8 Search Results for "Raubal, Martin"


Document
Benchmarking Regression Models Under Spatial Heterogeneity

Authors: Nina Wiedemann, Henry Martin, and René Westerholt

Published in: LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023)


Abstract
Machine learning methods have recently found much application on spatial data, for example in weather forecasting, traffic prediction, and soil analysis. At the same time, methods from spatial statistics were developed over the past decades to explicitly account for spatial structuring in analytical and inference tasks. In the light of this duality of having both types of methods available, we explore the following question: Under what circumstances are local, spatially-explicit models preferable over machine learning models that do not incorporate spatial structure explicitly in their specification? Local models are typically used to capture spatial non-stationarity. Thus, we study the effect of strength and type of spatial heterogeneity, which may originate from non-stationarity of a process itself or from heterogeneous noise, on the performance of different linear and non-linear, local and global machine learning and regression models. The results suggest that it is necessary to assess the performance of linear local models on an independent hold-out dataset, since models may overfit under certain conditions. We further show that local models are advantageous in settings with small sample size and high degrees of spatial heterogeneity. Our findings allow deriving model selection criteria, which are validated in benchmarking experiments on five well-known spatial datasets.

Cite as

Nina Wiedemann, Henry Martin, and René Westerholt. Benchmarking Regression Models Under Spatial Heterogeneity. In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 11:1-11:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{wiedemann_et_al:LIPIcs.GIScience.2023.11,
  author =	{Wiedemann, Nina and Martin, Henry and Westerholt, Ren\'{e}},
  title =	{{Benchmarking Regression Models Under Spatial Heterogeneity}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{11:1--11:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.11},
  URN =		{urn:nbn:de:0030-drops-189064},
  doi =		{10.4230/LIPIcs.GIScience.2023.11},
  annote =	{Keywords: spatial machine learning, spatial non-stationarity, Geographically Weighted Regression, local models, geostatistics}
}
Document
Short Paper
Predicting visit frequencies to new places (Short Paper)

Authors: Nina Wiedemann, Ye Hong, and Martin Raubal

Published in: LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023)


Abstract
Human mobility exhibits power-law distributed visitation patterns; i.e., a few locations are visited frequently and many locations only once. Current research focuses on the important locations of users or on recommending new places based on collective behaviour, neglecting the existence of scarcely visited locations. However, assessing whether a user will return to a location in the future is highly relevant for personalized location-based services. Therefore, we propose a new problem formulation aimed at predicting the future visit frequency to a new location, focusing on the previous mobility behaviour of a single user. Our preliminary results demonstrate that visit frequency prediction is a difficult task, but sophisticated learning models can detect insightful patterns in the historic mobility indicative of future visit frequency. We believe these models can uncover valuable insights into the spatial factors that drive individual mobility behaviour.

Cite as

Nina Wiedemann, Ye Hong, and Martin Raubal. Predicting visit frequencies to new places (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 84:1-84:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{wiedemann_et_al:LIPIcs.GIScience.2023.84,
  author =	{Wiedemann, Nina and Hong, Ye and Raubal, Martin},
  title =	{{Predicting visit frequencies to new places}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{84:1--84:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.84},
  URN =		{urn:nbn:de:0030-drops-189794},
  doi =		{10.4230/LIPIcs.GIScience.2023.84},
  annote =	{Keywords: Human mobility, Visitation patterns, Place recommendation, Next location prediction}
}
Document
Short Paper
3D Sketch Maps: Concept, Potential Benefits, and Challenges (Short Paper)

Authors: Kevin Gonyop Kim, Jakub Krukar, Panagiotis Mavros, Jiayan Zhao, Peter Kiefer, Angela Schwering, Christoph Hölscher, and Martin Raubal

Published in: LIPIcs, Volume 240, 15th International Conference on Spatial Information Theory (COSIT 2022)


Abstract
Studying the 3D aspect of spatial information has become increasingly important due to changes in the way we interact with the surrounding environments as well as technological innovations. Current pen-and-paper approaches of sketch mapping have a limitation in investigating 3D spatial knowledge as they are forced to be drawn on 2D interfaces. In this paper, we propose the concept of 3D sketch mapping as a tool to study human spatial knowledge by externalizing the mental models of spatial information with 3D representations. The goal of this paper is to introduce the concept, discuss its potential importance and challenges, and share our vision for future research directions.

Cite as

Kevin Gonyop Kim, Jakub Krukar, Panagiotis Mavros, Jiayan Zhao, Peter Kiefer, Angela Schwering, Christoph Hölscher, and Martin Raubal. 3D Sketch Maps: Concept, Potential Benefits, and Challenges (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 14:1-14:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


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@InProceedings{kim_et_al:LIPIcs.COSIT.2022.14,
  author =	{Kim, Kevin Gonyop and Krukar, Jakub and Mavros, Panagiotis and Zhao, Jiayan and Kiefer, Peter and Schwering, Angela and H\"{o}lscher, Christoph and Raubal, Martin},
  title =	{{3D Sketch Maps: Concept, Potential Benefits, and Challenges}},
  booktitle =	{15th International Conference on Spatial Information Theory (COSIT 2022)},
  pages =	{14:1--14:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-257-0},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{240},
  editor =	{Ishikawa, Toru and Fabrikant, Sara Irina and Winter, Stephan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.14},
  URN =		{urn:nbn:de:0030-drops-168992},
  doi =		{10.4230/LIPIcs.COSIT.2022.14},
  annote =	{Keywords: Sketch maps, mental representations, spatial knowledge}
}
Document
A Clustering-Based Framework for Individual Travel Behaviour Change Detection

Authors: Ye Hong, Yanan Xin, Henry Martin, Dominik Bucher, and Martin Raubal

Published in: LIPIcs, Volume 208, 11th International Conference on Geographic Information Science (GIScience 2021) - Part II


Abstract
The emergence of passively and continuously recorded movement data offers new opportunities to study the long-term change of individual travel behaviour from data-driven perspectives. This study proposes a clustering-based framework to identify travel behaviour patterns and detect potential change periods on the individual level. First, we extract important trips that depict individual characteristic movement. Then, considering trip mode, trip distance, and trip duration as travel behaviour dimensions, we measure the similarities of trips and group them into clusters using hierarchical clustering. The trip clusters represent dimensions of travel behaviours, and the change of their relative proportions over time reflect the development of travel preferences. We use two different methods to detect changes in travel behaviour patterns: the Herfindahl-Hirschman index-based method and the sliding window-based method. The framework is tested using data from a large-scale longitudinal GPS tracking data study in which participants had access to a Mobility-as-a-Service (MaaS) offer. The methods successfully identify significant travel behaviour changes for users. Moreover, we analyse the impact of the MaaS offer on individual travel behaviours with the obtained change information. The proposed framework for behaviour change detection provides valuable insights for travel demand management and evaluating people’s reactions to sustainable mobility options.

Cite as

Ye Hong, Yanan Xin, Henry Martin, Dominik Bucher, and Martin Raubal. A Clustering-Based Framework for Individual Travel Behaviour Change Detection. In 11th International Conference on Geographic Information Science (GIScience 2021) - Part II. Leibniz International Proceedings in Informatics (LIPIcs), Volume 208, pp. 4:1-4:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


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@InProceedings{hong_et_al:LIPIcs.GIScience.2021.II.4,
  author =	{Hong, Ye and Xin, Yanan and Martin, Henry and Bucher, Dominik and Raubal, Martin},
  title =	{{A Clustering-Based Framework for Individual Travel Behaviour Change Detection}},
  booktitle =	{11th International Conference on Geographic Information Science (GIScience 2021) - Part II},
  pages =	{4:1--4:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-208-2},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{208},
  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.II.4},
  URN =		{urn:nbn:de:0030-drops-147635},
  doi =		{10.4230/LIPIcs.GIScience.2021.II.4},
  annote =	{Keywords: Human mobility, Travel behaviour, Change detection, Trip clustering}
}
Document
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
Enhanced Multi Criteria Decision Analysis for Planning Power Transmission Lines

Authors: Joram Schito, Ulrike Wissen Hayek, and Martin Raubal

Published in: LIPIcs, Volume 114, 10th International Conference on Geographic Information Science (GIScience 2018)


Abstract
The energy transition towards alternative energy sources requires new power transmission lines to connect these additional energy production plants with electricity distribution centers. For this reason, Multi Criteria Decision Analysis (MCDA) offers a useful approach to determine the optimal path of future transmission lines with minimum impact on the environment, on the landscape, and on affected citizens. As objections could deteriorate such a project and in turn increase costs, transparent communication regarding the planning procedure is required that fosters citizens' acceptance. In this context, GIS-based information on the criteria taken into account and for modeling possible power transmission lines is essential. However, planners often forget that the underlying multi criteria decision model and the used data might lead to biased results. Therefore, this study empirically investigates the effect of various MCDA parameters by applying a sensitivity analysis on a multi criteria decision model. The output of this analysis is evaluated combining a Cluster Analysis, a Principal Component Analysis, and a Multivariate Analysis of Variance. Our results indicate that the variability of different corridor alternatives can be increased by using different MCDA parameter combinations. In particular, we found that applying continuous boundary models on areas leads to more distinct corridor alternatives than using a sharp-edged model, and better reflects actual planning practice for protecting areas against transmission lines. Comparing the results of two study areas, we conclude that our decision model behaved similarly across both sites and, hence, that the proposed procedure for enhancing the decision model is applicable to other study areas with comparable topographies. These results can help decision-makers and transmission line planners in simplifying and improving their decision models in order to increase credibility, legitimacy, and thus practical applicability.

Cite as

Joram Schito, Ulrike Wissen Hayek, and Martin Raubal. Enhanced Multi Criteria Decision Analysis for Planning Power Transmission Lines. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 15:1-15:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)


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@InProceedings{schito_et_al:LIPIcs.GISCIENCE.2018.15,
  author =	{Schito, Joram and Wissen Hayek, Ulrike and Raubal, Martin},
  title =	{{Enhanced Multi Criteria Decision Analysis for Planning Power Transmission Lines}},
  booktitle =	{10th International Conference on Geographic Information Science (GIScience 2018)},
  pages =	{15:1--15:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-083-5},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{114},
  editor =	{Winter, Stephan and Griffin, Amy and Sester, Monika},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.15},
  URN =		{urn:nbn:de:0030-drops-93438},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.15},
  annote =	{Keywords: Geographic Information Systems, Transmission Line Planning, Multi-Criteria Decision Analysis, Sensitivity Analysis, Cluster Analysis}
}
Document
Short Paper
Gaze Sequences and Map Task Complexity (Short Paper)

Authors: Fabian Göbel, Peter Kiefer, Ioannis Giannopoulos, and Martin Raubal

Published in: LIPIcs, Volume 114, 10th International Conference on Geographic Information Science (GIScience 2018)


Abstract
As maps are visual representations of spatial context to communicate geographic information, analysis of gaze behavior is promising to improve map design. In this research we investigate the impact of map task complexity and different legend types on the visual attention of a user. With an eye tracking experiment we could show that the complexity of two map tasks can be measured and compared based on AOI sequences analysis. This knowledge can help to improve map design for static maps or in the context of interactive systems, create better map interfaces, that adapt to the user's current task.

Cite as

Fabian Göbel, Peter Kiefer, Ioannis Giannopoulos, and Martin Raubal. Gaze Sequences and Map Task Complexity (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 30:1-30:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)


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@InProceedings{gobel_et_al:LIPIcs.GISCIENCE.2018.30,
  author =	{G\"{o}bel, Fabian and Kiefer, Peter and Giannopoulos, Ioannis and Raubal, Martin},
  title =	{{Gaze Sequences and Map Task Complexity}},
  booktitle =	{10th International Conference on Geographic Information Science (GIScience 2018)},
  pages =	{30:1--30:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-083-5},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{114},
  editor =	{Winter, Stephan and Griffin, Amy and Sester, Monika},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.30},
  URN =		{urn:nbn:de:0030-drops-93587},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.30},
  annote =	{Keywords: eye tracking, sequence analysis, map task complexity}
}
Document
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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