22 documents found in 229ms
# 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
Coesfeld, Jacqueline • Kyba, Christopher
Abstract: This set of Python-code is used to analyse the variation of VIIRS DNB nighttime imagery. The code is inline documented and the readme provides information on what is needed to run the code, and what order to run it in. These routines were used to produce the data and plots in the paper: Variation of Individual Location Radiance in VIIRS Day/Night Band Monthly Composite Images (Coesfeld et al. 2018). Monthly VIIRS DNB data can be downloaded from NOAA: https://ngdc.noaa.gov/eog/viirs/download_dnb_composites.html
Copyright [2018] [Jacqueline Coesfeld, 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 athttp://www.apache.org/licenses/LICENSE-2.0Unless 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.
# 4
Unger, Andrea • Rabe, Daniela • Klemann, Volker • Eggert, Daniel • Dransch, Doris
Abstract: The validation of a simulation model is a crucial task in model development. It involves the comparison of simulation data to observation data and the identification of suitable model parameters. SLIVISU is a Visual Analytics framework that enables geoscientists to perform these tasks for observation data that is sparse and uncertain. Primarily, SLIVISU was designed to evaluate sea level indicators, which are geological or archaeological samples supporting the reconstruction of former sea level over the last ten thousands of years and are compiled in a postgreSQL database system. At the same time, the software aims at supporting the validation of numerical sea-level reconstructions against this data by means of visual analytics.
# 5
Unger, Andrea • Rabe, Daniela • Eggert, Daniel • Dransch, Doris
Abstract: Geoarchives are an important source to understand the interplay of climate and landscape developments in the past. One important example are sediment cores from the ground of lakes. The microfacies-explorer is a Java-based prototype, that provides a tailored combination of visual and data mining methods enabling scientists to explore categorical data from geoarchives.
# 6
Sips, Mike • Dransch, Doris • Eggert, Daniel • Freytag, Johann-Christoph • Hollstein, Andre • (et. al.)
Abstract: GeoMultiSens developed an integrated processing pipeline to support the analysis of homogenized data from various remote sensing archives. The processing pipeline has five main components: (1) visual assessment of remote sensing Earth observations, (2) homogenization of selected Earth observation, (3) efficient data management with XtreemFS, (4) Python-based parallel processing and analysis algorithms implemented in a Flink cloud environment, and (5) visual exploration of the results. GeoMultiSens currently supports the classification of land-cover for Europe.
# 7
Eggert, Daniel • Sips, Mike • Dransch, Doris
Abstract: gms-vis is a web-based implementation of our visual-analytics approach for assessing remote-sensing data. It is implemented based on the GWT framework. Once deployed through a webserver it acts as the user interface for the GeoMultiSens (GMS) platform. Within the interface users can intuitively define spatial, temporal as well as quality constraints, for remote sensing scenes. A heatmap enables the user to assess the spatial distribution of selected scenes, while a time histogram allows the user to assess their temporal distribution. Finally, users can specify a workflow which will be executed by the GeoMultiSens platform. Though gms-vis is part of the GeoMultiSens platform, it is relatively self-contained and can be attached to different analysis frameworks and platforms with reasonable effort.
# 8
Eggert, Daniel • Sips, Mike • Dransch, Doris
Abstract: Gms-index-mediator is a standalone index for spatio-temporal data acting as a mediator between an application and a database. Even modern databases need several minutes to execute a spatio-temporal query to huge tables containing several million entries. Our index-mediator speeds the execution of such queries up by several magnitues, resulting in response times around 100ms. This version is tailored towards the GeoMultiSens database, but can be adapted to work with custom table layouts with reasonable effort.
# 9
Radosavljevic, Boris
Abstract: This publication contains tools for statistical evaluation and exploration of data published by Radosavljevic et al. (2016). These data contain bulk geochemistry data (total organic carbon, nitrogen, stable carbon isotope) and granulometry of nearshore samples in the vicinity of Herschel Island, Yukon, Canadian Beaufort Sea. In addition, the functions of the script herein provide a means for summaries and comparison with terrestrial (Couture, 2010; Tanski et al., 2017; Obu et al., 2016) and marine (a subset of Naidu et al., 2000) data. The tools are contained in a script written for the R software environment for statistical computing and graphics. The script (sediments_geochemistry_plots_and_summaries.r) is richly documented and explains the functionality. Each data file also contains a description of the data in a comma separated file (csv).The functions of the script are:myinteract() - interactive modemysum() - provides numerical summaries for WBP and TB, a box plot and runs a Two-sided Mann-Whitney-Wilcoxon testmyloc() - provides numerical summaries and comparisons among the current study, marine, and terrestrial samples, a box plot and runs a Two-sided Mann-Whitney-Wilcoxon testmyseds() - provides numerical summaries and comparisons of grain size data among the current studymycums() - plots cumulative frequency curves of grain size distributions by transectThe package contains (included in the zip folder):sediments_geochemistry_plots_and_summaries.r - script filegeochemistry_data_including_other_studies.csv - contains data by Radosavljevic et al. (2016) and other studies in the regionVolFrequenciesCoordsTransects.csv - contains volumetric grain size frequenciesgranulometry_stats.csv - contains summary statistics of grain size dataTransectSampleIndex.csv - provides an index of transectsTransectMap.png - an overview map of sample transects
# 10
Eggert, Daniel • Köthur, Patrick • Dransch, Doris
Abstract: The processing of Persistent Scatterer Interferometry (PSI) data and the estimation of displacement is a nonlinear and user-driven procedure that can introduce large errors for noisy backscatter points. Results may differ significantly depending on chosen thresholds, filter settings, constraints and final interpretation. Thus the identification of valid PS with rather low errors in the SAR data is a crucial step in the PSI workflow. PSI-Explorer is a scientific prototype of our visual-analytics (VA) approach supporting this important task. The prototype is written in Java and operates on Matlab files.
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