Towards Storytelling with Animated Pictorial Map Objects – An Experiment with Convolutional Neural Networks

Schnürer, Raimund; Öztireli, Cengiz; Sieber, René; Hurni, Lorenz

doi:https://doi.org/10.5194/ica-abs-1-324-2019

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Articles | Volume 1

https://doi.org/10.5194/ica-abs-1-324-2019

Articles | Volume 1

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15 Jul 2019

| 15 Jul 2019

Towards Storytelling with Animated Pictorial Map Objects – An Experiment with Convolutional Neural Networks

Raimund Schnürer, Cengiz Öztireli, René Sieber, and Lorenz Hurni

Raimund Schnürer

https://orcid.org/0000-0002-7558-3621

Institute of Cartography and Geoinformation, ETH Zurich, Switzerland

Cengiz Öztireli

Computer Graphics Laboratory, ETH Zurich, Switzerland

René Sieber

Institute of Cartography and Geoinformation, ETH Zurich, Switzerland

Lorenz Hurni

https://orcid.org/0000-0002-0453-8743

Institute of Cartography and Geoinformation, ETH Zurich, Switzerland

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Short summary

This paper introduces a methodology to support network managers in the quantification of the risk related to their networks. The method emphasizes the integration of the spatial and temporal attributes of the events that need to be modeled to estimate the risk. This work then demonstrates the usefulness of the methodology through its application to design and implement a risk assessment to estimate the potential impact of flood and mudflow events on a road network located in Switzerland.

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