43 Search Results for "Verstegen, Judith A."

Volume

LIPIcs, Volume 208

11th International Conference on Geographic Information Science (GIScience 2021) - Part II

GIScience 2021, September 27-30, 2021, Poznań, Poland (Virtual Conference)

Editors: Krzysztof Janowicz and Judith A. Verstegen

Volume

LIPIcs, Volume 177

11th International Conference on Geographic Information Science (GIScience 2021) - Part I

GIScience 2021, September 27-30, 2021, Poznań, Poland

Editors: Krzysztof Janowicz and Judith A. Verstegen

Document
DOI: 10.4230/LIPIcs.ESA.2025.105
Parameterized Algorithms for Computing Pareto Sets

Authors: Joshua Marc Könen, Heiko Röglin, and Tarek Stuck

Published in: LIPIcs, Volume 351, 33rd Annual European Symposium on Algorithms (ESA 2025)

Abstract
The problem of computing the set of Pareto-optimal solutions has been studied for a variety of multiobjective optimization problems. For many such problems, algorithms are known that compute the Pareto set in (weak) output-polynomial time. These algorithms are often based on dynamic programming and by weak output-polynomial time, we mean that the running time depends polynomially on the size of the Pareto set but also on the sizes of the Pareto sets of the subproblems that occur in the dynamic program. For some problems, like the multiobjective minimum spanning tree problem, such algorithms are not known to exist and for other problems, like multiobjective versions of many NP-hard problems, such algorithms cannot exist, unless 𝒫 = 𝒩𝒫. Dynamic programming over tree decompositions is a common technique in parameterized algorithms. In this paper, we study whether this technique can also be applied to compute Pareto sets of multiobjective optimization problems. We first derive an algorithm to compute the Pareto set for the multicriteria s-t cut problem and show how this result can be applied to a polygon aggregation problem arising in cartography that has recently been introduced by Rottmann et al. (GIScience 2021). We also show how to apply these techniques to also compute the Pareto set of the multiobjective minimum spanning tree problem and for the multiobjective TSP. The running time of our algorithms is O(f(w)⋅poly(n,p_{max})), where f is some function in the treewidth w, n is the input size, and p_{max} is an upper bound on the size of the Pareto sets of the subproblems that occur in the dynamic program. Finally, we present an experimental evaluation of computing Pareto sets on real-world instances of polygon aggregation problems. For this matter we devised a task-specific data structure that allows for efficient storage and modification of large sets of Pareto-optimal solutions. Throughout the implementation process, we incorporated several improved strategies and heuristics that significantly reduced both runtime and memory usage, enabling us to solve instances with treewidth of up to 22 within reasonable amount of time. Moreover, we conducted a preprocessing study to compare different tree decompositions in terms of their estimated overall runtime.
Cite as

Joshua Marc Könen, Heiko Röglin, and Tarek Stuck. Parameterized Algorithms for Computing Pareto Sets. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 105:1-105:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{konen_et_al:LIPIcs.ESA.2025.105,
  author =	{K\"{o}nen, Joshua Marc and R\"{o}glin, Heiko and Stuck, Tarek},
  title =	{{Parameterized Algorithms for Computing Pareto Sets}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{105:1--105:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-395-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{351},
  editor =	{Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.105},
  URN =		{urn:nbn:de:0030-drops-245749},
  doi =		{10.4230/LIPIcs.ESA.2025.105},
  annote =	{Keywords: parameterized algorithms, treewidth, multicriteria optimization problems, multicriteria MST, multicriteria TSP, polygon aggregation}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2025.13
Assessing Map Reproducibility with Visual Question-Answering: An Empirical Evaluation

Authors: Eftychia Koukouraki, Auriol Degbelo, and Christian Kray

Published in: LIPIcs, Volume 346, 13th International Conference on Geographic Information Science (GIScience 2025)

Abstract
Reproducibility is a key principle of the modern scientific method. Maps, as an important means of communicating scientific results in GIScience and across disciplines, should be reproducible. Currently, map reproducibility assessment is done manually, which makes the assessment process tedious and time-consuming, ultimately limiting its efficiency. Hence, this work explores the extent to which Visual Question-Answering (VQA) can be used to automate some tasks relevant to map reproducibility assessment. We selected five state-of-the-art vision language models (VLMs) and followed a three-step approach to evaluate their ability to discriminate between maps and other images, interpret map content, and compare two map images using VQA. Our results show that current VLMs already possess map-reading capabilities and demonstrate understanding of spatial concepts, such as cardinal directions, geographic scope, and legend interpretation. Our paper demonstrates the potential of using VQA to support reproducibility assessment and highlights the outstanding issues that need to be addressed to achieve accurate, trustworthy map descriptions, thereby reducing the time and effort required by human evaluators.
Cite as

Eftychia Koukouraki, Auriol Degbelo, and Christian Kray. Assessing Map Reproducibility with Visual Question-Answering: An Empirical Evaluation. In 13th International Conference on Geographic Information Science (GIScience 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 346, pp. 13:1-13:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{koukouraki_et_al:LIPIcs.GIScience.2025.13,
  author =	{Koukouraki, Eftychia and Degbelo, Auriol and Kray, Christian},
  title =	{{Assessing Map Reproducibility with Visual Question-Answering: An Empirical Evaluation}},
  booktitle =	{13th International Conference on Geographic Information Science (GIScience 2025)},
  pages =	{13:1--13:12},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-378-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{346},
  editor =	{Sila-Nowicka, Katarzyna and Moore, Antoni and O'Sullivan, David and Adams, Benjamin and Gahegan, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2025.13},
  URN =		{urn:nbn:de:0030-drops-238426},
  doi =		{10.4230/LIPIcs.GIScience.2025.13},
  annote =	{Keywords: map comparison, computational reproducibility, visual question answering, large language models, GeoAI}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2025.17
The Inherent Structure of Experiments as a Constraint to Spatial Analysis and Modeling

Authors: Simon Scheider and Judith A. Verstegen

Published in: LIPIcs, Volume 346, 13th International Conference on Geographic Information Science (GIScience 2025)

Abstract
We argue that in order to justify a modeling approach for a particular purpose, we need to better understand the experimental structure that is supposed to be represented by a given model application. For this purpose, we introduce a logic for specifying causal as well as spatio-temporal experiments, based on which we reinterpret Sinton’s structure of spatial information from a pragmatic, experimental viewpoint. We illustrate the use of this logic based on a landuse modeling example, showing to what extent remote sensing and simulation approaches can be justified by decomposing the example into experiments required for answering its main question.
Cite as

Simon Scheider and Judith A. Verstegen. The Inherent Structure of Experiments as a Constraint to Spatial Analysis and Modeling. In 13th International Conference on Geographic Information Science (GIScience 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 346, pp. 17:1-17:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{scheider_et_al:LIPIcs.GIScience.2025.17,
  author =	{Scheider, Simon and Verstegen, Judith A.},
  title =	{{The Inherent Structure of Experiments as a Constraint to Spatial Analysis and Modeling}},
  booktitle =	{13th International Conference on Geographic Information Science (GIScience 2025)},
  pages =	{17:1--17:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-378-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{346},
  editor =	{Sila-Nowicka, Katarzyna and Moore, Antoni and O'Sullivan, David and Adams, Benjamin and Gahegan, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2025.17},
  URN =		{urn:nbn:de:0030-drops-238468},
  doi =		{10.4230/LIPIcs.GIScience.2025.17},
  annote =	{Keywords: pragmatic Logic, experimental Norms, spatio-temporal Models}
}
Artifact
Dataset
DOI: 10.4230/artifacts.22460
Spatio-temporal modeling questions

Authors: Simon Scheider

Abstract
Cite as

Simon Scheider. Spatio-temporal modeling questions (Dataset, Source Code). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@misc{dagstuhl-artifact-22460,
   title = {{Spatio-temporal modeling questions}}, 
   author = {Scheider, Simon},
   note = {Dataset, European Research Council (ERC) under the European23 Union’s Horizon 2020 research and innovation programme (grant agreement No. 803498), swhId: \href{https://archive.softwareheritage.org/swh:1:dir:c63d8dc4808114f58911f1870afaa462b6338d4f;origin=https://github.com/simonscheider/ModelQuestions;visit=swh:1:snp:da0d8a88344ade91475e6389b44575ac3d2b3229;anchor=swh:1:rev:be8d1f3aae6c3a977783539178dd32e98e9c15a9}{\texttt{swh:1:dir:c63d8dc4808114f58911f1870afaa462b6338d4f}} (visited on 2024-11-28)},
   url = {https://github.com/simonscheider/ModelQuestions},
   doi = {10.4230/artifacts.22460},
}
Document
DOI: 10.4230/LIPIcs.COSIT.2024.7
What Is a Spatio-Temporal Model Good For?: Validity as a Function of Purpose and the Questions Answered by a Model

Authors: Simon Scheider and Judith A. Verstegen

Published in: LIPIcs, Volume 315, 16th International Conference on Spatial Information Theory (COSIT 2024)

Abstract
The concept of validity is a cornerstone of science. Given this central role, it is somewhat surprising to find that validity remains a rather obscure concept. Unfortunately, the term is often reduced to a matter of ground truth data, seemingly because we fail to come to grips with it. In this paper, instead, we take a purpose-based approach to the validity of spatio-temporal models. We argue that a model application is valid only if the model delivers an answer to a particular spatio-temporal question specifying some experiment including spatio-temporal controls and measures. Such questions constitute the information purposes of models, forming an intermediate layer in a pragmatic knowledge pyramid with corresponding levels of validity. We introduce a corresponding question-based grammar that allows us to formally distinguish among contemporary inference, prediction, retrodiction, projection, and retrojection models. We apply the grammar to corresponding examples and discuss the possibilities for validating such models as a means to a given end.
Cite as

Simon Scheider and Judith A. Verstegen. What Is a Spatio-Temporal Model Good For?: Validity as a Function of Purpose and the Questions Answered by a Model. In 16th International Conference on Spatial Information Theory (COSIT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 315, pp. 7:1-7:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{scheider_et_al:LIPIcs.COSIT.2024.7,
  author =	{Scheider, Simon and Verstegen, Judith A.},
  title =	{{What Is a Spatio-Temporal Model Good For?: Validity as a Function of Purpose and the Questions Answered by a Model}},
  booktitle =	{16th International Conference on Spatial Information Theory (COSIT 2024)},
  pages =	{7:1--7:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-330-0},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{315},
  editor =	{Adams, Benjamin and Griffin, Amy L. and Scheider, Simon and McKenzie, Grant},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2024.7},
  URN =		{urn:nbn:de:0030-drops-208225},
  doi =		{10.4230/LIPIcs.COSIT.2024.7},
  annote =	{Keywords: validity, fitness-for-purpose, spatio-temporal modeling, pragmatics, question grammar}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2023.4
Genetic Programming for Computationally Efficient Land Use Allocation Optimization

Authors: Moritz J. Hildemann, Alan T. Murray, and Judith A. Verstegen

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

Abstract
Land use allocation optimization is essential to identify ideal landscape compositions for the future. However, due to the solution encoding, standard land use allocation algorithms cannot cope with large land use allocation problems. Solutions are encoded as sequences of elements, in which each element represents a land unit or a group of land units. As a consequence, computation times increase with every additional land unit. We present an alternative solution encoding: functions describing a variable in space. Function encoding yields the potential to evolve solutions detached from individual land units and evolve fields representing the landscape as a single object. In this study, we use a genetic programming algorithm to evolve functions representing continuous fields, which we then map to nominal land use maps. We compare the scalability of the new approach with the scalability of two state-of-the-art algorithms with standard encoding. We perform the benchmark on one raster and one vector land use allocation problem with multiple objectives and constraints, with ten problem sizes each. The results prove that the run times increase exponentially with the problem size for standard encoding schemes, while the increase is linear with genetic programming. Genetic programming was up to 722 times faster than the benchmark algorithm. The improvement in computation time does not reduce the algorithm performance in finding optimal solutions; often, it even increases. We conclude that evolving functions enables more efficient land use allocation planning and yields much potential for other spatial optimization applications.
Cite as

Moritz J. Hildemann, Alan T. Murray, and Judith A. Verstegen. Genetic Programming for Computationally Efficient Land Use Allocation Optimization. In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 4:1-4:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{hildemann_et_al:LIPIcs.GIScience.2023.4,
  author =	{Hildemann, Moritz J. and Murray, Alan T. and Verstegen, Judith A.},
  title =	{{Genetic Programming for Computationally Efficient Land Use Allocation Optimization}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{4:1--4:15},
  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.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.4},
  URN =		{urn:nbn:de:0030-drops-188996},
  doi =		{10.4230/LIPIcs.GIScience.2023.4},
  annote =	{Keywords: Land use planning, Spatial optimization, Solution encoding, Computation time reduction}
}
Document
Complete Volume
DOI: 10.4230/LIPIcs.GIScience.2021.II
LIPIcs, Volume 208, GIScience 2021, Complete Volume

Authors: Krzysztof Janowicz and Judith A. Verstegen

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

Abstract
LIPIcs, Volume 208, GIScience 2021, Complete Volume
Cite as

11th International Conference on Geographic Information Science (GIScience 2021) - Part II. Leibniz International Proceedings in Informatics (LIPIcs), Volume 208, pp. 1-224, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@Proceedings{janowicz_et_al:LIPIcs.GIScience.2021.II,
  title =	{{LIPIcs, Volume 208, GIScience 2021, Complete Volume}},
  booktitle =	{11th International Conference on Geographic Information Science (GIScience 2021) - Part II},
  pages =	{1--224},
  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.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2021.II},
  URN =		{urn:nbn:de:0030-drops-147585},
  doi =		{10.4230/LIPIcs.GIScience.2021.II},
  annote =	{Keywords: LIPIcs, Volume 208, GIScience 2021, Complete Volume}
}
Document
Front Matter
DOI: 10.4230/LIPIcs.GIScience.2021.II.0
Front Matter, Table of Contents, Preface, Conference Organization

Authors: Krzysztof Janowicz and Judith A. Verstegen

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

Abstract
Front Matter, Table of Contents, Preface, Conference Organization
Cite as

11th International Conference on Geographic Information Science (GIScience 2021) - Part II. Leibniz International Proceedings in Informatics (LIPIcs), Volume 208, pp. 0:i-0:xiv, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{janowicz_et_al:LIPIcs.GIScience.2021.II.0,
  author =	{Janowicz, Krzysztof and Verstegen, Judith A.},
  title =	{{Front Matter, Table of Contents, Preface, Conference Organization}},
  booktitle =	{11th International Conference on Geographic Information Science (GIScience 2021) - Part II},
  pages =	{0:i--0:xiv},
  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.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2021.II.0},
  URN =		{urn:nbn:de:0030-drops-147593},
  doi =		{10.4230/LIPIcs.GIScience.2021.II.0},
  annote =	{Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2021.II.1
Adaptive Voronoi Masking: A Method to Protect Confidential Discrete Spatial Data

Authors: Fiona Polzin and Ourania Kounadi

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

Abstract
Geomasks assure the protection of individuals in a discrete spatial point data set by aggregating, transferring or altering original points. This study develops an alternative approach, referred to as Adaptive Voronoi Masking (AVM), which is based on the concepts of Adaptive Aerial Elimination (AAE) and Voronoi Masking (VM). It considers the underlying population density by establishing areas of K-anonymity in which Voronoi polygons are created. Contrary to other geomasks, AVM considers the underlying topography and displaces data points to street intersections thus decreasing the risk of false-identification since residences are not endowed with a data point. The geomasking effects of AVM are examined by various spatial analytical results and are compared with the outputs of AAE, VM, and Donut Masking (DM). VM attains the best efficiency for the mean centres whereas DM does for the median centres. Regarding the Nearest Neighbour Hierarchical Cluster Analysis and Ripley’s K-function, DM demonstrates the strongest performance since its cluster ellipsoids and clustering distance are the most similar to those of the original data. The extend of the original data is preserved the most by VM, while AVM retains the topology of the point pattern. Overall, AVM was ranked as 2nd in terms of data utility (i) and also outperforms all methods regarding the risk of false re-identification (ii) because no data point is moved to a residence. Furthermore, AVM maintains the Spatial K-anonymity (iii) which is also done by AAE and partly by DM. Based on the performance combination of these factors, AVM is an advantageous technique to mask geodata.
Cite as

Fiona Polzin and Ourania Kounadi. Adaptive Voronoi Masking: A Method to Protect Confidential Discrete Spatial Data. In 11th International Conference on Geographic Information Science (GIScience 2021) - Part II. Leibniz International Proceedings in Informatics (LIPIcs), Volume 208, pp. 1:1-1:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{polzin_et_al:LIPIcs.GIScience.2021.II.1,
  author =	{Polzin, Fiona and Kounadi, Ourania},
  title =	{{Adaptive Voronoi Masking: A Method to Protect Confidential Discrete Spatial Data}},
  booktitle =	{11th International Conference on Geographic Information Science (GIScience 2021) - Part II},
  pages =	{1:1--1:17},
  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.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2021.II.1},
  URN =		{urn:nbn:de:0030-drops-147606},
  doi =		{10.4230/LIPIcs.GIScience.2021.II.1},
  annote =	{Keywords: Geoprivacy, location privacy, geomasking, Adaptive Voronoi Masking, Voronoi Masking, Adaptive Aerial Elimination, Donut Geomasking, ESDA}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2021.II.2
Reproducible Research and GIScience: An Evaluation Using GIScience Conference Papers

Authors: Frank O. Ostermann, Daniel Nüst, Carlos Granell, Barbara Hofer, and Markus Konkol

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

Abstract
GIScience conference authors and researchers face the same computational reproducibility challenges as authors and researchers from other disciplines who use computers to analyse data. Here, to assess the reproducibility of GIScience research, we apply a rubric for assessing the reproducibility of 75 conference papers published at the GIScience conference series in the years 2012-2018. Since the rubric and process were previously applied to the publications of the AGILE conference series, this paper itself is an attempt to replicate that analysis, however going beyond the previous work by evaluating and discussing proposed measures to improve reproducibility in the specific context of the GIScience conference series. The results of the GIScience paper assessment are in line with previous findings: although descriptions of workflows and the inclusion of the data and software suffice to explain the presented work, in most published papers they do not allow a third party to reproduce the results and findings with a reasonable effort. We summarise and adapt previous recommendations for improving this situation and propose the GIScience community to start a broad discussion on the reusability, quality, and openness of its research. Further, we critically reflect on the process of assessing paper reproducibility, and provide suggestions for improving future assessments. The code and data for this article are published at https://doi.org/10.5281/zenodo.4032875.
Cite as

Frank O. Ostermann, Daniel Nüst, Carlos Granell, Barbara Hofer, and Markus Konkol. Reproducible Research and GIScience: An Evaluation Using GIScience Conference Papers. In 11th International Conference on Geographic Information Science (GIScience 2021) - Part II. Leibniz International Proceedings in Informatics (LIPIcs), Volume 208, pp. 2:1-2:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{ostermann_et_al:LIPIcs.GIScience.2021.II.2,
  author =	{Ostermann, Frank O. and N\"{u}st, Daniel and Granell, Carlos and Hofer, Barbara and Konkol, Markus},
  title =	{{Reproducible Research and GIScience: An Evaluation Using GIScience Conference Papers}},
  booktitle =	{11th International Conference on Geographic Information Science (GIScience 2021) - Part II},
  pages =	{2:1--2:16},
  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.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2021.II.2},
  URN =		{urn:nbn:de:0030-drops-147615},
  doi =		{10.4230/LIPIcs.GIScience.2021.II.2},
  annote =	{Keywords: reproducible research, open science, reproducibility, GIScience}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2021.II.3
Comparison of Simulated Fast and Green Routes for Cyclists and Pedestrians

Authors: Christina Ludwig, Sven Lautenbach, Eva-Marie Schömann, and Alexander Zipf

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

Abstract
Routes with a high share of greenery are attractive for cyclist and pedestrians. We analyze how strongly such green routes differ from the respective fast routes using the openrouteservice. Greenness of streets was estimated based on OpenStreetMap data in combination with Sentinel-II imagery, 3d laser scan data and administrative information on trees on public ground. We assess the effect both at the level of the individual route and at the urban level for two German cities: Dresden and Heidelberg. For individual routes, we study how strongly green routes differ from the respective fast routes. In addition, we identify parts of the road network which represent important green corridors as well as unattractive parts which can or cannot be avoided at the cost of reasonable detours. In both cities, our results show the importance of urban green spaces for the provision of attractive green routes and provide new insights for urban planning by identifying unvegetated bottlenecks in the street network for which no green alternatives exist at this point.
Cite as

Christina Ludwig, Sven Lautenbach, Eva-Marie Schömann, and Alexander Zipf. Comparison of Simulated Fast and Green Routes for Cyclists and Pedestrians. In 11th International Conference on Geographic Information Science (GIScience 2021) - Part II. Leibniz International Proceedings in Informatics (LIPIcs), Volume 208, pp. 3:1-3:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{ludwig_et_al:LIPIcs.GIScience.2021.II.3,
  author =	{Ludwig, Christina and Lautenbach, Sven and Sch\"{o}mann, Eva-Marie and Zipf, Alexander},
  title =	{{Comparison of Simulated Fast and Green Routes for Cyclists and Pedestrians}},
  booktitle =	{11th International Conference on Geographic Information Science (GIScience 2021) - Part II},
  pages =	{3:1--3:15},
  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.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2021.II.3},
  URN =		{urn:nbn:de:0030-drops-147622},
  doi =		{10.4230/LIPIcs.GIScience.2021.II.3},
  annote =	{Keywords: Routing, OpenStreetMap, route choice, urban vegetation, sustainable mobility}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2021.II.4
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.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
DOI: 10.4230/LIPIcs.GIScience.2021.II.5
Will You Take This Turn? Gaze-Based Turning Activity Recognition During Navigation

Authors: Negar Alinaghi, Markus Kattenbeck, Antonia Golab, and Ioannis Giannopoulos

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

Abstract
Decision making is an integral part of wayfinding and people progressively use navigation systems to facilitate this task. The primary decision, which is also the main source of navigation error, is about the turning activity, i.e., to decide either to turn left or right or continue straight forward. The fundamental step to deal with this error, before applying any preventive approaches, e.g., providing more information, or any compensatory solutions, e.g., pre-calculating alternative routes, could be to predict and recognize the potential turning activity. This paper aims to address this step by predicting the turning decision of pedestrian wayfinders, before the actual action takes place, using primarily gaze-based features. Applying Machine Learning methods, the results of the presented experiment demonstrate an overall accuracy of 91% within three seconds before arriving at a decision point. Beyond the application perspective, our findings also shed light on the cognitive processes of decision making as reflected by the wayfinder’s gaze behaviour: incorporating environmental and user-related factors to the model, results in a noticeable change with respect to the importance of visual search features in turn activity recognition.
Cite as

Negar Alinaghi, Markus Kattenbeck, Antonia Golab, and Ioannis Giannopoulos. Will You Take This Turn? Gaze-Based Turning Activity Recognition During Navigation. In 11th International Conference on Geographic Information Science (GIScience 2021) - Part II. Leibniz International Proceedings in Informatics (LIPIcs), Volume 208, pp. 5:1-5:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{alinaghi_et_al:LIPIcs.GIScience.2021.II.5,
  author =	{Alinaghi, Negar and Kattenbeck, Markus and Golab, Antonia and Giannopoulos, Ioannis},
  title =	{{Will You Take This Turn? Gaze-Based Turning Activity Recognition During Navigation}},
  booktitle =	{11th International Conference on Geographic Information Science (GIScience 2021) - Part II},
  pages =	{5:1--5:16},
  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.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2021.II.5},
  URN =		{urn:nbn:de:0030-drops-147649},
  doi =		{10.4230/LIPIcs.GIScience.2021.II.5},
  annote =	{Keywords: Activity Recognition, Wayfinding, Eye Tracking, Machine Learning}
}
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