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Supplement to: The New World Atlas of Artificial Night Sky Brightness

These are maps of artificial night sky radiance that were produced by the Light Pollution Science and Technology Institute (ISTIL), and described in the paper "The New World Atlas of Artificial Night Sky Brightness" (Falchi et al. 2016).The data are stored in a 2.9 Gb geotiff file, on a 30 arcsecond grid. The map reports simulated zenith radiance data in [mcd/m^2]. The map is based on data from the VIIRS Day Night Band (DNB, MIller et al. 2013), which has been propagated through the atmosphere using the radiative transfer code reported in (Cinzano and Falchi, 2012). The upward emission function and the radiance calibration were obtained using data from Sky Quality Meters (including data from Duriscoe et al. 2007; Falchi 2010; Kyba et al 2013, 2015 and Zamorano et al. 2016).Note that the maps report artificial light only! The zenith radiance from natural sources such as stars and the Milky Way are not included, and must be added in order to match the data that would be obtained from an actual outdoor measurement.A kmz file for quick view of the data is also provided. Access to the FTP site to download the data can be requested via the data request form on the landing page.Version History:13 November 2019: change of the licence to CC BY NC 4.0 (after end of embargo period).

Supplement to: Smart speed imaging in Digital Image Correlation: Application to Seismotectonic Scale Modelling

The presented datasets and scripts have been obtained for testing the performance of a trigger algorithm for use in combination with a ringshear tester ‘RST-01.pc’. Glass beads (fused quartz microbeads, 300-400 µm diameter) and thai rice are sheared at varying velocity, stiffness and normal load. The data is provided as preprocessed mat-files ('*.mat') to be opened with Matlab R2015a and later. Several scripts are provided to reproduce the figures found in (Rudolf et al., submitted). A detailed list of files together with the respective software needed to view and execute them is available in 'List_of_Files_Rudolf-et-al-2018.pdf' (also available in MS Excel Format). More information on the datasets and a small documentation of the scripts is given in 'Explanations_Rudolf-et-al-2018.pdf'. The complete data publication, including all descriptions, datasets, and evaluation scripts is available as 'Dataset_Rudolf-et-al-2018.zip'.

PISM simulation results of the Antarctic Ice Sheet deglaciation

This dataset contains PISM simulation results (http://www.pism-docs.org) of the Antarctic Ice Sheet based on code release pik-holocene-gl-rebound: http://doi.org/10.5281/zenodo.1199066 .With the help of added python scripts, Fig. 3 and other model related extended data figures can be reproduced as in the journal publication: Kingslake, Scherer, Albrecht et al. (2018, http://dx.doi.org/10.1038/s41586-018-0208-x).

DASF: Web: Web components for the data analytics software framework

DASF: Web is part of the Data Analytics Software Framework (DASF, https://git.geomar.de/digital-earth/dasf), developed at the GFZ German Research Centre for Geosciences (https://www.gfz-potsdam.de). It is funded by the Initiative and Networking Fund of the Helmholtz Association through the Digital Earth project (https://www.digitalearth-hgf.de/). DASF: Web collects all web components for the data analytics software framework DASF. It provides ready to use interactive data visualization components like time series charts, radar plots, stacked-parameter-relation (spr) and more, as well as a powerful map component for the visualization of spatio-temporal data. Moreover dasf-web includes the web bindings for the DASF RCP messaging protocol and therefore allows to connect any algorithm or method (e.g. via the dasf-messaging-python implementation) to the included data visualization components. Because of the component based architecture the integrated method could be deployed anywhere (e.g. close to the data it is processing), while the interactive data visualizations are executed on the local machine. dasf-web is implemented in Typescript and uses Vuejs/Vuetify, Openlayers and D3 as a technical basis.

Seismological Monitoring using Interferometric Concepts (SeisMIC)

Monitoring Velocity Changes using Ambient Seismic Noise SeisMIC (Seismological Monitoring using Interferometric Concepts) is a python software that emerged from the miic library. SeisMIC provides functionality to apply some concepts of seismic interferometry to different data of elastic waves. Its main use case is the monitoring of temporal changes in a mediums Green's Function (i.e., monitoring of temporal velocity changes). SeisMIC will handle the whole workflow to create velocity-change time-series including: Downloading raw data, Adaptable preprocessing of the waveform data, Computating cross- and/or autocorrelation, Plotting tools for correlations, Database management of ambient seismic noise correlations, Adaptable postprocessing of correlations, Computation of velocity change (dv/v) time series, postprocessing of dv/v time series, plotting of dv/v time-series

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