This process is herein referred to as model calibration. Depending on the amount of available stress data records and the complexity of the model the calibration can be a lengthy process of trial-and-error to estimate the best-fit boundary conditions. The tool FAST Calibration (Fast Automatic Stress Tensor Calibration) is a Matlab script that facilitates and speeds up this calibration process. By using a linear regression it requires only three test model scenarios with different displacement boundary conditions to calibrate a geomechanical-numerical model on available stress data records. The differences between the modelled and observed stresses are used for the linear regression that allows to compute the displacement boundary conditions required for the best-fit estimation. The influence of observed stress data records on the best-fit displacement boundary conditions can be weighted. Furthermore, FAST Calibration provides a cross checking of the best-fit estimate against indirect stress information that cannot be used for the calibration process, such as the observation of borehole breakouts or drilling induced fractures.
    Description: Other
    Description: GNU General Public License, Version 3, 29 June 2007 Copyright © 2021 Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Potsdam, Germany FAST Calibration is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. FAST Calibration 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 GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.
    Keywords: geomechanical-numerical model ; stress ; in-situ stress ; model calibration ; stress tensor calibration ; modelling tool ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 NEOTECTONICS ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 PLATE TECTONICS 〉 CRUSTAL MOTION 〉 CRUSTAL MOTION DIRECTION ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 PLATE TECTONICS 〉 FAULT MOVEMENT ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 PLATE TECTONICS 〉 PLATE BOUNDARIES ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 PLATE TECTONICS 〉 STRESS
    Type: Software , Software
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    DATA GFZ
  • 7
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    Matlab Script FAST Calibration v 2.4 (2023)
    GFZ German Research Center for Geosciences
    Details
    Publication Date: 2023-12-04
    Description: Abstract
    Description: The 3D geomechanical-numerical modelling aims at a continuous description of the stress state in a subsurface volume. The model is fitted to the model-independent stress data records by adaptation of the displacement boundary conditions. This process is herein referred to as model calibration. Depending on the amount of available stress data records and the complexity of the model the calibration can be a lengthy process of trial-and-error to estimate the best-fit boundary conditions. The tool FAST Calibration (Fast Automatic Stress Tensor Calibration) is a Matlab script that facilitates and speeds up this calibration process. By using a linear regression it requires only three test model scenarios with different displacement boundary conditions to calibrate a geomechanical-numerical model on available stress data records. The differences between the modelled and observed stresses are used for the linear regression that allows to compute the displacement boundary conditions required for the best-fit estimation. The influence of observed stress data records on the best-fit displacement boundary conditions can be weighted. Furthermore, FAST Calibration provides a cross checking of the best-fit estimate against indirect stress information that cannot be used for the calibration process, such as the observation of borehole breakouts or drilling induced fractures. In order to bridge the scale gap between a regional stress model and a local reservoir model, the multistage calibration procedure is applied where a local model is calibrated solely on the stress state provided by a regional model. FAST Calibration provides the necessary tools and guidelines.
    Keywords: geomechanical-numerical model ; stress ; in-situ stress ; model calibration ; stress tensor calibration ; modelling tool ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 NEOTECTONICS ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 PLATE TECTONICS 〉 CRUSTAL MOTION 〉 CRUSTAL MOTION DIRECTION ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 PLATE TECTONICS 〉 FAULT MOVEMENT ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 PLATE TECTONICS 〉 PLATE BOUNDARIES ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 PLATE TECTONICS 〉 STRESS
    Type: Software , Software
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    DATA GFZ
  • 8
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    Historical road network of Kenya (1950s – 1980s) extracted from topographic maps (Version 1.0) (2024)
    TRR228 Database (TRR228DB)
    Details
    Publication Date: 2024-04-26
    Description: Abstract
    Description: This dataset includes a shapefile representing the digitized historical road network of Kenya. It contains over 56,000 km of historical roads extracted from 449 historical topographic maps of 1:50,000 scale and 71 maps of 1:100,000 scale covering the time period from the 1950s to the 1980s. The topographic maps were obtained from various sources in Kenya and the UK. Most of maps were collected in Kenya provided by the Survey of Kenya and several local county governments’ survey and urban planning departments. Additionally, some maps were obtained from archives in Great Britain, namely the Bodleian Library of the University of Oxford and the Cambridge University Library. All the acquired maps were originally created and published by the Directorate of Overseas Surveys (DOS), the War Office, General Staff, Geographical Section and the Survey of Kenya. The road data was extracted from these maps using deep learning techniques, including a Python script and ArcGIS Pro “Multi-Task Road Extractor” tool.
    Keywords: Infrastructure ; Imagery/Base Maps/Earth Cover ; Road Network ; Roads ; Geodata ; Historical Data ; Vector Data ; GIS ; Africa ; African History ; Historical Maps ; Infrastructure ; Road ; Geographic information system ; Data ; road network ; road ; data ; infrastructure development
    Type: Dataset , Shapefile
    Format: ESRI Shapefile
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    DATA GFZ
  • 9
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    ScanArray Core (1G 2012-2017) (2012)
    The ScanArray consortium
    Details
    Publication Date: 2024-05-21
    Description: Abstract
    Description: The ScanArray experiment is a major collaborative effort of institutions in Scandinavia and Germany to map crustal and mantle structure below Scandinavia using a dense temporary deployment of broadband seismometers. Scientific questions to be addressed include (among others): 1. What supports the topographic high of the Scandes? 2. How does lithospheric thickness vary within Fennoscandia? 3. What is the internal fabric of the mantle lithosphere? 4. Are there differences in the crustal structure between the different blocks of Fennoscandia? This data set, termed ScanArray core, comprises the temporary stations deployed by the University of Copenhagen, the University of Aarhus, and the University of Oslo, the Karlsruhe Institute of Technology (KIT) and the GeoForschungsZentrum Potsdam (GFZ) as part of the ScanArray experiment. Stations within this dataset are deployed for periods between 2 and 4 years. Data are available from the GFZ seismological data archive with network code 1G. Waveform data will be fully opened in early 2020. The wider ScanArray dataset additionally includes the multi-use temporary deployments Neonor2 (FDSN-code 2D, University of Bergen, NORSAR) and ScanLips3D (University of Leicester; archived at IRIS DMC), and the permanent networks of Sweden (UP, SNSN), Norway (NS, NNSN), Denmark (DK, DNSN) and Finland (HE, FNSN) as well as a subset of NORSAR stations (NO). The SNSN rearranged the distribution of broadband seismometers and deployed additional temporary stations to meet the objectives of the ScanArray experiment. ScanArray core and these other networks (except ScanLips3D) jointly form the virtual network _SCANARRAY. Partners of the ScanArray consortium are: University of Aarhus, Uppsala University, University of Oslo, University of Bergen, Karlsruhe Institute of Technology, NORSAR, University of Copenhagen, Deutsches GeoForschungsZentrum (GFZ) and Istanbul Technical University.
    Keywords: Lithosphere ; Monitoring system ; Seismological stations ; In Situ/Laboratory Instruments 〉 Magnetic/Motion Sensors 〉 Seismometers ; In Situ Land-based Platforms 〉 GEOPHYSICAL STATIONS/NETWORKS ; Passive seismic ; Seismometers ; Velocity ; MiniSEED ; GIPP ; MESI
    Type: Dataset , Seismic Network
    Format: 1200GB
    Format: .mseed
    Format: XML
    Location Call Number Expected Availability
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    DATA GFZ
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