10 documents found in 369ms
# 1
Heimann, Sebastian • Isken, Marius • Kühn, Daniela • Sudhaus, Henriette • Steinberg, Andreas • (et. al.)
Abstract: Grond is an open source software tool for robust characterization of earthquake sources. Moment tensors and finite fault rupture models can be estimated from a combination of seismic waveforms, waveform attributes and geodetic observations like InSAR and GNSS. It helps you to investigate diverse magmatic, tectonic, and other geophysical processes at all scales. It delivers meaningful model uncertainties through a Bayesian bootstrap-based probabilistic joint inversion scheme. The optimisation explores the full model space and maps model parameter trade-offs with a flexible design of objective functions. Rapid forward modelling is enabled by using pre-computed Green's function databases, handled through the Pyrocko software library. They serve synthetic near-field surface displacements and synthetic seismic waveforms for arbitrary earthquake source models and geometries.
# 2
Mikolaj, Michal
Abstract: This software publication describes the data acquisition, processing and modelling of hydrological, meteorological and gravity time series prepared for the Argentine-German Geodetic Observatory (AGGO) in La Plata, Argentina. The corresponding output data set is available at http://doi.org/10.5880/GFZ.5.4.2018.001 (Mikolaj et al., 2018). Processed hydrological series include soil moisture, temperature, electric conductivity, and groundwater variation. The processed meteorological time series comprise air temperature, humidity, pressure, wind speed, solar short- and long-waver radiation, and precipitation. Modelling scripts include evapotranspiration, combined precipitation, and water content variation in the zone between deepest soil moisture sensor and groundwater. In addition, large-scale hydrological, oceanic as well as atmospheric effect are modelled along with the local hydrological effects. To allow for a comparison of the model outputs to observations, processing script of gravity residuals is provided as well.
# 3
Mikolaj, Michal • Güntner, Andreas • Brunini, Claudio • Wziontek, Hartmut • Gende, Mauricio • (et. al.)
Abstract: The data set contains hydrological, meteorological and gravity time series collected at Argentine-German Geodetic Observatory (AGGO) in La Plata, Argentina. The hydrological series include soil moisture, temperature, electric conductivity, soil parameters, and groundwater variation. The meteorological time series comprise air temperature, humidity, pressure, wind speed, solar short- and long-waver radiation, and precipitation. The observed hydrometeorological parameters are extended by modelled value of evapotranspiration and water content variation in the zone between deepest soil moisture sensor and the groundwater level. Gravity products include large-scale hydrological, oceanic as well as atmospheric effects. These gravity effects are furthermore extended by local hydrological effects and gravity residuals suitable for comparison and evaluation of the model performance. Provided are directly observed values denoted as Level 1 product along with pre-processed series corrected for known issues (Level 2). Level 3 products are model outputs acquired using Level 2 data. The maximal temporal coverage of the data set ranges from May 2016 up to November 2018 with some exceptions for sensors and models set up in May 2017. The data set is organized in a database structure suitable for implementation in a relational database management system. All definitions and data tables are provided in separate text files allowing for traditional use without database installation. Software related to the data acquisition, processing, and modelling can be found in a separate publication describing scripts applied to the data set presented here. The software publication is available at https://doi.org/10.5880/GFZ.5.4.2018.002 (Mikolaj, 2018)
# 4
Scherler, Dirk • Wulf, Hendrik • Gorelick, Noel
Abstract: This dataset is supplementary to the article of Scherler et al. (submitted), in which the global distribution of supraglacial debris cover is mapped and analyzed. For mapping supraglacial debris cover, we combined glacier outlines from the Randolph Glacier Inventory (RGI) version 6.0 (RGI consortium, 2017) with remote sensing-based ice and snow identification. Areas that belong to glaciers but that are neither ice nor snow were classified as debris cover. This dataset contains the outlines of the mapped debris-covered glaciers areas, stored in shapefiles (.shp). For creating this dataset, we used optical satellite data from Landsat 8 (for the time period 2013-2017), and from Sentinel-2A/B (2015-2017). For the ice and snow identification, we used three different algorithms: a red to short-wavelength infrared (swir) band ratio (RATIO; Hall et al., 1988), the normalized difference snow index (NDSI; Dozier, 1989), and linear spectral unmixing-derived fractional debris cover (FDC; e.g., Keshava and Mustard, 2002). For a detailed description of the debris-cover mapping and an analysis of the data, please see Scherler et al. (submitted). This dataset includes debris cover outlines based on either Landsat 8 (LS8; 30-m resolution) or Sentinel 2 (S2; 10-m resolution), and the three algorithms RATIO, NDSI, FDC. In total, there exist six different zip-files that each contain 19 shapefiles. The structure of the shapefiles follows that of the RGI version 6.0 (RGI consortium, 2017), with one shapefile for each RGI region. The original RGI shapefiles provide each glacier as one entry (feature) and include a variety of ancillary information, such as area, slope, aspect (RGI Consortium 2017a, Technical Note p. 12ff). Because the debris-cover outlines are based on the RGI v6.0 glacier outlines, all fields of the original shapefiles, which refer to the glacier, are retained, and expanded with four new fields: - DC_Area: Debris-covered area in m². Note that this unit for area is different from the unit used for reporting the glacier area (km²).- DC_BgnDate: Start of the time period from which satellite imagery was used to map debris cover.- DC_EndDate: End of the time period from which satellite imagery was used to map debris cover.- DC_CTSmean: Mean number of observations (CTS = COUNTS) per pixel and glacier. This number is derived from the number of available satellite images for the respective time period, reduced by filtering pixels due to cloud and snow cover. The dataset has a global extent and covers all of the glaciers in the RGI v. 6.0, but it exhibits poor coverage in the RGI region Subantarctic and Antarctic, where the debris cover extents are based on very few observations.
# 5
Ritter, Malte Christian • Santimano, Tasca • Rosenau, Matthias • Leever, Karen • Oncken, Onno
Abstract: This dataset is supplementary to the article of Ritter et al. (2017). In this article, a new experimental device is presented that facilitates precise measurements of boundary forces and surface deformation at high temporal and spatial resolution. This supplementary dataset contains the measurement data from two experiments carried out in this new experimental device: one experiment of an accretionary critical wedge and one of Riedel-type strike-slip deformation. For a detailed description of the set-up and an analysis of the data, please see Ritter et al. (2017). The data available for either experiment are:• A video showing deformation in top view together with the evolution of boundary force. This file is in AVI-format.• A time-series of 2D vector fields describing the surface deformation. These vector fields were obtained from top-view video images of the respective experiment by means of digital image correlation (DIC). Each vector field is contained in a separate file; the files are consecutively numbered. The vector fields are stored in *.mat-files that can be opened using e.g. the software Matlab or the freely available GNU Octave. They take the form of Matlab structure arrays and are compatible to the PIVmat-toolbox by Moisy (2016) that is freely available. The most important fields of the structure are: x and y, that are vectors spanning a coordinate system, and vx and vy, which are arrays containing the actual vector components in x- and y-direction, respectively.• A file containing the measurements of the boundary force applied to drive deformation. This file is also a *.mat-file, containing a structure F with fields force, velocity and position. These fields are vectors describing the force applied by the indenter, the indenter velocity and the indenter position
# 6
Rosenau, Matthias • Corbi, Fabio • Dominguez, Stephane • Rudolf, Michael • Ritter, Malte • (et. al.)
Abstract: This data set contains various data derived from rock and rock analogue testing and analogue models which are presented in Rosenau et al. (2016) to which these data are supplement to..A first group of data contains animations of complementary analogue and numerical models of subduction zone earthquake cycles (A). A second group comprises analogue earthquake data and time series of surface deformation derived from scale models of subduction zone earthquake cycles (B). A third group consist of time series of stick-slip experiments using a ring shear tester (C). Finally, friction data both from rocks and rock analogue materials (D) as well as elasticity data from rock analogues are presented (E).See the Description of data and the List of files in the Data Download section for additional data description.
# 7
Darmawan, Herlan • Walter, Thomas • Richter, Nicole • Nikkoo, Mehdi
Abstract: This data publication is a high resolution Digital Elevation Model (DEM) generated for the Merapi summit by combining terrestrial laser scanning (TLS) and unmanned aerial vehicles (UAVs) photogrammetry data acquired in 2014 and 2015, respectively. The structures of the data are further analysed in Darmawan et al. 2017 (http://doi.org/10.1016/j.jvolgeores.2017.11.006). The published datasets consist of combined point clouds with ~65 million data points and a DEM with a resampled resolution of 0.5 m. The DEM data covers the complexity of the Merapi summit with area of 2 km2. The coordinate of the datasets is projected to global coordinates (WGS 1984 UTM Zone 49 South). TLS is a topography mapping technique which exploits the travel time of a laser beam to measure the range between the ground-based scanning instrument and the earth’s surface. TLS provides high accuracy, precision, and resolution for topography mapping, however, it requires different scan position to obtain accurate topography model in a complex topography. The TLS dataset was acquired by using a long-range RIEGL VZ-6000 instrument with a Pulse Repetition Rate (PRR) of 30 kHz. The Merapi data includes an observation range of 0.129 – 4393.75 m, a theta range (vertical) of 73 – 120° with a sampling angle of 0.041°, a phi range (horizontal) of 33° - 233° with a sampling angle of 0.05°, and 12 reflectors for each scan. The used TLS dataset was achieved by combining two scan positions, both realized in September 2014. In order to reduce still eminent shadowing, we conducted additionally a UAV photogrammetry survey. The UAV data allows to fill data gaps and generate a complete 3D point cloud. The UAV photogrammetry was conducted by using DJI Phantom 2 quadcopter drone in October 2015. The drone carried GoPro HERO 3+ camera and a H3-3D gimbal to reduce image shaking. We obtained over 300 images which cover the summit area of Merapi. By applying the Structure from Motion algorithm, we are able to generate a 3D point cloud model of Merapi summit. Further details on this procedure are provided in Darmawan et al. (2017). Structure from Motion is a technique to generate a 3D model based on 2D overlapped images. The algorithm detects and matches the same ground features of 2D images, reconstructs a 3D scene, and calculates a depth map for each camera frame. The algorithm used is implemented in Agisoft Photoscan Professional software. After importing the images in Agisoft, we used the ‘align image’ function with high accuracy setting to generate 3D sparse point cloud and ‘build dense cloud’ function with high quality to generate 3D dense point cloud. The 3D point clouds of TLS and UAV photogrammetry were then georeferenced to our georeferenced 3D point cloud which acquired in 2012. The RMS of TLS and UAV photogrammetry during georeferenced is 0.60 and 0.44 m, respectively, as described in Further details on this procedure are provided in Darmawan et al. (2017). After georeferencing, both 3D point clouds were merged and interpolated to a raster format in the ArcMap software.
# 8
Maystrenko, Yuriy • Bayer, Ulf • Scheck-Wenderoth, Magdalena
Abstract: The data files belong to a 3D structural model which covers the Glueckstadt Graben, NW Germany. The constructed 3D model is 170 km wide and 166 km long with a horizontal grid spacing of 2000 m, and a vertical resolution corresponding to the number of integrated layers. The 3D structural model includes 10 layers: (1) sea water; (2) Quaternary-Neogene; (3) Paleogene; (4) Upper Cretaceous; (5) Lower Cretaceous; (6) Jurassic; (7) uppermost part of the Middle Triassic and the Upper Triassic (Keuper); (8) Middle Triassic without uppermost and lowermost parts (Muschelkalk); (9) Lower Triassic and lowermost part of the Middle Triassic (Buntsandstein); (10) upper part of the Lower Permian and the Upper Permian (undivided Zechstein plus salt-rich Rotliegend). The thicknesses of the layers correspond to apparent thicknesses. In addition, data for earth surface topography is provided in the file: 0_Topography.dat. Model coordinates are based on the Gauss-Krueger DHDN (zone 3) system. The data format is ASCII and contains three columns (X, Y and Z), where X and Y are geographical coordinates (X = longitude, Y = latitude); Z (in m) is thickness of the layer or structural depth (base of layer) or surface elevation. The grid of each layer consists of 86 cells in W-E direction and 84 cells in S-N direction. The grid limits are the following: Xmin = 3450000 and Xmax = 3620000; Ymin = 5915100 and Ymax = 6081100. The vertical datum of the 3D model refers to the mean sea level. Organisation of data files: Data are organized in two folders (“Bases” and “Thicknesses”); data for earth surface topography (in case of water: sea level) is in the root folder ( 0_Topography.dat).The folder “Bases” contains 10 data files named according to the model layers as outlined above. The folder “Thicknesses” contains 10 data files named according to the model layers as outlined above.
# 9
Scheck-Wenderoth, Magdalena • Maystrenko, Yuriy
Abstract: The data files belong to a 3D structural model which covers the Vøring and Møre basins offshore Norway. In addition, a part of the exposed Fennoscandian Caledonides in the south-east and an oceanic crustal domain are covered by the model. The constructed 3D model is 490 km wide and 660 km long with a horizontal grid spacing of 2500 m, and a vertical resolution corresponding to the number of integrated layers. The lithospheric-scale 3D structural model includes 14 layers: (1) sea water;(2) upper Neogene (post-middle Miocene) sediments;(3) middle-upper Paleogene-lower Neogene (pre-middle Miocene) sediments;(4) lower Paleogene (Paleocene) sediments;(5) oceanic layer 2AB (basalts);(6) Upper Cretaceous (post-Cenomanian) sediments;(7) Lower Cretaceous (preCenomanian) sediments;(8) pre-Cretaceous sediments;(9) continental crystalline crust;(10) oceanic layer 3A;(11) high-density zones within the continental crystalline crust;(12) oceanic layer 3B;(13) high-density bodies within the lower continental crystalline crust;(14) lithospheric mantle. The thicknesses of the layers correspond to apparent thicknesses. In addition, data for earth surface topography is provided in the file: 0_Topography.dat. Model coordinates are based on the UTM 33 Zone (Northern Hemisphere) using the WGS 84 datum. The data format is ASCII and contains three columns (X, Y and Z), where X and Y are geographical coordinates (X = longitude, Y = latitude); Z (in m) is thickness of the layer or structural depth (base of layer) or surface elevation. The grid of each layer consists of 196 cells in W-E direction and 265 cells in S-N direction. The grid limits are the following: Xmin = -222590 and Xmax = 267410; Ymin = 6892200 and Ymax = 7552200. The vertical datum of the 3D model refers to the mean sea level. Organisation of data files: Data are organised in two folders (“Bases” and “Thicknesses”); data for earth surface topography (in case of water: sea level) is in the root folder: 0_Topography.dat. The folder “Bases” contains 14 data files named according to the model layers as outlined above. The folder “Thicknesses” contains 14 data files named according to the model layers as outlined above.
# 10
Isken, Marius • Sudhaus, Henriette • Heimann, Sebastian • Steinberg, Andreas • Daout, Simon • (et. al.)
Abstract: We present a modular open-source software framework - kite (http://pyrocko.org), written in Python and C. The software enables rapid post-processing of space-born InSAR-derived surface displacement maps, swift parametrization and sub-sampling of the displacement measurements. With our package we aim to ease and streamline the optimization of earthquake source parameters from InSAR and GPS data and facilitate their joint optimization with seismological waveforms in combination with the pyrocko toolbox. Through such joint data optimizations from near- and far-field observations the determination of rupture parameters and processes will become more accurate and robust. Moreover, we present an intuitive kinematic deformation modelling sandbox for handling and manipulating various kinds of tectonic and volcanic deformation sources, interacting in elastic homogeneous or layered, full- or half-spaces.
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