21 documents found in 362ms
# 1
Quinteros, Javier
Abstract: This service provides routing information for distributed data centres, in the case where multiple different seismic data centres offer access to data and products using compatible types of services. Examples of the data and product objects are seismic timeseries waveforms, station inventory, or quality parameters from the waveforms. The European Integrated Data Archive (EIDA) is an example of a set of distributed data centres (the EIDA „nodes“). EIDA have offered Arclink and Seedlink services for many years, and now offers FDSN web services, for accessing their holdings. In keeping with the distributed nature of EIDA, these services could run at different nodes or elsewhere; even on computers from normal users. Depending on the type of service, these may only provide information about a reduced subset of all the available waveforms. To be effective, the Routing Service must know the locations of all services integrated into a system and serve this information in order to help the development of smart clients and/or services at a higher level, which can offer the user an integrated view of the entire system (EIDA), hiding the complexity of its internal structure. The service is intended to be open and able to be queried by anyone without the need of credentials or authentication.
# 2
Ritter, Malte C. • Rosenau, Matthias • Oncken, Onno
Abstract: This dataset is supplementary material to the article of Ritter et al. (2017). In this article, the similarity of fault propagation work in analogue sandbox experiments to natural fault networks is investigated through measurements in a strike-slip sandbox and in a ring-shear-tester. The transient shear strength of the samples is measured for different fault lengths and from this the work is determined. For a detailed description of the procedure and the set-up please see Ritter et al. (2017). The data available in this supplementary publication are:• For the strike-slip experiments three video sequences of the deformation together with the evolution of boundary force for fault lengths of 20 cm, 30 cm and 40 cm. The videos show the curl of the deformation field, determined by Digital Image Correlation of top-view video images. These files are in AVI-format and included in the zip folder 2017-005-Ritter-movies.zip.• A folder containing force vs. displacement measurements for each experiment (2017-005-Ritter-forces.zip). These are 25 ASCII-files that contain two columns of numerical data: the first column is the displacement in meter; the second column is the corresponding force in newton. The files are named according to the following pattern: <fault length in meter>_<experiment number>.asc• A Matlab script to load the force files and calculate the work. This file is called “plotwork.m” and calls the Matlab function “work.m”, which does the actual calculations. These files have been tested in Matlab version 2012b. The surface deformation data are available upon request.
# 3
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
# 4
Schröter, Kai • Redweik, Richard • Lüdtke, Stefan • Meier, Jessica • Bochow, Mathias • (et. al.)
Abstract: Climate change manifests in terms of changing frequency and magnitude of extreme hydro-meteorological events and thus drives changes in urban flood hazard. Flood risk oriented urban planning is key to derive smart adaptation strategies, strengthen resilience and achieve sustainable development. 3D city models offer detailed spatial information which is useful to describe the exposure and to characterize the susceptibility of buildings at risk. This web-based application presents the 3d-city flood damage module (3DCFD) prototype which has been developed and implemented within a pathfinder projected funded by Climate-KIC during 2015-2016. The presentation illustrates the results of the 3DCFD-module exemplarily for the demonstration case in the City of Dresden. Relative damage to residential buildings which results from various flooding scenarios is shown for the focus area Pieschen in Dresden. The application allows the user to browse through the virtual city model and to colour the residential buildings regarding their relative damage values caused by different flooding scenarios. To do so click on 'Content', then on the brush-icon next to 'Buildings' and select a certain style from the drop-down menu. A style represents a specific combination of loss model and flooding scenario. Flooding scenarios provide spatially detailed inundation depth information according to different water stages at the gauge Dresden. Currently two flood loss models are implemented: a simple stage-damage-function (sdf) which related inundation depth to relative loss and the 3DCFD-module which uses additional information about building characteristics available from the virtual city model. A click on a coloured building will display additional information. The loss estimation module has been developed by the German Research Centre for Geosciences (GFZ), Section Hydrology. The web-application has been developed by virtualcitySYSTEMS GmbH. The data consisting of flood scenarios, a virtual 3D city model, and a terrain model were provided by the City of Dresden.
# 5
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.
# 6
Brunke, Heinz-Peter • Widmer-Schidrig, Rudolf • Korte, Monika
Abstract: For frequencies above 30 mHz the instrument intrinsic noise level of typical fluxgate magnetometers used at geomagnetic observatories usually masks ambient magnetic field variations on magnetically quiet days. Natural field variations referred to as pulsations (Pc-1, Pc-2, Pi-1) fall in this band. Usually their intensity is so small that they rarely surpass the instrumental noise of fluxgate magnetometers. INTERMAGNET has set a minimum quality standard for definitive 1 s data (Turbitt, 2014) which can actually hardly be met by fluxgate magnetometers in use by magnetic observatories. Brunke et al. (2017) propose a method to improve 1Hz observatory data by merging data from the proven and tested fluxgate magnetometers currently in use with induction coil magnetometers into a single data stream. This data publication includes the according MATLAB software package implementing the merging of both data sets. The content of the software package and the functionality of each module is described in the content.txt file that is also included in the zip folder. The resulting data are in line with the INTERMAGNET format for 1 s magnetic data, but surpasses the INTERMAGNET 1 s standard by far. The long term stability of the fluxgate data is not affected. The changes to the fluxgate data remain within the range of the instrument intrinsic noise. In addition to the Matlab software, we provide test datasets of one day length kindly provided by the magnetic observatories Niemegk, Conrad and Eskdalemuir.
# 7
Brunke, Heinz-Peter
Abstract: This data publication includes a matlab software package as described in Brunke (2017). In addition to the Matlab software, we provide three test dataset from the Niemegk magnetic observatories (NGK). We present a numerical method, allowing for the evaluation of an arbitrary number (minimum 5 as there are 5 independent parameters) of telescope orientations. The traditional measuring schema uses a fixed number of eight orientations (Jankowski et al, 1996). Our method provides D, I and Z base values and calculated uncertitudes of them. A general approach has significant advantages. Additional measurements may by seamlessly incorporate for higher accuracy. Individual erroneous readings are identified and can be discarded without invalidating the entire data set, a-priory information can be incorporated. We expect the general method to ease requirements also for automated DI-flux measurements. The method can reveal certain properties of the DI-theodolite, which are not captured by the conventional method. Based on the alternative evaluation method, a new faster and less error prone measuring schema is presented. It avoids the need to calculate the magnetic meridian prior to the inclination measurements. Measurements in the vicinity of the magnetic equator become possible with theodolites without zenith ocular.
# 8
Lu, Biao • Barthelmes, Franz • Petrovic, Svetozar • Pflug, Hartmut • Förste, Christoph • (et. al.)
Abstract: The dataset contains the results of airborne gravimetry realized by the GEOHALO flight mission over Italy in 2012. The intention was to show whether and how an efficient airborne gravity field determination is feasible in wide areas when using a fast jet aircraft like HALO at higher altitudes. Here, unlike in airborne gravimetry for exploration purposes, the aim is not primarily to reach the highest spatial resolution by flying as low and slowly as possible. A challenge for HALO would be to map areas (e.g., Antarctica) where only insufficient or no terrestrial gravity data are available to achieve a resolution which is better than that of satellite-only gravity field models. This is beneficial for the generation of global gravity field models which require a uniform, high spatial resolution for the gravity data over the entire Earth. The raw gravimetry recordings were recorded by the GFZ air-marine gravimeter Chekan-AM. Kinematic vertical accelerations were calculated from Doppler observations which were derived by GNSS carrier phase measurements (1 Hz). To remove the high-frequency noise, a low-pass filter with a cut-off wavelength of 200 s (corresponding to a half-wavelength resolution of approximately 12 km) was applied to both the Chekan-AM measurements and GNSS kinematic accelerations. To investigate how future airborne gravity campaigns using jet aircraft could be optimized, a dedicated flight track was repeated two times which shows that the equipment worked well also at higher altitude and speed. For the accuracy analysis 17 crossover points could be used. This analysis yielded a RMS of the gravity differences of 1.4 mGal which, according to the law of error propagation, implies an accuracy of a single measurement to be 1 mGal. The dataset is provided in as ASCII text (Lu-et-al_2017-001_Tracks_GEOHALO.txt) and is described in the README. For a detailed description of the set-up and analysis of the data, please see Biao et al. (2017, http://doi.org/10.1002/2017JB014425).
# 9
Schröter, Kai • Rivas Lopez, Maria del Rocio • Nguyen, Viet Dung • Wortmann, Michael • Liersch, Stefan • (et. al.)
Abstract: This data set provides a set of residential flood loss maps (ESRI Shapefiles) for the German part of the Danube catchment for current and future climate based on a stochastic event set of flood hazard footprints (Schröter et al. 2017; http://doi.org/10.5880/GFZ.5.4.2017.003). The multi-polygon maps provide flood loss in EUR for residential land use areas according to the ATKIS (Authoritative Topographic Cartographic Information System) codes residential areas (2111) and areas of mixed use (2113), (BKG GEODATENZENTRUM: ATKIS-Basis-DLM, 2005). Loss values are calculated using the FloodLossEstimationMOdel for the residential sector (FLEMOps+r) developed by Elmer et al. (2010) in combination with exposure data based on total replacement costs for residential buildings (Kleist et al., 2006). Asset values with a spatial resolution corresponding to the underlying inundation depth maps of the stochastic event set (100x100 m) have been derived by applying a binary disaggregation method and using the digital basic landscape model ATKIS as ancillary information (Wünsch et al. 2009). The flood event sets are derived for the historical period (1970-1990) and two RCPs (4.5 and 8.5) for the near future (2020-2049) and far future (2070-2099) for four CORDEX models. These flood event sets are created within continuous long-term simulations of a coupled model chain including the IMAGE stochastic multi-variable, multi-site weather generator, the eco-hydrological model SWIM and 1D river network coupled with 2D hydro-numeric hinterland inundation model, see Schröter et al. (2017) for further details The data have been produced within the OASIS+ demonstrator project 'Future Danube Multi Hazard and Risk Model' funded by Climate-KIC in the period from January 2016 to December 2017. Key features:• Flood loss maps for residential areas in the German part of the Danube catchment from stochastic flood event sets for current and future climate.• High spatial resolution for ATKIS residential land use areas intersected with 100x100 m inundation depth maps.• Flood loss scenarios for historical period (1970-1990) and two RCPs (4.5 and 8.5) for the near future (2020-2049) and far future (2070-2099) from four CORDEX models Key usage:• Large-scale flood risk assessment• Future flood risk assessment• Flood risk management with long-term perspective A full description of the data provenance and specification is given in the README_Schroeter-et-al-2017-004.txt file available in the data download section at this DOI Landing Page.
# 10
Schröter, Kai • Rivas Lopez, Maria del Rocio • Nguyen, Viet Dung • Wortmann, Michael • Liersch, Stefan • (et. al.)
Abstract: This data set provides a stochastic event set of flood inundation depth maps (fluvial flood hazard footprints) for the German part of the Danube catchment for current and future climate in GEOTIFF format.. The maps provide inundation depth information in cm above ground level on a 100 m grid along the major rivers (4150 km) based on 2D hydro-numeric simulations. Flood event sets are derived for the historical period (1970-1990) and two RCPs (4.5 and 8.5) for the near future (2020-2049) and far future (2070-2099) for four CORDEX models. These flood event sets are created within continuous long-term simulations of a coupled model chain including the IMAGE stochastic multi-variable, multi-site weather generator, the eco-hydrological model SWIM and 1D river network coupled with 2D hydro-numeric hinterland inundation model. 10,000 years of continuous daily simulation of meteorological fields are available for each time period, rcp and climate model. The current version of the flood inundation data sets includes 100 years of simulations. 1D model cross section geometries are based on 10m DEM (BKG), adjustment of dike heights in model calibration. 2D hinterland simulation using LISFLOOD-FP inertia model on a 100m grid resampled from 10 m DEM. Key usages of the data are large-scale flood risk assessment, future flood risk assessment and flood risk management with long-term perspective. The data have been produced within the OASIS+ demonstrator project 'Future Danube Multi Hazard and Risk Model' funded by Climate-KIC in the period from January 2016 to December 2017.
Map products (GEOTIFF) • wd_x.tif: Inundation depth map of maximum inundation depth (cm.) for one flood event from the stochastic event set. • wd_max.tif: Raster indicating the maximum water depth of inundation (cm) of each pixel in the simulation of 100 years for one scenario and model. • freq_flood.tif: Inundation frequency map indicating the number of flooding events for each pixel from a within a simulation of 100 years for one scenario and model. Scenario specifications: CMxRCPyTz T0: reference time period (1970-1999) T1: near future (2020 – 2049) T2: far future (2070 – 2099) RCP4.5: representative concentration pathway 4.5 RCP8.5: representative concentration pathway 8.5 CM1: ICHEC_KNMI, ICHEC_EC,EARTH, Irish centre for high end computing, RACMO_22E_v1, Dutch Meteorological Institute (KNMI) ensemble: r1i1p1 CM2: ICHEC_SMHI, ICHEC_EC_EARTH, Irish centre for high end computing, RCA4_v1, Swedish Meteorological Institute (SMHI) ensemble: r12i1p1 CM3: MOHC_SMHI, HadGEM2-ES, Met Office Hadley Centre UK, RCA4_v1, Swedish Meteorological Institute (SMHI) ensemble: r1i1p1 CM4: MPI, MPI-M-MPI-ESM-LR, Max Planck Institute for Meteorology, REMO2009, MPI and CSC (climate service centre) ensemble: r1i1p1
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