5 Search Results for "Jonietz, David"

Document
DOI: 10.4230/DagRep.12.4.26
Urban Mobility Analytics (Dagstuhl Seminar 22162)

Authors: David Jonietz, Monika Sester, Kathleen Stewart, Stephan Winter, Martin Tomko, and Yanan Xin

Published in: Dagstuhl Reports, Volume 12, Issue 4 (2022)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 22162 "Urban Mobility Analytics". The seminar brought together researchers from academia and industry who work in complementary ways on urban mobility analytics. The seminar especially aimed at bringing together ideas and approaches from deep learning research, which is requiring large datasets, and reproducible research, which is requiring access to data.
Cite as

David Jonietz, Monika Sester, Kathleen Stewart, Stephan Winter, Martin Tomko, and Yanan Xin. Urban Mobility Analytics (Dagstuhl Seminar 22162). In Dagstuhl Reports, Volume 12, Issue 4, pp. 26-53, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@Article{jonietz_et_al:DagRep.12.4.26,
  author =	{Jonietz, David and Sester, Monika and Stewart, Kathleen and Winter, Stephan and Tomko, Martin and Xin, Yanan},
  title =	{{Urban Mobility Analytics (Dagstuhl Seminar 22162)}},
  pages =	{26--53},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2022},
  volume =	{12},
  number =	{4},
  editor =	{Jonietz, David and Sester, Monika and Stewart, Kathleen and Winter, Stephan and Tomko, Martin and Xin, Yanan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.12.4.26},
  URN =		{urn:nbn:de:0030-drops-172792},
  doi =		{10.4230/DagRep.12.4.26},
  annote =	{Keywords: data analytics, Deep learning, Reproducible research, urban mobility}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2021.I.2
Estimation of Moran’s I in the Context of Uncertain Mobile Sensor Measurements

Authors: Dominik Bucher, Henry Martin, David Jonietz, Martin Raubal, and René Westerholt

Published in: LIPIcs, Volume 177, 11th International Conference on Geographic Information Science (GIScience 2021) - Part I (2020)

Abstract
Measures of spatial autocorrelation like Moran’s I do not take into account information about the reliability of observations. In a context of mobile sensors, however, this is an important aspect to consider. Mobile sensors record data asynchronously and capture different contexts, which leads to considerable heterogeneity. In this paper we propose two different ways to integrate the reliability of observations with Moran’s I. These proposals are tested in the light of two case studies, one based on real temperatures and movement data and the other using synthetic data. The results show that the way reliability information is incorporated into the Moran’s I estimates has a strong impact on how the measure responds to volatile available information. It is shown that absolute reliability information is much less powerful in addressing the problem of differing contexts than relative concepts that give more weight to more reliable observations, regardless of the general degree of uncertainty. The results presented are seen as an important stimulus for the discourse on spatial autocorrelation measures in the light of uncertainties.
Cite as

Dominik Bucher, Henry Martin, David Jonietz, Martin Raubal, and René Westerholt. Estimation of Moran’s I in the Context of Uncertain Mobile Sensor Measurements. In 11th International Conference on Geographic Information Science (GIScience 2021) - Part I. Leibniz International Proceedings in Informatics (LIPIcs), Volume 177, pp. 2:1-2:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{bucher_et_al:LIPIcs.GIScience.2021.I.2,
  author =	{Bucher, Dominik and Martin, Henry and Jonietz, David and Raubal, Martin and Westerholt, Ren\'{e}},
  title =	{{Estimation of Moran’s I in the Context of Uncertain Mobile Sensor Measurements}},
  booktitle =	{11th International Conference on Geographic Information Science (GIScience 2021) - Part I},
  pages =	{2:1--2:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-166-5},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{177},
  editor =	{Janowicz, Krzysztof and Verstegen, Judith A.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2021.I.2},
  URN =		{urn:nbn:de:0030-drops-130375},
  doi =		{10.4230/LIPIcs.GIScience.2021.I.2},
  annote =	{Keywords: mobile sensors, Moran’s I, uncertainty, probabilistic forecasting}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.COSIT.2019.27
Towards Modeling Geographical Processes with Generative Adversarial Networks (GANs) (Short Paper)

Authors: David Jonietz and Michael Kopp

Published in: LIPIcs, Volume 142, 14th International Conference on Spatial Information Theory (COSIT 2019)

Abstract
Recently, Generative Adversarial Networks (GANs) have demonstrated great potential for a range of Machine Learning tasks, including synthetic video generation, but have so far not been applied to the domain of modeling geographical processes. In this study, we align these two problems and - motivated by the potential advantages of GANs compared to traditional geosimulation methods - test the capability of GANs to learn a set of underlying rules which determine a geographical process. For this purpose, we turn to Conway’s well-known Game of Life (GoL) as a source for spatio-temporal training data, and further argue for its (and simple variants of it) usefulness as a potential standard training data set for benchmarking generative geographical process models.
Cite as

David Jonietz and Michael Kopp. Towards Modeling Geographical Processes with Generative Adversarial Networks (GANs) (Short Paper). In 14th International Conference on Spatial Information Theory (COSIT 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 142, pp. 27:1-27:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{jonietz_et_al:LIPIcs.COSIT.2019.27,
  author =	{Jonietz, David and Kopp, Michael},
  title =	{{Towards Modeling Geographical Processes with Generative Adversarial Networks (GANs)}},
  booktitle =	{14th International Conference on Spatial Information Theory (COSIT 2019)},
  pages =	{27:1--27:9},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-115-3},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{142},
  editor =	{Timpf, Sabine and Schlieder, Christoph and Kattenbeck, Markus and Ludwig, Bernd and Stewart, Kathleen},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2019.27},
  URN =		{urn:nbn:de:0030-drops-111193},
  doi =		{10.4230/LIPIcs.COSIT.2019.27},
  annote =	{Keywords: GAN, generative modeling, deep learning, geosimulation, game of life}
}
Document
DOI: 10.4230/LIPIcs.COSIT.2017.15
Uncertainty in Wayfinding: A Conceptual Framework and Agent-Based Model

Authors: David Jonietz and Peter Kiefer

Published in: LIPIcs, Volume 86, 13th International Conference on Spatial Information Theory (COSIT 2017)

Abstract
Though the wayfinding process is inherently uncertain, most models of wayfinding do not offer sufficient possibilities for modeling uncertainty. Such modeling approaches, however, are required to engineer assistance systems that recognize, predict, and react to a wayfinder's uncertainty. This paper introduces a conceptual framework for modeling uncertainty in wayfinding. It is supposed that uncertainty when following route instructions in wayfinding is caused by non-deterministic spatial reference system transformations. The uncertainty experienced by a wayfinder varies over time and depends on how well wayfinding instructions fit with the environment. The conceptual framework includes individual differences regarding wayfinding skills and regarding uncertainty tolerance. It is implemented as an agent-based model, based on the belief-desire-intention (BDI) framework. The feasibility of the approach is demonstrated with agent-based simulations.
Cite as

David Jonietz and Peter Kiefer. Uncertainty in Wayfinding: A Conceptual Framework and Agent-Based Model. In 13th International Conference on Spatial Information Theory (COSIT 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 86, pp. 15:1-15:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{jonietz_et_al:LIPIcs.COSIT.2017.15,
  author =	{Jonietz, David and Kiefer, Peter},
  title =	{{Uncertainty in Wayfinding: A Conceptual Framework and Agent-Based Model}},
  booktitle =	{13th International Conference on Spatial Information Theory (COSIT 2017)},
  pages =	{15:1--15:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-043-9},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{86},
  editor =	{Clementini, Eliseo and Donnelly, Maureen and Yuan, May and Kray, Christian and Fogliaroni, Paolo and Ballatore, Andrea},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2017.15},
  URN =		{urn:nbn:de:0030-drops-77497},
  doi =		{10.4230/LIPIcs.COSIT.2017.15},
  annote =	{Keywords: Wayfinding, Uncertainty, Agent-Based Model}
}
Document
DOI: 10.4230/LIPIcs.COSIT.2017.16
Timing of Pedestrian Navigation Instructions

Authors: Ioannis Giannopoulos, David Jonietz, Martin Raubal, Georgios Sarlas, and Lisa Stähli

Published in: LIPIcs, Volume 86, 13th International Conference on Spatial Information Theory (COSIT 2017)

Abstract
During pedestrian navigation in outdoor urban environments we often utilize assistance systems to support decision-making. These systems help wayfinders by providing relevant information withing the context of their surroundings, e.g., landmark-based instructions of the type "turn left at the church". Next to the instruction type and content, also the timing of the instruction must be considered in order to facilitate the wayfinding process. In this work we present our findings concerning the user and environmental factors that have an impact on the timing of instructions. We applied a survival analysis on data collected through an experiment in a realistic virtual environment in order to analyze the expected distance to the decision point until instructions are needed. The presented results can be used by navigation systems for instruction timing based on the characteristics of the current wayfinder and environment.
Cite as

Ioannis Giannopoulos, David Jonietz, Martin Raubal, Georgios Sarlas, and Lisa Stähli. Timing of Pedestrian Navigation Instructions. In 13th International Conference on Spatial Information Theory (COSIT 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 86, pp. 16:1-16:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{giannopoulos_et_al:LIPIcs.COSIT.2017.16,
  author =	{Giannopoulos, Ioannis and Jonietz, David and Raubal, Martin and Sarlas, Georgios and St\"{a}hli, Lisa},
  title =	{{Timing of Pedestrian Navigation Instructions}},
  booktitle =	{13th International Conference on Spatial Information Theory (COSIT 2017)},
  pages =	{16:1--16:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-043-9},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{86},
  editor =	{Clementini, Eliseo and Donnelly, Maureen and Yuan, May and Kray, Christian and Fogliaroni, Paolo and Ballatore, Andrea},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2017.16},
  URN =		{urn:nbn:de:0030-drops-77606},
  doi =		{10.4230/LIPIcs.COSIT.2017.16},
  annote =	{Keywords: navigation, wayfinding, instructions, timing, survival analysis}
}
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