Universitätssiegel
Julian Hangenauer

Dr. Julian Hagenauer

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Forschungsinteressen

  • Data Mining
  • Machine Learning/Neural Networks
  • Agent-based Modeling
  • Optimization

Publikationen

International Peer-Reviewed Journals

Hagenauer, J. and Helbich, M. (2013). Hierarchical self-organizing maps for clustering spatio-temporal data. International Journal of Geographical Information Science (in press). [pdf (preprint)] [Journal link]

Hagenauer, J. and Helbich, M. (2013). Contextual neural gas for spatial clustering and analysis. International Journal of Geographical Information Science, 27(2):251–266. [pdf (preprint)] [Journal link]

Helbich, M., Brunauer, W., Hagenauer, J., and Leitner, M. (2013). Data-driven regionalization of housing markets. Annals of the Association of American Geographers. [Journal link]

Hagenauer, J. and Helbich, M. (2012). Mining urban land-use patterns from volunteered geographic information by means of genetic algorithms and artificial neural networks. International Journal of Geographical Information Science, 26(6):963–982. [docx (preprint)] [Journal link]

Höfle, B., Hollaus, M., and Hagenauer, J. (2012). Urban vegetation detection using radiometrically calibrated small-footprint full-waveform airborne lidar data. ISPRS Journal of Photogrammetry and Remote Sensing, 67:134–147. [Journal link]

Helbich, M., Hagenauer, J., and Leitner, M. (2011). Raum-zeitliche Analyse von Verbrechens-Hotspots mittels Trajektorien und Kohonen-Karten. Mitteilungen der Österreichischen Geographischen Gesellschaft, Jahresband 153:291–304. [Journal link]

Conference Proceedings

Hagenauer, J., Helbich, M., Leitner, M., Ratcliffe, J., Chainey, S., and Edwards, R. (2012). Data mining of collaboratively collected geographic crime information using an unsupervised neural network approach. In Proceedings of AutoCarto 2012, Columbus, OH. [pdf]

Hagenauer, J. and Helbich, M. (2011). Abgrenzung urbaner Räume mittels OpenStreetMap und maschinellen Lernverfahren. In Schilcher, M., editor, Geoinformationssysteme. Beiträge zum 16. Münchner Fortbildungsseminar, pages 78–81, Heidelberg, Germany. Abcverlag.

Hagenauer, J., Helbich, M., and Leitner, M. (2011). Visualization of crime trajectories with self-organizing maps: A case study on evaluating the impact of hurricanes on spatiotemporal crime hotspots. In 25th International Cartographic Conference, Paris, France. [pdf]

Helbich, M., Hagenauer, J., and Leitner, M. (2011). Visualisierung von Verbrechensmustern in Houston mit Methoden des Data Minings. In Theorie und quantitative Methoden in der Geographie – Kolloqiumsbeiträge, volume 19, pages 79–83, Heidelberg, Germany. Geographisches Institut.

Roick, O., Hagenauer, J., and Zipf, A. (2011). OSMatrix – grid-based analysis and visualization of OpenStreetMap. In Proceedings of the 1st European State of the Map, Vienna, Austria. [pdf]

Poster

Hagenauer, J. and Zipf, A. (2010). Generating focus maps using open standards. 6th International Conference GIScience 2010, Zürich, Switzerland.

Helbich, M. and Hagenauer, J. (2010). Mining urban land-use patterns from volunteered geographic information using genetic algorithms and artificial neural networks. Introduction of the Doctoral College GIScience (University of Salzburg) at the Austrian Science Fund, Vienna, Austria.

Downloads

The SPAWNN suite for clustering and analyzing spatial data with (self-organizing) neural networks can be found here.
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Letzte Änderung: 23.02.2017
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