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Geo Engine

Geo Engine is a cloud-based service that bundles the integration and efficient processing of spatio-temporal data and intuitively opens up the latest visualization and analysis methods, such as deep learning. This enables companies to unlock previously unused potential.

Geo Engine is an EXIST research transfer project of the Database Research Group of the Philipps University of Marburg. The project uses research results obtained in the projects GFBio and Natur 4.0 in the field of geodata processing, visualization, and deep learning.

Team

• Dr. Christian Beilschmidt
• Dr. Johannes Drönner
• Michael Mattig
• Philip Schweitzer

Mentors

• Prof. Dr. Bernhard Seeger
• Prof. Dr. Jörg Bendix
• Martin Pompéry

Publications and Talks

• Christian Beilschmidt, Johannes Drönner, Nikolaus Glombiewski, Michael Körber, Michael Mattig, Andreas Morgen, Bernhard Seeger:
  VAT to the Future: Extrapolating Visual Complex Event Processing.
  OpenSky 2019: 25-36
• Christian Beilschmidt, Michael Mattig, Thomas Fober, Bernhard Seeger:
  An Efficient Method for Exploratory Data Visualization of Big Spatial Data on Commodity Hardware.
  INFORMATIK 2019
• Christian Beilschmidt, Johannes Drönner, Néstor Fernández, Christian Langer, Michael Mattig, Bernhard Seeger:
  Analyzing Essential Biodiversity Variables with the VAT System.
  Biodiversity Information Science and Standards 3, e36319
• Johannes Drönner, Sebastian Egli, Boris Thies, Jörg Bendix, Bernhard Seeger:
  FFLSD - Fast Fog and Low Stratus Detection tool for large satellite time-series.
  Computers & Geosciences 128: 51-59 (2019)
• Christian Beilschmidt, Michael Mattig, Thomas Fober, Bernhard Seeger:
  An Efficient Aggregation and Overlap Removal Algorithm for Circle Maps.
  GeoInformatica (2019) 23: 473
• Christian Beilschmidt, Johannes Drönner, Nikolaus Glombiewski, Christian Heigele, Jana Holznigenkemper, Anna Isenberg, Michael Körber, Michael Mattig, Andreas Morgen, Bernhard Seeger:
  Pretty Fly for a VAT GUI: Visualizing Event Patterns for Flight Data.
  DEBS 2019: 224-227
• Christian Beilschmidt, Johannes Drönner, Néstor Fernández, Christian Langer, Michael Mattig, Bernhard Seeger:
  Towards an EBV Analyzer based on VAT.
  Proceedings 10th International Conference on Ecological Informatics: 182 (2018)
• Johannes Drönner, Nikolaus Korfhage, Sebastian Egli, Markus Mühling, Boris Thies, Jörg Bendix, Bernd Freisleben, Bernhard Seeger:
  Fast Cloud Segmentation Using Convolutional Neural Networks.
  Remote Sensing 10(11): 1782 (2018)
• Marco Schmidt, Christian Beilschmidt, Johannes Drönner, Michael Mattig, Bernhard Seeger:
  Unter welchen Klimabedingungen wächst meine Pflanze? – Mit dem GFBio-VAT Umweltdaten aus Verbreitungsdaten extrahieren.
  Gärtnerisch-Botanischer Brief 209 (2018): 79-81
• Christian Beilschmidt, Johannes Drönner, Michael Mattig, Marco Schmidt, Christian Authmann, Aidin Niamir, Thomas Hickler, Bernhard Seeger:
  VAT: A Scientific Toolbox for Interactive Geodata Exploration.
  Datenbank-Spektrum 17(3): 233-243 (2017)
• Christian Beilschmidt, Johannes Drönner, Michael Mattig, Marco Schmidt, Christian Authmann, Aidin Niamir, Thomas Hickler, Bernhard Seeger:
  Interactive Data Exploration for Geoscience.
  BTW (Workshops) 2017: 117-126
• Christian Beilschmidt, Johannes Drönner, Michael Mattig, Bernhard Seeger:
  VAT: A System for Data-Driven Biodiversity Research.
  EDBT 2017: 546-549
• Christian Beilschmidt, Thomas Fober, Michael Mattig, Bernhard Seeger:
  A Linear-Time Algorithm for the Aggregation and Visualization of Big Spatial Point Data.
  SIGSPATIAL/GIS 2017: 73:1-73:4
• Christian Beilschmidt, Thomas Fober, Michael Mattig, Bernhard Seeger:
  Quality Measures for Visual Point Clustering in Geospatial Mapping.
  W2GIS 2017: 153-168
• Christian Authmann, Christian Beilschmidt, Johannes Drönner, Michael Mattig, Bernhard Seeger:
  VAT: A System for Visualizing, Analyzing and Transforming Spatial Data in Science.
  Datenbank-Spektrum 15(3): 175-184 (2015)
• Christian Authmann, Christian Beilschmidt, Johannes Drönner, Michael Mattig, Bernhard Seeger:
  Rethinking Spatial Processing in Data-Intensive Science.
  BTW Workshops 2015: 161-170
• Christian Authmann, Christian Beilschmidt, Johannes Drönner, Michael Mattig, Bernhard Seeger:
  Analytical Workflows for Large Data.
  TDWG 2014 Symposium: Biodiversity Informatics workflows and services.