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  • 1
    Publication Date: 2020-02-12
    Description: These data are supplementary material to “Bedrock Geology of DFDP-2B, Central Alpine Fault, New Zealand” (Toy et al., 2017, http://doi.org/10.1080/00288306.2017.1375533). The data tables SF3 and SF4 are provided as well as Excel as well as CSV and PDF versions (in the zip folder). The table numbers below are referring to Toy et al. (2017): Toy_SF1.pdf (Data Description): Supplementary Data to “Bedrock Geology of DFDP-2B, Central Alpine Fault, New Zealand”, including supplementary methods, Information on reference frames and corrections, and protocols for thin section preparation and scanning electron microscopic analyses. Toy_SF2: Table S1. Time vs. depth during drilling, with lag dip corrections Toy_SF3: Table S2. Energy dispersive spectroscopy (EDS) data acquired using a TESCAN Integrated Mineral Analyzer (TIMA) and phases detected by mineral liberation analysis (MLA) Toy_SF4: Table S3. Electron backscatter diffraction (EBSD) grain sizes
    Language: English
    Type: info:eu-repo/semantics/workingPaper
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  • 2
    Publication Date: 2023-01-18
    Description: As the negative impacts of hydrological extremes increase in large parts of the world, a better understanding of the drivers of change in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is a lack of comprehensive, empirical data about the processes, interactions and feedbacks in complex human-water systems leading to flood and drought impacts. To fill this gap, we present an IAHS Panta Rhei benchmark dataset containing socio-hydrological data of paired events, i.e. two floods or two droughts that occurred in the same area (Kreibich et al. 2017, 2019). The contained 45 paired events occurred in 42 different study areas (in three study areas we have data on two paired events), which cover different socioeconomic and hydroclimatic contexts across all continents. The dataset is unique in covering floods and droughts, in the number of cases assessed and in the amount of qualitative and quantitative socio-hydrological data contained. References to the data sources are provided in 2022-002_Kreibich-et-al_Key_data_table.xlsx where possible. Based on templates, we collected detailed, review-style reports describing the event characteristics and processes in the case study areas, as well as various semi-quantitative data, categorised into management, hazard, exposure, vulnerability and impacts. Sources of the data were classified as follows: scientific study (peer-reviewed paper and PhD thesis), report (by governments, administrations, NGOs, research organisations, projects), own analysis by authors, based on a database (e.g. official statistics, monitoring data such as weather, discharge data, etc.), newspaper article, and expert judgement. The campaign to collect the information and data on paired events started at the EGU General Assembly in April 2019 in Vienna and was continued with talks promoting the paired event data collection at various conferences. Communication with the Panta Rhei community and other flood and drought experts identified through snowballing techniques was important. Thus, data on paired events were provided by professionals with excellent local knowledge of the events and risk management practices.
    Language: English
    Type: info:eu-repo/semantics/workingPaper
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  • 3
    Publication Date: 2023-06-12
    Description: As the negative impacts of hydrological extremes increase in large parts of the world, a better understanding of the drivers of change in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is a lack of comprehensive, empirical data about the processes, interactions and feedbacks in complex human-water systems leading to flood and drought impacts. To fill this gap, we present an IAHS Panta Rhei benchmark dataset containing socio-hydrological data of paired events, i.e. two floods or two droughts that occurred in the same area (Kreibich et al. 2017, 2019). The contained 45 paired events occurred in 42 different study areas (in three study areas we have data on two paired events), which cover different socioeconomic and hydroclimatic contexts across all continents. The dataset is unique in covering floods and droughts, in the number of cases assessed and in the amount of qualitative and quantitative socio-hydrological data contained. References to the data sources are provided in 2023-001_Kreibich-et-al_Key_data_table.xlsx where possible. Based on templates, we collected detailed, review-style reports describing the event characteristics and processes in the case study areas, as well as various semi-quantitative data, categorised into management, hazard, exposure, vulnerability and impacts. Sources of the data were classified as follows: scientific study (peer-reviewed paper and PhD thesis), report (by governments, administrations, NGOs, research organisations, projects), own analysis by authors, based on a database (e.g. official statistics, monitoring data such as weather, discharge data, etc.), newspaper article, and expert judgement. The campaign to collect the information and data on paired events started at the EGU General Assembly in April 2019 in Vienna and was continued with talks promoting the paired event data collection at various conferences. Communication with the Panta Rhei community and other flood and drought experts identified through snowballing techniques was important. Thus, data on paired events were provided by professionals with excellent local knowledge of the events and risk management practices.
    Language: English
    Type: info:eu-repo/semantics/workingPaper
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  • 4
    Publication Date: 2021-01-28
    Description: 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.
    Language: English
    Type: info:eu-repo/semantics/other
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  • 5
    Publication Date: 2023-01-18
    Description: The Digital Earth Flood Event Explorer supports geoscientists and experts to analyse flood events along the process cascade event generation, evolution and impact across atmospheric, terrestrial, and marine disciplines. It applies the concept of scientific workflows and the component-based Data Analytics Software Framework (DASF, Eggert and Dransch, 2021) to an exemplary showcase. It aims at answering the following geoscientific questions: - How does precipitation change over the course of the 21st century under different climate scenarios over a certain region? - What are the main hydro-meteorological controls of a specific flood event? - What are useful indicators to assess socio-economic flood impacts? - How do flood events impact the marine environment? - What are the best monitoring sites for upcoming flood events? The Flood Event Explorer developed scientific workflows for each geoscientific question providing enhanced analysis methods from statistics, machine learning, and visual data exploration that are implemented in different languages and software environments, and that access data form a variety of distributed databases. The collaborating scientists are from different Helmholtz research centers and belong to different scientific fields such as hydrology, climate-, marine-, and environmental science, and computer- and data science. It is funded by the Initiative and Networking Fund of the Helmholtz Association through the Digital Earth project (https://www.digitalearth-hgf.de/).
    Language: English
    Type: info:eu-repo/semantics/other
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  • 6
    Publication Date: 2021-01-28
    Description: 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.
    Language: English
    Type: info:eu-repo/semantics/other
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  • 7
    Publication Date: 2021-01-28
    Description: 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.
    Language: English
    Type: info:eu-repo/semantics/other
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  • 8
    Publication Date: 2022-01-28
    Description: 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 RPC 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.
    Language: English
    Type: info:eu-repo/semantics/other
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  • 9
    Publication Date: 2023-01-19
    Description: “1-month seismological experiment on Etna, Italy in 2019" is a 1-month seismological experi-ment realized near the Pizzi Deneri Observatory on Etna, Italy, by Eva Eibl and Daniel Vollmer (University of Potsdam) in collaboration with Philippe Jousset from GFZ Potsdam Germany and Gilda Currenti and Graziano Larocca from INGV-OE, Italy. From August to September 2019, we recorded the volcano-seismic events accompanying the volcanic activity using a rotational sensor and a co-located seismometer. The aim of the seismological experiment was to study LP events, VT events and tremor. We used a 3-component broadband seismometer (Nanometrics Trillium Compact 120 s) and a 3-component rotational sensor (iXblue blueSeis-3A) and stored the data on a DataCube and CommunicationCube, respectively. Sensors were installed on the same 35 * 35 * 3 cm3 granitic base plate at about 40 cm depth enclosed by backfilled pyroclastic material to avoid wind noise. The instruments recorded at 200 Hz sampling rate and were located about 2 km from the craters on Etna. The setup was powered using 3 solar panels of 140W each and three batteries of 75Ah each. We oriented the rotational sensor and seismometer using a Quadrans fiber-optical gyrocompass. The Quadrans is not affected by magnetic minerals in the ground and our sensors are hence properly aligned to geographic north. We converted the seismometer data to MSEED using Pyrocko’s Jackseis program and created a catalogs of LP events and VT events that were further investigated in Eibl et al. 2022. Waveform data are available from the GEOFON data centre, under network code ZR.
    Language: English
    Type: info:eu-repo/semantics/workingPaper
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  • 10
    Publication Date: 2021-10-05
    Description: Abstract
    Description: 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).
    Description: Other
    Description: Artificial lights raise the night sky luminance, creating the most visible effect of light pollution, artificial sky glow. Despite the increasing interest among scientists in fields such as ecology, astronomy, healthcare, land use planning, light pollution lacks a current quantification of its magnitude on a global scale. To overcome this, here we present the World atlas of the artificial sky luminance, computed with our light pollution propagation software using new high resolution satellite data and new precision sky brightness measurements. This atlas shows that more than 80% of the World and more than 99% of the U.S.A. and Europe populations live under light polluted skies. The Milky Way is hidden for more than one third of humanity, including 60% of Europeans and nearly 80% of North Americans. Moreover, 23% of World's lands between 75°N and 60°S, 88% of Europe and almost half of U.S.A. experience light polluted nights.
    Keywords: artificial light ; ALAN ; skyglow ; light pollution ; atlas ; night ; radiative transfer ; Suomi NPP ; Sky Quality Meter ; EARTH SCIENCE SERVICES 〉 DATA ANALYSIS AND VISUALIZATION 〉 VISUALIZATION/IMAGE PROCESSING
    Language: English
    Type: Dataset , Dataset
    Format: 26001739 Bytes
    Format: 1 Files
    Format: application/octet-stream
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