4 Search Results for "Laube, Patrick"


Document
Short Paper
From Change Detection to Change Analytics: Decomposing Multi-Temporal Pixel Evolution Vectors (Short Paper)

Authors: Victoria Scherelis, Patrick Laube, and Michael Doering

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


Abstract
Change detection is a well-established process of detaining spatial and temporal changes of entities between two or more timesteps. Current advancements in digital map processing offer vast new sources of multitemporal geodata. As the temporal aspect gains complexity, the dismantling of detected changes on a pixel-based scale becomes a costly undertaking. In efforts to establish and preserve the evolution of detected changes in long time series, this paper presents a method that allows the decomposition of pixel evolution vectors into three dimensions of change, described as directed change, change variability, and change magnitude. The three dimensions of change compile to complex change analytics per individual pixels and offer a multi-faceted analysis of landscape changes on an ordinal scale. Finally, the integration of class confidence from learned uncertainty estimates illustrates the avenue to include uncertainty into the here presented change analytics, and the three dimensions of change are visualized in complex change maps.

Cite as

Victoria Scherelis, Patrick Laube, and Michael Doering. From Change Detection to Change Analytics: Decomposing Multi-Temporal Pixel Evolution Vectors (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 65:1-65:6, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2023)


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@InProceedings{scherelis_et_al:LIPIcs.GIScience.2023.65,
  author =	{Scherelis, Victoria and Laube, Patrick and Doering, Michael},
  title =	{{From Change Detection to Change Analytics: Decomposing Multi-Temporal Pixel Evolution Vectors}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{65:1--65:6},
  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.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.65},
  URN =		{urn:nbn:de:0030-drops-189604},
  doi =		{10.4230/LIPIcs.GIScience.2023.65},
  annote =	{Keywords: Digital map processing, spatio-temporal modelling, land-use change}
}
Document
Short Paper
Deconstructed and Inverted Multi-Criteria Evaluation for On-The-Fly Scenario Development and Decision-Making (Short Paper)

Authors: Martin Geilhausen and Patrick Laube

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


Abstract
We propose a variation of the conventional spatial multi-criteria evaluation workflow for suitability analysis that allows efficient on-the fly scenario development for decision-making. Our approach proposes to reconstruct the conventional MCE workflow in order to exclude computationally expensive geoprocessing from the iterative scenario development. We then introduce a procedure that replaces costly iterations of spatial operations with one off-line preprocessing step followed by iterations of much less computationally expensive database queries. We illustrate our approach for deconstructed and inverted multi-criteria analysis with a case study aiming at selecting suitable sites for wind turbines in the Swiss alps.

Cite as

Martin Geilhausen and Patrick Laube. Deconstructed and Inverted Multi-Criteria Evaluation for On-The-Fly Scenario Development and Decision-Making (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 27:1-27:7, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018)


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@InProceedings{geilhausen_et_al:LIPIcs.GISCIENCE.2018.27,
  author =	{Geilhausen, Martin and Laube, Patrick},
  title =	{{Deconstructed and Inverted Multi-Criteria Evaluation for On-The-Fly Scenario Development and Decision-Making}},
  booktitle =	{10th International Conference on Geographic Information Science (GIScience 2018)},
  pages =	{27:1--27:7},
  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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.27},
  URN =		{urn:nbn:de:0030-drops-93558},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.27},
  annote =	{Keywords: Multi-criteria evaluation, efficiency, decision-making, data structures}
}
Document
Trajectory Grouping Structure under Geodesic Distance

Authors: Irina Kostitsyna, Marc van Kreveld, Maarten Löffler, Bettina Speckmann, and Frank Staals

Published in: LIPIcs, Volume 34, 31st International Symposium on Computational Geometry (SoCG 2015)


Abstract
In recent years trajectory data has become one of the main types of geographic data, and hence algorithmic tools to handle large quantities of trajectories are essential. A single trajectory is typically represented as a sequence of time-stamped points in the plane. In a collection of trajectories one wants to detect maximal groups of moving entities and their behaviour (merges and splits) over time. This information can be summarized in the trajectory grouping structure. Significantly extending the work of Buchin et al. [WADS 2013] into a realistic setting, we show that the trajectory grouping structure can be computed efficiently also if obstacles are present and the distance between the entities is measured by geodesic distance. We bound the number of critical events: times at which the distance between two subsets of moving entities is exactly epsilon, where epsilon is the threshold distance that determines whether two entities are close enough to be in one group. In case the n entities move in a simple polygon along trajectories with tau vertices each we give an O(tau n^2) upper bound, which is tight in the worst case. In case of well-spaced obstacles we give an O(tau(n^2 + m lambda_4(n))) upper bound, where m is the total complexity of the obstacles, and lambda_s(n) denotes the maximum length of a Davenport-Schinzel sequence of n symbols of order s. In case of general obstacles we give an O(tau min(n^2 + m^3 lambda_4(n), n^2m^2)) upper bound. Furthermore, for all cases we provide efficient algorithms to compute the critical events, which in turn leads to efficient algorithms to compute the trajectory grouping structure.

Cite as

Irina Kostitsyna, Marc van Kreveld, Maarten Löffler, Bettina Speckmann, and Frank Staals. Trajectory Grouping Structure under Geodesic Distance. In 31st International Symposium on Computational Geometry (SoCG 2015). Leibniz International Proceedings in Informatics (LIPIcs), Volume 34, pp. 674-688, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)


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@InProceedings{kostitsyna_et_al:LIPIcs.SOCG.2015.674,
  author =	{Kostitsyna, Irina and van Kreveld, Marc and L\"{o}ffler, Maarten and Speckmann, Bettina and Staals, Frank},
  title =	{{Trajectory Grouping Structure under Geodesic Distance}},
  booktitle =	{31st International Symposium on Computational Geometry (SoCG 2015)},
  pages =	{674--688},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-83-5},
  ISSN =	{1868-8969},
  year =	{2015},
  volume =	{34},
  editor =	{Arge, Lars and Pach, J\'{a}nos},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SOCG.2015.674},
  URN =		{urn:nbn:de:0030-drops-51212},
  doi =		{10.4230/LIPIcs.SOCG.2015.674},
  annote =	{Keywords: moving entities, trajectories, grouping, computational geometry}
}
Document
Representation, Analysis and Visualization of Moving Objects (Dagstuhl Seminar 12512)

Authors: Joachim Gudmundsson, Patrick Laube, and Emiel Van Loon

Published in: Dagstuhl Reports, Volume 2, Issue 12 (2013)


Abstract
From December 16 to December 21, 2012, the Dagstuhl Seminar 12512 "Representation, Analysis and Visualization of Moving Objects" was held in Schloss Dagstuhl -- Leibniz Center for Informatics. The major goal of this seminar was to bring together the diverse and fast growing, research community that is involved in developing better computational techniques for spatio-temporal object representation, data mining, and visualization of moving object data. The participants included experts from fields such as computational geometry, data mining, visual analytics, GIS science, urban planning and movement ecology. Most of the participants came from academic institutions but some also from government agencies and industry. The seminar has led to a fruitful exchange of ideas between different disciplines, to the creation of new interdisciplinary collaborations and to recommendations for future research directions. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper.

Cite as

Joachim Gudmundsson, Patrick Laube, and Emiel Van Loon. Representation, Analysis and Visualization of Moving Objects (Dagstuhl Seminar 12512). In Dagstuhl Reports, Volume 2, Issue 12, pp. 89-106, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2013)


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@Article{gudmundsson_et_al:DagRep.2.12.89,
  author =	{Gudmundsson, Joachim and Laube, Patrick and Van Loon, Emiel},
  title =	{{Representation, Analysis and Visualization of Moving Objects (Dagstuhl Seminar 12512)}},
  pages =	{89--106},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2013},
  volume =	{2},
  number =	{12},
  editor =	{Gudmundsson, Joachim and Laube, Patrick and Van Loon, Emiel},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.2.12.89},
  URN =		{urn:nbn:de:0030-drops-39966},
  doi =		{10.4230/DagRep.2.12.89},
  annote =	{Keywords: movement analysis, algorithms, visualization, geo-ecology, urban planning}
}
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