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  • 1
    Call number: S 99.0139(337)
    In: Wissenschaftliche Arbeiten der Fachrichtung Geodäsie und Geoinformatik der Leibniz Universität Hannover, Nr. 337
    Type of Medium: Series available for loan
    Pages: 151 Seiten , Illustrationen, Diagramme
    ISSN: 0174-1454
    Series Statement: Wissenschaftliche Arbeiten der Fachrichtung Geodäsie und Geoinformatik der Leibniz Universität Hannover Nr. 337
    Language: German
    Note: Dissertation, Gottfried Wilhelm Leibniz Universität Hannover, 2017 , Inhaltsverzeichnis 1 Einleitung 1.1 Zielsetzung 1.2 Struktur 2 Grundlagen und Stand der Forschung 2.1 Mobile Mapping Systeme 2.1.1 Allgemeine Funktionsweise 2.1.2 Riegl VMX-250 2.1.3 Alternative Systeme 2.2 Punktwolken 2.2.1 Definition 2.2.2 Abgrenzung zu vermaschten Punkten 2.2.3 Speicherformate von Punktwolken 2.2.4 Visualisierungstechniken 2.2.5 Level Of Detail 2.3 Farbmodelle 2.3.1 Farbanpassung 2.4 Verteiltes Rechnen 2.5 Verdeckungsanalyse 2.6 Registrierung mehrerer Datensätze 2.7 Visualisierungssysteme 2.7.1 Standalone Point Cloud Viewer 2.7.2 Webbasierte Systeme 3 Effizienzbetrachtungen 3.1 Effiziente Verarbeitung von Massendaten durch Parallelisierung 3.1.1 Parallelisierungsformen 3.1.2 Umsetzung 3.1.3 Vergleich 3.2 Effiziente Datenstrukturen 3.2.1 Scanstreifen 3.2.2 Scanstreifenbasierte Pufferstrategie 3.2.3 Rasterdatenstruktur 3.2.4 Randproblematik und Caching 4 Modulare Verarbeitungskette f ̈ur Mobile Mapping Daten 4.1 Analyse der beteiligten Komponenten des Herstellerworkflows 4.2 Exemplarische modulare Verarbeitungskette 4.3 Vorverarbeitungsmodul 4.3.1 Vereinfachung 4.3.2 Zeitsegmentierung 4.3.3 Bestimmung von Punktattributen 4.4 Segmentierung und Klassifikation 4.4.1 Bodenextraktion 4.4.2 Objektsegmentierung 5 Sensordatenintegration: Kalibrierung der Kameraorientierung 5.1 Zeitstempelabweichung 5.2 Ansatz 5.3 Extraktion von Silhouetten 5.3.1 Extraktion von Silhouetten aus Kamerabildern 5.3.2 Extraktion von Silhouetten aus Laserscandaten 5.4 ICP-basierte Identifikation der Korrespondenzen 5.4.1 Beschränkung der Scanpunktbildsilhouette 5.4.2 Gruppierung der Scanpunktdaten 5.4.3 ICP unter Berücksichtigung der Punktnormalen 5.5 Bestimmung der Kameraparameter mittels Rückwärtsschnitt 5.5.1 Wahl der Stichprobe 5.5.2 Anzahl an Iterationen 5.5.3 Bewertung der gefundenen Modelle 5.6 Ergebnisse 5.7 Verbesserungspotential und Probleme 5.7.1 Laufzeiten 5.7.2 Robustheit des Verfahrens und Qualität der Ergebnisse 6 Farbbestimmung 6.1 Farbextraktion 6.2 Verdeckungsanalyse 6.2.1 Geometrische Verdeckungsanalyse 6.2.2 Ballbasierter Tiefenpuffer 6.2.3 Ergebnisse 6.2.4 Nicht erfasste und dynamische Objekte 6.3 Farbanpassung 6.3.1 Einfärbesituationen benachbarter Scanpunkte 6.3.2 Objektweise Farbanpassung 6.3.3 IDP-Interpolierte radiometrische Helligkeitsanpassung von Bodenpunkten 6.3.4 Radiometrische Helligkeits- und Sättigungsanpassung von Objektpunkten 6.4 Farbsynthese 6.4.1 Histogrammbasierte Farbinterpolation 6.4.2 Ergebnis 7 Aus Punktwolken abgeleitete Modelle 7.1 3D Modelle 7.1.1 Identifikation planarer Bereiche 7.1.2 Nachbearbeitung der erstellten Texturen 7.1.3 Effiziente Verwaltung von Texturen 7.1.4 Erhöhung der Speichereffizienz 7.1.5 Level of Detail 7.2 2D Modelle 7.2.1 Trackjektorienabschnitte 7.2.2 Ermittlung relevanter Ebenen 7.2.3 Ergebnis 8 Visualisierung von Mobile Mapping Daten 8.1 3D Visualisierung 8.1.1 Visualisierung via Web-App 8.1.2 Performante Client-Server Kommunikation und Serialisierung 8.1.3 Scheduling der LOD-Daten 8.1.4 GUI Responsiveness 8.1.5 Navigation und Nutzerinteraktion 8.2 2D Visualisierung 8.2.1 Parallax Scrolling Visualisierung via Android-App 8.2.2 Beleuchtungsmodell 8.2.3 Ergebnis und Ausblick 9 Schlussfolgerungen und Ausblick 9.1 Ausblick Literaturverzeichnis
    Location: Lower compact magazine
    Branch Library: GFZ Library
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  • 2
    Publication Date: 2022-07-23
    Description: This open access book presents the results of three years collaboration between earth scientists and data scientists, in developing and applying data science methods for scientific discovery. The book will be highly beneficial for other researchers at senior and graduate level, interested in applying visual data exploration, computational approaches and scientifc workflows.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Book , NonPeerReviewed
    Format: application/pdf
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  • 3
    Publication Date: 2023-06-21
    Description: Modern digital scientific workflows - often implying Big Data challenges - require data infrastructures and innovative data science methods across disciplines and technologies. Diverse activities within and outside HGF deal with these challenges, on all levels. The series of Data Science Symposia fosters knowledge exchange and collaboration in the Earth and Environment research community. We invited contributions to the overarching topics of data management, data science and data infrastructures. The series of Data Science Symposia is a joint initiative by the three Helmholtz Centers HZG, AWI and GEOMAR Organization: Hela Mehrtens and Daniela Henkel (GEOMAR)
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
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  • 4
    Publication Date: 2023-12-22
    Description: Der Anteil erneuerbarer Energien bei der Wärme- (und Kälte-)Versorgung lag 2021 in Deutschland bei 16,5 % (knapp 200 TWh/a). Davon stammten 86 % aus Biomasse und davon wiederum 47% allein aus Holzfeuerungen im häuslichen Bereich. Der Rest der erneuerbaren Wärme stammte aus oberflächennaher Geothermie und Umgebungswärme (Wärmepumpen) mit 9 % und Solarthermie mit 4,2 %. Bisher vergleichsweise kleine Beiträge stammten aus der tiefen Geothermie. Im Jahr 2021 waren bezogen auf die rund 21 Millionen im Bestand befindlichen Einzelgebäudeheizanlagen (nicht Einzelraumfeuerstätten) 1,1 Mio. Wärmepumpen und 0,9 Mio. Biomassekessel im Betrieb. Hinzu kommen zusätzliche 2,5 Mio. solarthermische Anlagen mit einer Gesamtkollektorfläche von rund 21 Mio. m2. Bei den neu installierten Wärmeerzeugern konnten Wärmepumpen und Biomassekessel auch 2021 einen deutlich steigenden Absatz verzeichnen, wobei ihr Anteil an den insgesamt rund 930.000 neu installierten Wärmerzeugern bei knapp 25% lag. Doch 2021 nutzten immer noch rund 19 Mio. Wärmeerzeuger Gas und Öl. Darüber hinaus müssen in Wohngebäuden auch noch Etagenheizungen und veraltete Biomasseheizsysteme ausgetauscht werden. Für eine erfolgreiche Wärmewende bis 2045 im Gebäudewärmebereich müssen also weiterhin jedes Jahr rund eine Million neue komplett Erneuerbare-Heizanlagen installiert und in Betrieb genommen werden. Nach dem Anschluss an zumindest perspektivisch vollständig erneuerbar versorgte Wärmenetze sind für alle anderen Objekte Wärmepumpen, Wärmepumpen-Biomasse-Hybride und, nur wo es keine anderen Möglichkeiten gibt, reine Biomassekessel zu installieren. Alle Lösungen lassen sich zusätzlich mit Solarthermieanlagen ergänzen. Im Vergleich zu Erdgasthermen ist jedoch allein die Installation der deutlich komplexeren Systeme mit mindestens dem doppelten Zeitaufwand zu veranschlagen, während die Branche bereits heute über einen realen Fachkräftemangel klagt. Es braucht also wirksame Lösungsansätze der Forschung zur Überwindung dieser und vieler anderer Hemmnisse zur erfolgreichen Wärmewende bis 2045.
    Keywords: ddc:600
    Repository Name: Wuppertal Institut für Klima, Umwelt, Energie
    Language: German
    Type: conferenceobject , doc-type:conferenceObject
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  • 5
    Publication Date: 2021-08-03
    Description: Abstract
    Description: SEVA is a scalable exploration tool that supports users to conduct change detection based on optical Sentinel-2 satellite observations. It supports the following essential steps of change detection: a) exploration and selection of optical satellite images to recognize proper data for the current application scenario, b) automated extraction of changes from the optical satellite images, c) analysis of errors and d) assessment and interpretation of the extracted changes.
    Description: TechnicalInfo
    Description: License: GNU General Public License, Version 3, 29 June 2007 Copyright © 2020 Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Potsdam, Germany SEVA is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. SEVA is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.
    Keywords: remote sensing ; satellite data ; visualilsation ; change detection ; EARTH SCIENCE SERVICES 〉 DATA ANALYSIS AND VISUALIZATION ; EARTH SCIENCE SERVICES 〉 DATA ANALYSIS AND VISUALIZATION 〉 GEOGRAPHIC INFORMATION SYSTEMS 〉 WEB-BASED GEOGRAPHIC INFORMATION SYSTEMS
    Type: Software , Software
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  • 6
    Publication Date: 2016-10-05
    Print ISSN: 1618-2162
    Electronic ISSN: 1610-1995
    Topics: Computer Science
    Published by Springer
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  • 7
    Publication Date: 2020-04-17
    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.
    Type: Software , NonPeerReviewed
    Format: text
    Format: archive
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  • 8
    Publication Date: 2022-02-01
    Description: Abstract
    Description: The River Plume Workflow is part of the Flood Event Explorer (FEE, Eggert et al., 2022), developed at the GFZ German Research Centre for Geosciences in close collaboration with Helmholtz-Zentrum Hereon. It is funded by the Initiative and Networking Fund of the Helmholtz Association through the Digital Earth project (https://www.digitalearth-hgf.de/). The focus of the River Plume Workflow is the impact of riverine flood events on the marine environment. At the end of a flood event chain, an unusual amount of nutrients and pollutants is washed into the North Sea, which can have consequences, such as increased algae blooms. The workflow aims to enable users to detect a river plume in the North Sea and to determine its spatio-temporal extent. Identifying river plume candidates can either happen manually in the visual interface or also through an automatic anomaly detection algorithm, using Gaussian regression. In both cases a combination of observational data, namely FerryBox transects and satellite data, and model data are used. Once a river plume candidate is found, a statistical analysis supplies additional detail on the anomaly and helps to compare the suspected river plume to the surrounding data. Simulated trajectories of particles starting on the FerryBox transect at the time of the original observation and modelled backwards and forwards in time help to verify the origin of the river plume and allow users to follow the anomaly across the North Sea. An interactive map enables users to load additional observational data into the workflow, such as ocean colour satellite maps, and provides them with an overview of the flood impacts and the river plume’s development on its way through the North Sea. In addition, the workflow offers the functionality to assemble satellite-based chlorophyll observations along model trajectories as a time series. They allow scientists to understand processes inside the river plume and to determine the timescales on which these developments happen. For example, chlorophyll degradation rates in the Elbe river plume are currently investigated using these time series. The workflow's added value lies in the ease with which users can combine observational FerryBox data with relevant model data and other datasets of their choice. Furthermore, the workflow allows users to visually explore the combined data and contains methods to find and highlight anomalies. The workflow’s functionalities also enable users to map the spatio-temporal extent of the river plume and investigate the changes in productivity that occur in the plume. All in all, the River Plume Workflow simplifies the investigation and monitoring of flood events and their impacts in marine environments.
    Description: TechnicalInfo
    Description: Copyright 2022 Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Potsdam, Germany / DE Flood Event Explorer Licensed under the Apache License, Version 2.0 (the "License"); you may not use these files except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless 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.
    Keywords: Digital Earth ; Flood ; DASF ; Workflow ; river plume ; ferrybox ; impact ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 FLOODS ; EARTH SCIENCE SERVICES 〉 DATA ANALYSIS AND VISUALIZATION
    Type: Software , Software
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  • 9
    Publication Date: 2022-02-01
    Description: Abstract
    Description: The Socio-Economic Flood Impacts Workflow is part of the Flood Event Explorer (FEE, Eggert et al., 2022), developed at the GFZ German Research Centre for Geosciences . It is funded by the Initiative and Networking Fund of the Helmholtz Association through the Digital Earth project (https://www.digitalearth-hgf.de/). The Socio-Economic Flood Impacts Workflow aims to support the identification of relevant controls and useful indicators for the assessment of flood impacts. It should support answering the question What are useful indicators to assess socio-economic flood impacts?. Floods impact individuals and communities and may have significant social, economic and environmental consequences. These impacts result from the interplay of hazard - the meteo-hydrological processes leading to high water levels and inundation of usually dry land, exposure - the elements affected by flooding such as people, build environment or infrastructure, and vulnerability - the susceptibility of exposed elements to be harmed by flooding. In view of the complex interactions of hazard and impact processes a broad range of data from disparate sources need to be compiled and analysed across the boundaries of climate and atmosphere, catchment and river network, and socio-economic domains. The workflow approaches this problem and supports scientists to integrate observations, model outputs and other datasets for further analysis in the region of interest. The workflow provides functionalities to select the region of interest, access hazard, exposure and vulnerability related data from different sources, identifying flood periods as relevant time ranges, and calculate defined indices. The integrated input data set is further filtered for the relevant flood event periods in the region of interest to obtain a new comprehensive flood data set. This spatio-temporal dataset is analysed using data-science methods such as clustering, classification or correlation algorithms to explore and identify useful indicators for flood impacts. For instance, the importance of different factors or the interrelationships among multiple variables to shape flood impacts can be explored. The added value of the Socio-Economic Flood Impacts Workflow is twofold. First, it integrates scattered data from disparate sources and makes it accessible for further analysis. As such, the effort to compile, harmonize and combine a broad range of spatio-temporal data is clearly reduced. Also, the integration of new datasets from additional sources is much more straightforward. Second, it enables a flexible analysis of multivariate data and by reusing algorithms from other workflows it fosters a more efficient scientific work that can focus on data analysis instead of tedious data wrangling.
    Description: TechnicalInfo
    Description: Copyright 2022 Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Potsdam, Germany / DE Flood Event Explorer Licensed under the Apache License, Version 2.0 (the "License"); you may not use these files except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless 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.
    Keywords: Digital Earth ; Flood ; DASF ; Workflow ; hydrometeorological controls ; indicators ; impact assessment ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 FLOODS ; EARTH SCIENCE SERVICES 〉 DATA ANALYSIS AND VISUALIZATION
    Type: Software , Software
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  • 10
    Publication Date: 2022-02-01
    Description: Abstract
    Description: The Flood Similarity Workflow is part of the Flood Event Explorer (FEE, Eggert et al., 2022), developed at the GFZ German Research Centre for Geosciences . It is funded by the Initiative and Networking Fund of the Helmholtz Association through the Digital Earth project (https://www.digitalearth-hgf.de/). River floods and associated adverse consequences are caused by complex interactions of hydro-meteorological and socio-economic pre-conditions and event characteristics. The Flood Similarity Workflow supports the identification, assessment and comparison of hydro-meteorological controls of flood events. The analysis of flood events requires the exploration of discharge time series data for hundreds of gauging stations and their auxiliary data. Data availability and accessibility and standard processing techniques are common challenges in that application and addressed by this workflow. The Flood Similarity Workflow allows the assessment and comparison of arbitrary flood events. The workflow includes around 500 gauging stations in Germany comprising discharge data and the associated extreme value statistics as well as precipitation and soil moisture data. This provides the basis to identify and compare flood events based on antecedent catchment conditions, catchment precipitation, discharge hydrographs, and inundation maps. The workflow also enables the analysis of multidimensional flood characteristics including aggregated indicators (in space and time), spatial patterns and time series signatures. The added value of the Flood Event Explorer comprises two major points. First, scientist work on a common, homogenized database of flood events and their hydro-meteorological controls for a large spatial and temporal domain , with fast and standardized interfaces to access the data. Second, the standardized computation of common flood indicators allows a consistent comparison and exploration of flood events.
    Description: TechnicalInfo
    Description: Copyright 2022 Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Potsdam, Germany / DE Flood Event Explorer Licensed under the Apache License, Version 2.0 (the "License"); you may not use these files except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless 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.
    Keywords: Digital Earth ; Flood ; DASF ; Workflow ; hydrometeorological controls ; compare ; assess ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 FLOODS ; EARTH SCIENCE SERVICES 〉 DATA ANALYSIS AND VISUALIZATION
    Type: Software , Software
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