Volume
LIPIcs, Volume 114
10th International Conference on Geographic Information Science (GIScience 2018)
Event
GIScience 2018, August 28-31, 2018, Melbourne, AustraliaEditors
Publication Details
- published at: 2018-08-02
- Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
- ISBN: 978-3-95977-083-5
- DBLP: db/conf/giscience/giscience2018
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Document
Complete Volume
LIPIcs, Volume 114, GIScience'18, Complete Volume
Abstract
LIPIcs, Volume 114, GIScience'18, Complete Volume
Cite as
10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@Proceedings{winter_et_al:LIPIcs.GIScience.2018,
title = {{LIPIcs, Volume 114, GIScience'18, Complete Volume}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
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},
URN = {urn:nbn:de:0030-drops-97424},
doi = {10.4230/LIPIcs.GIScience.2018},
annote = {Keywords: Information systems, Location based services, Geographic information systems, Personalization}
}
Document
Front Matter
Front Matter, Table of Contents, Preface, Conference Organization
Abstract
Front Matter, Table of Contents, Preface, Conference Organization
Cite as
10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 0:i-0:xvi, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{winter_et_al:LIPIcs.GISCIENCE.2018.0,
author = {Winter, Stephan and Griffin, Amy and Sester, Monika},
title = {{Front Matter, Table of Contents, Preface, Conference Organization}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {0:i--0:xvi},
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.2018.0},
URN = {urn:nbn:de:0030-drops-93282},
doi = {10.4230/LIPIcs.GISCIENCE.2018.0},
annote = {Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
Document
Early Detection of Herding Behaviour during Emergency Evacuations
Abstract
Social scientists have observed a number of irrational behaviours during emergency evacuations, caused by a range of possible cognitive biases. One such behaviour is herding - people following and trusting others to guide them, when they do not know where the nearest exit is. This behaviour may lead to safety under a knowledgeable leader, but can also lead to dead-ends. We present a method for the automatic early detection of herding behaviour to avoid suboptimal evacuations. The method comprises three steps: (i) people clusters identification during evacuation, (ii) collection of clusters' spatio-temporal information to extract features for describing cluster behaviour, and (iii) unsupervised learning classification of clusters' behaviour into 'benign' or 'harmful' herding. Results using a set of different detection scores show accuracies higher than baselines in identifying harmful behaviour; thus, laying the ground for timely irrational behaviour detection to increase the performance of emergency evacuation systems.
Cite as
David Amores, Maria Vasardani, and Egemen Tanin. Early Detection of Herding Behaviour during Emergency Evacuations. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 1:1-1:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{amores_et_al:LIPIcs.GISCIENCE.2018.1,
author = {Amores, David and Vasardani, Maria and Tanin, Egemen},
title = {{Early Detection of Herding Behaviour during Emergency Evacuations}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {1:1--1:15},
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.2018.1},
URN = {urn:nbn:de:0030-drops-93293},
doi = {10.4230/LIPIcs.GISCIENCE.2018.1},
annote = {Keywords: spatio-temporal data, emergency evacuations, herding behaviour}
}
Document
What Makes Spatial Data Big? A Discussion on How to Partition Spatial Data
Abstract
The amount of available spatial data has significantly increased in the last years so that traditional analysis tools have become inappropriate to effectively manage them. Therefore, many attempts have been made in order to define extensions of existing MapReduce tools, such as Hadoop or Spark, with spatial capabilities in terms of data types and algorithms. Such extensions are mainly based on the partitioning techniques implemented for textual data where the dimension is given in terms of the number of occupied bytes. However, spatial data are characterized by other features which describe their dimension, such as the number of vertices or the MBR size of geometries, which greatly affect the performance of operations, like the spatial join, during data analysis. The result is that the use of traditional partitioning techniques prevents to completely exploit the benefit of the parallel execution provided by a MapReduce environment. This paper extensively analyses the problem considering the spatial join operation as use case, performing both a theoretical and an experimental analysis for it. Moreover, it provides a solution based on a different partitioning technique, which splits complex or extensive geometries. Finally, we validate the proposed solution by means of some experiments on synthetic and real datasets.
Cite as
Alberto Belussi, Damiano Carra, Sara Migliorini, Mauro Negri, and Giuseppe Pelagatti. What Makes Spatial Data Big? A Discussion on How to Partition Spatial Data. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 2:1-2:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{belussi_et_al:LIPIcs.GISCIENCE.2018.2,
author = {Belussi, Alberto and Carra, Damiano and Migliorini, Sara and Negri, Mauro and Pelagatti, Giuseppe},
title = {{What Makes Spatial Data Big? A Discussion on How to Partition Spatial Data}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {2:1--2:15},
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.2018.2},
URN = {urn:nbn:de:0030-drops-93306},
doi = {10.4230/LIPIcs.GISCIENCE.2018.2},
annote = {Keywords: Spatial join, SpatialHadoop, MapReduce, partitioning, big data}
}
Document
Intersections of Our World
Abstract
There are several situations where the type of a street intersections can become very important, especially in the case of navigation studies. The types of intersections affect the route complexity and this has to be accounted for, e.g., already during the experimental design phase of a navigation study. In this work we introduce a formal definition for intersection types and present a framework that allows for extracting information about the intersections of our planet. We present a case study that demonstrates the importance and necessity of being able to extract this information.
Cite as
Paolo Fogliaroni, Dominik Bucher, Nikola Jankovic, and Ioannis Giannopoulos. Intersections of Our World. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 3:1-3:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{fogliaroni_et_al:LIPIcs.GISCIENCE.2018.3,
author = {Fogliaroni, Paolo and Bucher, Dominik and Jankovic, Nikola and Giannopoulos, Ioannis},
title = {{Intersections of Our World}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {3:1--3:15},
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.2018.3},
URN = {urn:nbn:de:0030-drops-93310},
doi = {10.4230/LIPIcs.GISCIENCE.2018.3},
annote = {Keywords: intersection types, navigation, experimental design}
}
Document
Considerations of Graphical Proximity and Geographical Nearness
Abstract
"Near things are more similar than more distant things" states Tobler's first law of geography. This seems obvious and is part to much cognitive research into the perception of the environment. The statement's validity for assessments of geographical nearness purely from map symbols has yet to be ascertained. This paper considers this issue through a theoretical framework grounded in Gestalt concepts, behavioral ecological psychology and information psychology. It sets out to consider how influential experience or training may be on the association of graphical proximity with geographical nearness. A pilot study presents some initial findings. The findings regarding the influence of experience or training are ambiguous, but point to the rapid acquisition of affordances in the survey instruments as another factor for future research.
Cite as
Francis Harvey. Considerations of Graphical Proximity and Geographical Nearness. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 4:1-4:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{harvey:LIPIcs.GISCIENCE.2018.4,
author = {Harvey, Francis},
title = {{Considerations of Graphical Proximity and Geographical Nearness}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {4:1--4:18},
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.2018.4},
URN = {urn:nbn:de:0030-drops-93322},
doi = {10.4230/LIPIcs.GISCIENCE.2018.4},
annote = {Keywords: proximity, nearness, perception, cognition}
}
Document
An Empirical Study on the Names of Points of Interest and Their Changes with Geographic Distance
Abstract
While Points Of Interest (POIs), such as restaurants, hotels, and barber shops, are part of urban areas irrespective of their specific locations, the names of these POIs often reveal valuable information related to local culture, landmarks, influential families, figures, events, and so on. Place names have long been studied by geographers, e.g., to understand their origins and relations to family names. However, there is a lack of large-scale empirical studies that examine the localness of place names and their changes with geographic distance. In addition to enhancing our understanding of the coherence of geographic regions, such empirical studies are also significant for geographic information retrieval where they can inform computational models and improve the accuracy of place name disambiguation. In this work, we conduct an empirical study based on 112,071 POIs in seven US metropolitan areas extracted from an open Yelp dataset. We propose to adopt term frequency and inverse document frequency in geographic contexts to identify local terms used in POI names and to analyze their usages across different POI types. Our results show an uneven usage of local terms across POI types, which is highly consistent among different geographic regions. We also examine the decaying effect of POI name similarity with the increase of distance among POIs. While our analysis focuses on urban POI names, the presented methods can be generalized to other place types as well, such as mountain peaks and streets.
Cite as
Yingjie Hu and Krzysztof Janowicz. An Empirical Study on the Names of Points of Interest and Their Changes with Geographic Distance. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 5:1-5:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{hu_et_al:LIPIcs.GISCIENCE.2018.5,
author = {Hu, Yingjie and Janowicz, Krzysztof},
title = {{An Empirical Study on the Names of Points of Interest and Their Changes with Geographic Distance}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {5:1--5:15},
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.2018.5},
URN = {urn:nbn:de:0030-drops-93337},
doi = {10.4230/LIPIcs.GISCIENCE.2018.5},
annote = {Keywords: Place names, points of interest, geographic information retrieval, semantic similarity, geospatial semantics}
}
Document
Outlier Detection and Comparison of Origin-Destination Flows Using Data Depth
Abstract
Advances in location-aware technology have resulted in massive trajectory data. Origin-destination (OD) trajectories provide rich information on urban flow and transport demand. This study describes a new method for detecting OD flows outliers and conducting hypothesis testing between two OD flow datasets in terms of the variations of spatial extent, that is, spread. The proposed method is based on data depth, which measures the centrality and outlyingness of a point with respect to a given dataset in R^d. Based on the center-outward ordering property, the proposed method analyzes the underlying characteristics of OD flows, such as location, outlyingness, and spread. The ability of the method to detect OD anomalies is compared with that of the Mahalanobis distance approach, and an F-test is used to verify the difference in scale. Empirical evaluation has demonstrated that our method effectively identifies OD flows outliers in an interactive way. Furthermore, the method can provide new perspectives such as spatial extent by considering the overall structure of data when comparing two different OD flows in terms of scale.
Cite as
Myeong-Hun Jeong, Junjun Yin, and Shaowen Wang. Outlier Detection and Comparison of Origin-Destination Flows Using Data Depth. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 6:1-6:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{jeong_et_al:LIPIcs.GISCIENCE.2018.6,
author = {Jeong, Myeong-Hun and Yin, Junjun and Wang, Shaowen},
title = {{Outlier Detection and Comparison of Origin-Destination Flows Using Data Depth}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {6:1--6:14},
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.2018.6},
URN = {urn:nbn:de:0030-drops-93341},
doi = {10.4230/LIPIcs.GISCIENCE.2018.6},
annote = {Keywords: Movement Analysis, Trajectory Data Mining, Data Depth, Outlier Detection}
}
Document
Is Salience Robust? A Heterogeneity Analysis of Survey Ratings
Abstract
Differing weights for salience subdimensions (e.g. visual or structural salience) have been suggested since the early days of salience models in GIScience. Up until now, however, it remains unclear whether weights found in studies are robust across environments, objects and observers. In this study we examine the robustness of a survey-based salience model. Based on ratings of N_{o}=720 objects by N_{p}=250 different participants collected in-situ in two different European cities (Regensburg and Augsburg) we conduct a heterogeneity analysis taking into account environment and sense of direction stratified by gender. We find, first, empirical evidence that our model is invariant across environments, i.e. the strength of the relationships between the subdimensions of salience does not differ significantly. The structural model coefficients found can, hence, be used to calculate values for overall salience across different environments. Second, we provide empirical evidence that invariance of our measurement model is partly not given with respect to both, gender and sense of direction. These compositional invariance problems are a strong indicator for personal aspects playing an important role.
Cite as
Markus Kattenbeck, Eva Nuhn, and Sabine Timpf. Is Salience Robust? A Heterogeneity Analysis of Survey Ratings. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 7:1-7:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{kattenbeck_et_al:LIPIcs.GISCIENCE.2018.7,
author = {Kattenbeck, Markus and Nuhn, Eva and Timpf, Sabine},
title = {{Is Salience Robust? A Heterogeneity Analysis of Survey Ratings}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {7:1--7:16},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.7},
URN = {urn:nbn:de:0030-drops-93353},
doi = {10.4230/LIPIcs.GISCIENCE.2018.7},
annote = {Keywords: Salience Model, Measurement Invariance, Heterogeneity Analysis, PLS Path Modeling, Structural Equation Models}
}
Document
Labeling Points of Interest in Dynamic Maps using Disk Labels
Abstract
Dynamic maps which support panning, rotating and zooming are available on every smartphone today. To label geographic features on these maps such that the user is presented with a consistent map view even on map interaction is a challenge. We are presenting a map labeling scheme, which allows to label maps at an interactive speed. For any possible map rotation the computed labeling remains free of intersections between labels. It is not required to remove labels from the map view to ensure this. The labeling scheme supports map panning and continuous zooming. During zooming a label appears and disappears only once. When zooming out of the map a label disappears only if it may overlap an equally or more important label in an arbitrary map rotation. This guarantees that more important labels are preferred to less important labels on small scale maps. We are presenting some extensions to the labeling that could be used for more sophisticated labeling features such as area labels turning into point labels at smaller map scales.
The proposed labeling scheme relies on a preprocessing phase. In this phase for each label the map scale where it is removed from the map view is computed. During the phase of map presentation the precomputed label set must only be filtered, what can be done very fast. We are presenting some hints that allow to efficiently compute the labeling in the preprocessing phase. Using these a labeling of about 11 million labels can be computed in less than 20 minutes. We are also presenting a datastructure to efficiently filter the precomputed label set in the interaction phase.
Cite as
Filip Krumpe. Labeling Points of Interest in Dynamic Maps using Disk Labels. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 8:1-8:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{krumpe:LIPIcs.GISCIENCE.2018.8,
author = {Krumpe, Filip},
title = {{Labeling Points of Interest in Dynamic Maps using Disk Labels}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {8:1--8:14},
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.2018.8},
URN = {urn:nbn:de:0030-drops-93369},
doi = {10.4230/LIPIcs.GISCIENCE.2018.8},
annote = {Keywords: Map labeling, dynamic maps, label consistency, real-time, sorting/searching}
}
Document
Improving Discovery of Open Civic Data
Abstract
We describe a method and system design for improved data discovery in an integrated network of open geospatial data that supports collaborative policy development between governments and local constituents. Metadata about civic data (such as thematic categories, user-generated tags, geo-references, or attribute schemata) primarily rely on technical vocabularies that reflect scientific or organizational hierarchies. By contrast, public consumers of data often search for information using colloquial terminology that does not align with official metadata vocabularies. For example, citizens searching for data about bicycle collisions in an area are unlikely to use the search terms with which organizations like Departments of Transportation describe relevant data. Users may also search with broad terms, such as "traffic safety", and will then not discover data tagged with narrower official terms, such as "vehicular crash". This mismatch raises the question of how to bridge the users' ways of talking and searching with the language of technical metadata. In similar situations, it has been beneficial to augment official metadata with semantic annotations that expand the discoverability and relevance recommendations of data, supporting more inclusive access. Adopting this strategy, we develop a method for automated semantic annotation, which aggregates similar thematic and geographic information. A novelty of our approach is the development and application of a crosscutting base vocabulary that supports the description of geospatial themes. The resulting annotation method is integrated into a novel open access collaboration platform (Esri's ArcGIS Hub) that supports public dissemination of civic data and is in use by thousands of government agencies. Our semantic annotation method improves data discovery for users across organizational repositories and has the potential to facilitate the coordination of community and organizational work, improving the transparency and efficacy of government policies.
Cite as
Sara Lafia, Andrew Turner, and Werner Kuhn. Improving Discovery of Open Civic Data. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 9:1-9:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{lafia_et_al:LIPIcs.GISCIENCE.2018.9,
author = {Lafia, Sara and Turner, Andrew and Kuhn, Werner},
title = {{Improving Discovery of Open Civic Data}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {9:1--9:15},
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.2018.9},
URN = {urn:nbn:de:0030-drops-93376},
doi = {10.4230/LIPIcs.GISCIENCE.2018.9},
annote = {Keywords: data discovery, metadata, query expansion, interoperability}
}
Document
Local Co-location Pattern Detection: A Summary of Results
Abstract
Given a set of spatial objects of different features (e.g., mall, hospital) and a spatial relation (e.g., geographic proximity), the problem of local co-location pattern detection (LCPD) pairs co-location patterns and localities such that the co-location patterns tend to exist inside the paired localities. A co-location pattern is a set of spatial features, the objects of which are often related to each other. Local co-location patterns are common in many fields, such as public security, and public health. For example, assault crimes and drunk driving events co-locate near bars. The problem is computationally challenging because of the exponential number of potential co-location patterns and candidate localities. The related work applies data-unaware or clustering heuristics to partition the study area, which results in incomplete enumeration of possible localities. In this study, we formally defined the LCPD problem where the candidate locality was defined using minimum orthogonal bounding rectangles (MOBRs). Then, we proposed a Quadruplet & Grid Filter-Refine (QGFR) algorithm that leveraged an MOBR enumeration lemma, and a novel upper bound on the participation index to efficiently prune the search space. The experimental evaluation showed that the QGFR algorithm reduced the computation cost substantially. One case study using the North American Atlas-Hydrography and U.S. Major City Datasets was conducted to discover local co-location patterns which would be missed if the entire dataset was analyzed or methods proposed by the related work were applied.
Cite as
Yan Li and Shashi Shekhar. Local Co-location Pattern Detection: A Summary of Results. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 10:1-10:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{li_et_al:LIPIcs.GISCIENCE.2018.10,
author = {Li, Yan and Shekhar, Shashi},
title = {{Local Co-location Pattern Detection: A Summary of Results}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {10:1--10:15},
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.2018.10},
URN = {urn:nbn:de:0030-drops-93387},
doi = {10.4230/LIPIcs.GISCIENCE.2018.10},
annote = {Keywords: Co-location pattern, Participation index, Spatial heterogeneity}
}
Document
Detection and Localization of Traffic Signals with GPS Floating Car Data and Random Forest
Abstract
As Floating Car Data are becoming increasingly available, in recent years many research works focused on leveraging them to infer road map geometry, topology and attributes. In this paper, we present an algorithm, relying on supervised learning to detect and localize traffic signals based on the spatial distribution of vehicle stop points. Our main contribution is to provide a single framework to address both problems. The proposed method has been experimented with a one-month dataset of real-world GPS traces, collected on the road network of Mitaka (Japan). The results show that this method provides accurate results in terms of localization and performs advantageously compared to the OpenStreetMap database in exhaustivity. Among many potential applications, the output predictions may be used as a prior map and/or combined with other sources of data to guide autonomous vehicles.
Cite as
Yann Méneroux, Hiroshi Kanasugi, Guillaume Saint Pierre, Arnaud Le Guilcher, Sébastien Mustière, Ryosuke Shibasaki, and Yugo Kato. Detection and Localization of Traffic Signals with GPS Floating Car Data and Random Forest. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 11:1-11:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{meneroux_et_al:LIPIcs.GISCIENCE.2018.11,
author = {M\'{e}neroux, Yann and Kanasugi, Hiroshi and Saint Pierre, Guillaume and Le Guilcher, Arnaud and Musti\`{e}re, S\'{e}bastien and Shibasaki, Ryosuke and Kato, Yugo},
title = {{Detection and Localization of Traffic Signals with GPS Floating Car Data and Random Forest}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {11:1--11:15},
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.2018.11},
URN = {urn:nbn:de:0030-drops-93397},
doi = {10.4230/LIPIcs.GISCIENCE.2018.11},
annote = {Keywords: Map Inference, Machine Learning, GPS Traces, Traffic Signal}
}
Document
Heterogeneous Skeleton for Summarizing Continuously Distributed Demand in a Region
Abstract
There has long been interest in the skeleton of a spatial object in GIScience. The reasons for this are many, as it has proven to be an extremely useful summary and explanatory representation of complex objects. While much research has focused on issues of computational complexity and efficiency in extracting the skeletal and medial axis representations as well as interpreting the final product, little attention has been paid to fundamental assumptions about the underlying object. This paper discusses the implied assumption of homogeneity associated with methods for deriving a skeleton. Further, it is demonstrated that addressing heterogeneity complicates both the interpretation and identification of a meaningful skeleton. The heterogeneous skeleton is introduced and formalized, along with a method for its identification. Application results are presented to illustrate the heterogeneous skeleton and provides comparative contrast to homogeneity assumptions.
Cite as
Alan T. Murray, Xin Feng, and Ali Shokoufandeh. Heterogeneous Skeleton for Summarizing Continuously Distributed Demand in a Region. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 12:1-12:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{murray_et_al:LIPIcs.GISCIENCE.2018.12,
author = {Murray, Alan T. and Feng, Xin and Shokoufandeh, Ali},
title = {{Heterogeneous Skeleton for Summarizing Continuously Distributed Demand in a Region}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {12:1--12:11},
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.2018.12},
URN = {urn:nbn:de:0030-drops-93400},
doi = {10.4230/LIPIcs.GISCIENCE.2018.12},
annote = {Keywords: Medial axis, Object center, Geographical summary, Spatial analytics}
}
Document
A Network Flow Model for the Analysis of Green Spaces in Urban Areas
Abstract
Green spaces in urban areas offer great possibilities of recreation, provided that they are easily accessible. Therefore, an ideal city should offer large green spaces close to where its residents live. Although there are several measures for the assessment of urban green spaces, the existing measures usually focus either on the total size of green spaces or on their accessibility. Hence, in this paper, we present a new methodology for assessing green-space provision and accessibility in an integrated way. The core of our methodology is an algorithm based on linear programming that computes an optimal assignment between residential areas and green spaces. In a basic setting, it assigns a green space of a prescribed size exclusively to each resident such that the average distance between residents and assigned green spaces is minimized. We contribute a detailed presentation on how to engineer an assignment-based method such that it yields reasonable results (e.g., by considering distances in the road network) and becomes efficient enough for the analysis of large metropolitan areas (e.g., we were able to process an instance of Berlin with about 130000 polygons representing green spaces, 18000 polygons representing residential areas, and 6 million road segments). Furthermore, we show that the optimal assignments resulting from our method enable a subsequent analysis that reveals both interesting global properties of a city as well as spatial patterns. For example, our method allows us to identify neighborhoods with a shortage of green spaces, which will help spatial planners in their decision making.
Cite as
Benjamin Niedermann, Johannes Oehrlein, Sven Lautenbach, and Jan-Henrik Haunert. A Network Flow Model for the Analysis of Green Spaces in Urban Areas. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 13:1-13:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{niedermann_et_al:LIPIcs.GISCIENCE.2018.13,
author = {Niedermann, Benjamin and Oehrlein, Johannes and Lautenbach, Sven and Haunert, Jan-Henrik},
title = {{A Network Flow Model for the Analysis of Green Spaces in Urban Areas}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {13:1--13:16},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.13},
URN = {urn:nbn:de:0030-drops-93412},
doi = {10.4230/LIPIcs.GISCIENCE.2018.13},
annote = {Keywords: urban green, transportation problem, maximum flow, linear program}
}
Document
Continuous Obstructed Detour Queries
Abstract
In this paper, we introduce Continuous Obstructed Detour (COD) Queries, a novel query type in spatial databases. COD queries continuously return the nearest point of interests (POIs) such as a restaurant, an ATM machine and a pharmacy with respect to the current location and the fixed destination of a moving pedestrian in presence of obstacles like a fence, a lake or a private building. The path towards a destination is typically not predetermined and the nearest POIs can change over time with the change of a pedestrian's current location towards a fixed destination. The distance to a POI is measured as the summation of the obstructed distance from the pedestrian's current location to the POI and the obstructed distance from the POI to the pedestrian's destination. Evaluating the query for every change of a pedestrian's location would incur extremely high processing overhead. We develop an efficient solution for COD queries and verify the effectiveness and efficiency of our solution in experiments.
Cite as
Rudra Ranajee Saha, Tanzima Hashem, Tasmia Shahriar, and Lars Kulik. Continuous Obstructed Detour Queries. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 14:1-14:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{saha_et_al:LIPIcs.GISCIENCE.2018.14,
author = {Saha, Rudra Ranajee and Hashem, Tanzima and Shahriar, Tasmia and Kulik, Lars},
title = {{Continuous Obstructed Detour Queries}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {14:1--14:16},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.14},
URN = {urn:nbn:de:0030-drops-93426},
doi = {10.4230/LIPIcs.GISCIENCE.2018.14},
annote = {Keywords: Obstacles Continuous Detour Queries Spatial Databases}
}
Document
Enhanced Multi Criteria Decision Analysis for Planning Power Transmission Lines
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.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
FUTURES-AMR: Towards an Adaptive Mesh Refinement Framework for Geosimulations
Abstract
Adaptive Mesh Refinement (AMR) is a computational technique used to reduce the amount of computation and memory required in scientific simulations. Geosimulations are scientific simulations using geographic data, routinely used to predict outcomes of urbanization in urban studies. However, the lack of support for AMR techniques with geosimulations limits exploring prediction outcomes at multiple resolutions. In this paper, we propose an adaptive mesh refinement framework FUTURES-AMR, based on static user-defined policies to enable multi-resolution geosimulations. We develop a prototype for the cellular automaton based urban growth simulation FUTURES by exploiting static and dynamic mesh refinement techniques in conjunction with the Patch Growing Algorithm (PGA). While, the static refinement technique supports a statically defined fixed resolution mesh simulation at a location, the dynamic refinement technique supports dynamically refining the resolution based on simulation outcomes at runtime. Further, we develop two approaches - asynchronous AMR and synchronous AMR, suitable for parallel execution in a distributed computing environment with varying support for solution integration of the multi-resolution results. Finally, using the FUTURES-AMR framework with different policies in an urban study, we demonstrate reduced execution time, and low memory overhead for a multi-resolution simulation.
Cite as
Ashwin Shashidharan, Ranga Raju Vatsavai, Derek B. Van Berkel, and Ross K. Meentemeyer. FUTURES-AMR: Towards an Adaptive Mesh Refinement Framework for Geosimulations. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 16:1-16:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{shashidharan_et_al:LIPIcs.GISCIENCE.2018.16,
author = {Shashidharan, Ashwin and Vatsavai, Ranga Raju and Van Berkel, Derek B. and Meentemeyer, Ross K.},
title = {{FUTURES-AMR: Towards an Adaptive Mesh Refinement Framework for Geosimulations}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {16:1--16:15},
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.2018.16},
URN = {urn:nbn:de:0030-drops-93440},
doi = {10.4230/LIPIcs.GISCIENCE.2018.16},
annote = {Keywords: Adaptive mesh refinement, Geosimulation, Distributed system, Multi-resolution, Urban geography}
}
Document
xNet+SC: Classifying Places Based on Images by Incorporating Spatial Contexts
Abstract
With recent advancements in deep convolutional neural networks, researchers in geographic information science gained access to powerful models to address challenging problems such as extracting objects from satellite imagery. However, as the underlying techniques are essentially borrowed from other research fields, e.g., computer vision or machine translation, they are often not spatially explicit. In this paper, we demonstrate how utilizing the rich information embedded in spatial contexts (SC) can substantially improve the classification of place types from images of their facades and interiors. By experimenting with different types of spatial contexts, namely spatial relatedness, spatial co-location, and spatial sequence pattern, we improve the accuracy of state-of-the-art models such as ResNet - which are known to outperform humans on the ImageNet dataset - by over 40%. Our study raises awareness for leveraging spatial contexts and domain knowledge in general in advancing deep learning models, thereby also demonstrating that theory-driven and data-driven approaches are mutually beneficial.
Cite as
Bo Yan, Krzysztof Janowicz, Gengchen Mai, and Rui Zhu. xNet+SC: Classifying Places Based on Images by Incorporating Spatial Contexts. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 17:1-17:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{yan_et_al:LIPIcs.GISCIENCE.2018.17,
author = {Yan, Bo and Janowicz, Krzysztof and Mai, Gengchen and Zhu, Rui},
title = {{xNet+SC: Classifying Places Based on Images by Incorporating Spatial Contexts}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {17:1--17:15},
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.2018.17},
URN = {urn:nbn:de:0030-drops-93450},
doi = {10.4230/LIPIcs.GISCIENCE.2018.17},
annote = {Keywords: Spatial context, Image classification, Place types, Convolutional neural network, Recurrent neural network}
}
Document
Short Paper
A Critical Look at Cryptogovernance of the Real World: Challenges for Spatial Representation and Uncertainty on the Blockchain (Short Paper)
Abstract
Innovation in distributed ledger technologies-blockchains and smart contracts-has been lauded as a game-changer for environmental governance and transparency. Here we critically consider how problems related to spatial representation and uncertainty complicate the picture, focusing on two cases. The first regards the impact of uncertainty on the transfer of spatial assets, and the second regards its impact on smart contract code that relies on software oracles that report sensor measurements of the physical world. Cryptogovernance of the environment will require substantial research on both these fronts if it is to become a reality.
Cite as
Benjamin Adams and Martin Tomko. A Critical Look at Cryptogovernance of the Real World: Challenges for Spatial Representation and Uncertainty on the Blockchain (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 18:1-18:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{adams_et_al:LIPIcs.GISCIENCE.2018.18,
author = {Adams, Benjamin and Tomko, Martin},
title = {{A Critical Look at Cryptogovernance of the Real World: Challenges for Spatial Representation and Uncertainty on the Blockchain}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {18:1--18:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.18},
URN = {urn:nbn:de:0030-drops-93465},
doi = {10.4230/LIPIcs.GISCIENCE.2018.18},
annote = {Keywords: spatial information, spatial uncertainty, blockchain, smart contract, environmental management}
}
Document
Short Paper
Towards Optimal Deployment of a Sensor Network in a 3D Indoor Environment for the Mobility of People with Disabilities (Short Paper)
Abstract
Mobility of people with disabilities is one of the most important challenges for their social integration. There have been significant effort to develop assistive technologies to guide the PWD during their mobility in recent years. However, these technologies have limitations when it comes to the navigation and guidance of these people through accessible routes. This is specifically problematic in indoor environments where detection, location and tracking of people, and other dynamic objects that may limit the mobility of these people, are very challenging. Thus, many researches have leveraged the use of sensors to track users and dynamic objects in indoor environments. However, in most of the described methods, the sensors are manually deployed. Due to the complexity of indoor environments, the diversity of sensors and their sensing models, as well as the diversity of the profiles of people with disabilities and their needs during their mobility, the optimal deployment of a sensor network is a challenging task. There exist several optimization methods to maximize coverage and minimize the number of sensors while maintaining the minimum connectivity between the sensor nodes in a network. Most of the current sensor network optimization methods oversimplify the environment and do not consider the complexity of 3D indoor environments. In this paper, we propose a novel 3D local optimization algorithm based on a geometric spatial data structure that takes into account some of these complexities for the purpose of helping PWD in their mobility in 3D indoor environments such as shopping centers, museums and other public buildings.
Cite as
Ali Afghantoloee and Mir Abolfazl Mostafavi. Towards Optimal Deployment of a Sensor Network in a 3D Indoor Environment for the Mobility of People with Disabilities (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 19:1-19:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{afghantoloee_et_al:LIPIcs.GISCIENCE.2018.19,
author = {Afghantoloee, Ali and Mostafavi, Mir Abolfazl},
title = {{Towards Optimal Deployment of a Sensor Network in a 3D Indoor Environment for the Mobility of People with Disabilities}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {19:1--19:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.19},
URN = {urn:nbn:de:0030-drops-93471},
doi = {10.4230/LIPIcs.GISCIENCE.2018.19},
annote = {Keywords: 3D indoor navigation, Sensor network deployment, People with disabilities}
}
Document
Short Paper
Challenges in Creating an Annotated Set of Geospatial Natural Language Descriptions (Short Paper)
Abstract
In order to extract and map location information from natural language descriptions, a first step is to identify different language elements within the descriptions. In this paper, we describe a method and discuss the challenges faced in creating an annotated set of geospatial natural language descriptions using manual tagging, with the purpose of supporting validation and machine learning approaches to annotation and text interpretation.
Cite as
Niloofar Aflaki, Shaun Russell, and Kristin Stock. Challenges in Creating an Annotated Set of Geospatial Natural Language Descriptions (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 20:1-20:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{aflaki_et_al:LIPIcs.GISCIENCE.2018.20,
author = {Aflaki, Niloofar and Russell, Shaun and Stock, Kristin},
title = {{Challenges in Creating an Annotated Set of Geospatial Natural Language Descriptions}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {20:1--20:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.20},
URN = {urn:nbn:de:0030-drops-93482},
doi = {10.4230/LIPIcs.GISCIENCE.2018.20},
annote = {Keywords: Annotation challenges, spatial relations, spatial language}
}
Document
Short Paper
Improved and More Complete Conceptual Model for the Revision of IndoorGML (Short Paper)
Abstract
With the increasing number of indoor navigation applications, it is essential to have clear and complete conceptual model (in the form of UML class diagram) for IndoorGML. The current version of IndoorGML standard has an incomplete class diagram (incomplete w.r.t. attributes, of which some are appearing in the XML/GML schema), and that provides confusion for the users of the standard. Furthermore, there are some issues related to unclear association names, unclear class names, classes that related to the Primal space and the Dual space, code lists not specific per type (which should have their own code list values), untyped relationships to external object classes, and semantically overlapping classes. In this paper, we propose an enhancement for IndoorGML conceptual model (UML class diagram) to avoid the misunderstanding. We propose a conceptual model that maps the classes of the standard in a better way. This conceptual model is the basis for 1) a database schema when storing IndoorGML data, 2) the XML schema when exchanging IndoorGML data, and 3) when developing IndoorGML applications with an intuitive and clear GUI. Furthermore, the proposed conceptual model provides constraints for more meaningful model and to define more sharply what is considered valid data. This paper briefly reports these preliminary results on the UML conceptual model.
Cite as
Abdullah Alattas, Sisi Zlatanova, Peter van Oosterom, and Ki-Joune Li. Improved and More Complete Conceptual Model for the Revision of IndoorGML (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 21:1-21:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{alattas_et_al:LIPIcs.GISCIENCE.2018.21,
author = {Alattas, Abdullah and Zlatanova, Sisi and van Oosterom, Peter and Li, Ki-Joune},
title = {{Improved and More Complete Conceptual Model for the Revision of IndoorGML}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {21:1--21:12},
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.2018.21},
URN = {urn:nbn:de:0030-drops-93491},
doi = {10.4230/LIPIcs.GISCIENCE.2018.21},
annote = {Keywords: Navigation, Space, Boundary, CellSpace}
}
Document
Short Paper
Design for Geospatially Enabled Climate Modeling and Alert System (CLIMSYS): A Position Paper (Short Paper)
Abstract
The paper brings the focus on to multi-disciplinary approach of presenting climate analysis studies, taking help of interdisciplinary fields to structure the information. The system CLIMSYS provides the crucial element of spatially enabling climate data processing. Even though climate change is a matter of great scientific relevance and of broad general interest, there are some problems related to its communication. Its a fact that finding practical, workable and cost-efficient solutions to the problems posed by climate change is now a world priority and one which links government and non-government organizations in a way not seen before. An approach that should suffice is to create an accessible intelligent system that houses prior knowledge and curates the incoming data to deliver meaningful results. The objective of the proposed research is to develop a generalized system for climate data analysis that facilitates open sharing, central implementation, integrated components, knowledge creation, data format understanding, inferencing and ultimately optimal solution delivery, by the way of geospatial enablement.
Cite as
Devanjan Bhattacharya and Marco Painho. Design for Geospatially Enabled Climate Modeling and Alert System (CLIMSYS): A Position Paper (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 22:1-22:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{bhattacharya_et_al:LIPIcs.GISCIENCE.2018.22,
author = {Bhattacharya, Devanjan and Painho, Marco},
title = {{Design for Geospatially Enabled Climate Modeling and Alert System (CLIMSYS): A Position Paper}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {22:1--22:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.22},
URN = {urn:nbn:de:0030-drops-93504},
doi = {10.4230/LIPIcs.GISCIENCE.2018.22},
annote = {Keywords: Spatial enablement, climate modeling, natural hazards, spatial data infrastructure, sensor web}
}
Document
Short Paper
Geographical Exploration and Analysis Extended to Textual Content (Short Paper)
Abstract
Textual and socio-economical regional features can be integrated and merged by linearly combining the between-regions corresponding dissimilarities. The scheme accommodates for various squared Euclidean socio-economical and textual dissimilarities (such as chi2 or cosine dissimilarities derived from document-term matrix or topic modelling). Also, spatial configuration of the regions can be represented by a weighted unoriented network whose vertex weights match the relative importance of regions. Association between the network and the dissimilarities expresses in the multivariate spatial autocorrelation index delta, generalizing Moran's I, whose local version can be cartographied. Our case study bears on the Wikipedia notices and socio-economic profiles for the 2251 Swiss municipalities, whose weights (socio-economical or textual) can be freely chosen.
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Raphaël Ceré, Mattia Egloff, and François Bavaud. Geographical Exploration and Analysis Extended to Textual Content (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 23:1-23:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{cere_et_al:LIPIcs.GISCIENCE.2018.23,
author = {Cer\'{e}, Rapha\"{e}l and Egloff, Mattia and Bavaud, Fran\c{c}ois},
title = {{Geographical Exploration and Analysis Extended to Textual Content}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {23:1--23:7},
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.2018.23},
URN = {urn:nbn:de:0030-drops-93514},
doi = {10.4230/LIPIcs.GISCIENCE.2018.23},
annote = {Keywords: Spatial autocorrelation, Weighted spatial network, Document-term matrix, Multivariate features, Soft clustering}
}
Document
Short Paper
Evaluating Efficiency of Spatial Analysis in Cloud Computing Platforms (Short Paper)
Abstract
The increase of high-resolution spatial data and methodological developments in recent years has enabled a detailed analysis of individuals' experience in space and over time. However, despite the increasing availability of data and technological advances, such individual-level analysis is not always possible in practice because of its computing requirements. To overcome this limitation, there has been a considerable amount of research on the use of high-performance, public cloud computing platforms for spatial analysis and simulation. In this paper, we aim to evaluate the efficiency of spatial analysis in cloud computing platforms. We compared the computing speed for calculating the Moran's I index between a local machine and spot instances on clouds, and our results demonstrated that there could be significant improvements in terms of computing time when the analysis was performed parallel on clouds.
Cite as
Changlock Choi, Yelin Kim, Youngho Lee, and Seong-Yun Hong. Evaluating Efficiency of Spatial Analysis in Cloud Computing Platforms (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 24:1-24:5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{choi_et_al:LIPIcs.GISCIENCE.2018.24,
author = {Choi, Changlock and Kim, Yelin and Lee, Youngho and Hong, Seong-Yun},
title = {{Evaluating Efficiency of Spatial Analysis in Cloud Computing Platforms}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {24:1--24:5},
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.2018.24},
URN = {urn:nbn:de:0030-drops-93521},
doi = {10.4230/LIPIcs.GISCIENCE.2018.24},
annote = {Keywords: spatial analysis, parallel computing, cloud services}
}
Document
Short Paper
Towards the Usefulness of User-Generated Content to Understand Traffic Events (Short Paper)
Abstract
This paper explores the usefulness of Twitter data to detect traffic events and their geographical locations in India through machine learning and NLP. We develop a classification module that can identify tweets relevant for traffic authorities with 0.80 recall accuracy using a Naive Bayes classifier. The proposed model also handles vernacular geographical aspects while retrieving place information from unstructured texts using a multi-layered georeferencing module. This work shows Mumbai has a wide spread use of Twitter for traffic information dissemination with substantial geographical information contributed by the users.
Cite as
Rahul Deb Das and Ross S. Purves. Towards the Usefulness of User-Generated Content to Understand Traffic Events (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 25:1-25:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{das_et_al:LIPIcs.GISCIENCE.2018.25,
author = {Das, Rahul Deb and Purves, Ross S.},
title = {{Towards the Usefulness of User-Generated Content to Understand Traffic Events}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {25:1--25:7},
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.2018.25},
URN = {urn:nbn:de:0030-drops-93539},
doi = {10.4230/LIPIcs.GISCIENCE.2018.25},
annote = {Keywords: Urban mobility, traffic, UGC, tweet, event, GIR, geoparsing}
}
Document
Short Paper
Unfolding Urban Structures: Towards Route Prediction and Automated City Modeling (Short Paper)
Abstract
This paper extends previous work concerning intersection classification by including a new set of statistics that enable to describe the structure of a city at a higher level of detail. Namely, we suggest to analyze sequences of intersections of different types. We start with sequences of length two and present a probabilistic model to derive statistics for longer sequences. We validate the results by comparing them with real frequencies. Finally, we discuss how this work can contribute to the generation of virtual cities as well as to spatial configuration search.
Cite as
Paolo Fogliaroni, Marvin Mc Cutchan, Gerhard Navratil, and Ioannis Giannopoulos. Unfolding Urban Structures: Towards Route Prediction and Automated City Modeling (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 26:1-26:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{fogliaroni_et_al:LIPIcs.GISCIENCE.2018.26,
author = {Fogliaroni, Paolo and Mc Cutchan, Marvin and Navratil, Gerhard and Giannopoulos, Ioannis},
title = {{Unfolding Urban Structures: Towards Route Prediction and Automated City Modeling}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {26:1--26:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.26},
URN = {urn:nbn:de:0030-drops-93548},
doi = {10.4230/LIPIcs.GISCIENCE.2018.26},
annote = {Keywords: intersection types, spatial structure, spatial modeling, graph theory}
}
Document
Short Paper
Deconstructed and Inverted Multi-Criteria Evaluation for On-The-Fly Scenario Development and Decision-Making (Short Paper)
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.
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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
Short Paper
Space-Time Representation of Accessible Areas for Wheelchair Users in Urban Areas (Short Paper)
Abstract
Providing personalized information on the accessibility of urban places for people with disabilities can significantly increase their social participation. This information should be adapted with respect to their needs at the specific time and space. Location-based technologies are considered as proper services to provide such information and encourage mobility of these people in urban areas. However, generally these services focus on the spatial conditions of the accessibility and ignore users' capabilities and time dependent constraints. This is much more challenging for people with disabilities given the diversity of their physical capabilities and preferences. To address this issue, we propose an approach to measure the space-time accessibility of urban areas considering environmental characteristics, users' capabilities, and time constraints. The proposed approach is unique and it highlights time constraint that is rooted in time geography theory. Unlike the classical time geography, which suggests a uniform travel velocity, we consider a variable travel velocity in the proposed approach, which is more relevant to the mobility of people with disabilities. To implement the proposed method, a Fuzzy approach is applied to evaluate the wheelchair speeds for the segments of a pedestrian network. The proposed approach is implemented in Saint-Roch, Quebec City for a case study and the results are presented and discussed.
Cite as
Amin Gharebaghi and Mir Abolfazl Mostafavi. Space-Time Representation of Accessible Areas for Wheelchair Users in Urban Areas (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 28:1-28:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{gharebaghi_et_al:LIPIcs.GISCIENCE.2018.28,
author = {Gharebaghi, Amin and Mostafavi, Mir Abolfazl},
title = {{Space-Time Representation of Accessible Areas for Wheelchair Users in Urban Areas}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {28:1--28:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.28},
URN = {urn:nbn:de:0030-drops-93562},
doi = {10.4230/LIPIcs.GISCIENCE.2018.28},
annote = {Keywords: Mobility, Wheelchair users, Accessibility, Time geography, Potential travel areas}
}
Document
Short Paper
Spatial Periodicity Analysis of Urban Elements Application to the Ancient City of Amida (Short Paper)
Abstract
The characterization of urban structures using morphological indicators is the subject of many applications in the domains of urban planning and transport, but also in less traditional disciplines, such as urban archeology. When reading actual urban plans, it may be possible to identify relics of ancient cities, and to characterize them with the help of appropriate indicators. In this context, we propose a method for the characterization of the spacing between urban elements based on the analysis of their spatial periodicity. The purpose of this method is to detect specific distances in the actual urban structure, potentially characteristic of ancient measurement units. This method is implemented in a GIS software, to facilitate its use by historians and archeologists, and is illustrated by an application on the ancient roman city of Amida (Diyarbakir, Turkey).
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Jean-François Girres, Martine Assenat, Robin Ralite, and Ester Ribo-Delissey. Spatial Periodicity Analysis of Urban Elements Application to the Ancient City of Amida (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 29:1-29:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{girres_et_al:LIPIcs.GISCIENCE.2018.29,
author = {Girres, Jean-Fran\c{c}ois and Assenat, Martine and Ralite, Robin and Ribo-Delissey, Ester},
title = {{Spatial Periodicity Analysis of Urban Elements Application to the Ancient City of Amida}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {29:1--29:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.29},
URN = {urn:nbn:de:0030-drops-93577},
doi = {10.4230/LIPIcs.GISCIENCE.2018.29},
annote = {Keywords: Spatial analysis, Periodicity, Urban structures, Archeology}
}
Document
Short Paper
Gaze Sequences and Map Task Complexity (Short Paper)
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.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
Short Paper
Facilitating the Interoperable Use of Cross-Domain Statistical Data Based on Standardized Identifiers (Short Paper)
Abstract
In the big data era, the successful sharing and integration of data from various resources becomes an essential requirement. As statistical data serves as the foundation for professional domains to report the phenomena in the reality according to the selected administration units, its importance has been well recognized. However, statistical data is typically collected and published by different responsible agencies, hence the heterogeneity of how the data is designed, prepared and disseminated becomes an obstacle impeding the automatic and interoperable use in multidisciplinary applications. From a standardization perspective, this research proposes an identifier-based framework for modeling the spatial, temporal and thematic aspects of cross-domain statistical data, such that any piece of distributed statistical information can be correctly and automatically interpreted without any ambiguity for further analysis and exploration. The results indicate the proposed mechanism successfully enables a comprehensive management of indicators from different resources and enhances the easier data retrieval and correct use across different domains. Meanwhile, the interface design exemplifies an innovated improvement on the presentation and interpretation of statistical information. The proposed solution can be readily implemented for building a transparent sharing environment for the National Spatial Data Infrastructure (NSDI).
Cite as
Jung-Hong Hong and Jing-Cen Yang. Facilitating the Interoperable Use of Cross-Domain Statistical Data Based on Standardized Identifiers (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 31:1-31:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{hong_et_al:LIPIcs.GISCIENCE.2018.31,
author = {Hong, Jung-Hong and Yang, Jing-Cen},
title = {{Facilitating the Interoperable Use of Cross-Domain Statistical Data Based on Standardized Identifiers}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {31:1--31:7},
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.2018.31},
URN = {urn:nbn:de:0030-drops-93595},
doi = {10.4230/LIPIcs.GISCIENCE.2018.31},
annote = {Keywords: Cross-Domain, Statistical Data, Standardized Codes, Visualization}
}
Document
Short Paper
Identification of Geographical Segmentation of the Rental Apartment Market in the Tokyo Metropolitan Area (Short Paper)
Abstract
It is often said that the real estate market is divided geographically in such a manner that the value of attributes of real estate properties is different for each area. This study proposes a new approach to the investigation of the geographical segmentation of the real estate market. We develop a price model with many regional explanatory variables, and implement the generalized fused lasso - a regression method for promoting sparsity - to extract the areas where the valuation standard is the same. The proposed method is applied to rental data of apartments in the Tokyo metropolitan area, and we find that the geographical segmentation displays hierarchal patterns. Specifically, we observe that the market is divided by wards, railway lines and stations, and neighbourhoods.
Cite as
Ryo Inoue, Rihoko Ishiyama, and Ayako Sugiura. Identification of Geographical Segmentation of the Rental Apartment Market in the Tokyo Metropolitan Area (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 32:1-32:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{inoue_et_al:LIPIcs.GISCIENCE.2018.32,
author = {Inoue, Ryo and Ishiyama, Rihoko and Sugiura, Ayako},
title = {{Identification of Geographical Segmentation of the Rental Apartment Market in the Tokyo Metropolitan Area}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {32:1--32:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.32},
URN = {urn:nbn:de:0030-drops-93608},
doi = {10.4230/LIPIcs.GISCIENCE.2018.32},
annote = {Keywords: geographical market segmentations, rental housing market, sparse modelling, generalised fused lasso, Tokyo metropolitan area}
}
Document
Short Paper
Automatic Wall Detection and Building Topology and Property of 2D Floor Plan (Short Paper)
Abstract
Recently, indoor space construction information has been actively carried out primarily in large buildings and in underground facilities. However, the building of this data was done by only a handful of people, and it was a time- and money-intensive task. Therefore, the technology of automatically extracting a wall and constructing a 3D model from architectural floor plans was developed. Complete automation is still limited by accuracy issues, and only a few sets of floor plan data to which the technology can be applied exist. In addition, it is difficult to extract complicated walls and their thickness to build the wall-junction structure of indoor spatial information, which requires significant topological information in the automation process. In this paper, we propose an automatic method of extracting the wall from an architectural floor plan suitable for the restoration of the indoor spatial information according to the indoor spatial information standard.
Cite as
Hanme Jang, Jong Hyeon Yang, and Yu Kiyun. Automatic Wall Detection and Building Topology and Property of 2D Floor Plan (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 33:1-33:5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{jang_et_al:LIPIcs.GISCIENCE.2018.33,
author = {Jang, Hanme and Yang, Jong Hyeon and Kiyun, Yu},
title = {{Automatic Wall Detection and Building Topology and Property of 2D Floor Plan}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {33:1--33:5},
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.2018.33},
URN = {urn:nbn:de:0030-drops-93616},
doi = {10.4230/LIPIcs.GISCIENCE.2018.33},
annote = {Keywords: Image Segmentation, Indoor space, Adjacency matrix, Wall thickness}
}
Document
Short Paper
Mapping Wildlife Species Distribution With Social Media: Augmenting Text Classification With Species Names (Short Paper)
Abstract
Social media has considerable potential as a source of passive citizen science observations of the natural environment, including wildlife monitoring. Here we compare and combine two main strategies for using social media postings to predict species distributions: (i) identifying postings that explicitly mention the target species name and (ii) using a text classifier that exploits all tags to construct a model of the locations where the species occurs. We find that the first strategy has high precision but suffers from low recall, with the second strategy achieving a better overall performance. We furthermore show that even better performance is achieved with a meta classifier that combines data on the presence or absence of species name tags with the predictions from the text classifier.
Cite as
Shelan S. Jeawak, Christopher B. Jones, and Steven Schockaert. Mapping Wildlife Species Distribution With Social Media: Augmenting Text Classification With Species Names (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 34:1-34:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{jeawak_et_al:LIPIcs.GISCIENCE.2018.34,
author = {Jeawak, Shelan S. and Jones, Christopher B. and Schockaert, Steven},
title = {{Mapping Wildlife Species Distribution With Social Media: Augmenting Text Classification With Species Names}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {34:1--34:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.34},
URN = {urn:nbn:de:0030-drops-93626},
doi = {10.4230/LIPIcs.GISCIENCE.2018.34},
annote = {Keywords: Social media, Text mining, Volunteered Geographic Information, Ecology}
}
Document
Short Paper
Multimodal-Transport Collaborative Evacuation Strategies for Urban Serious Emergency Incidents Based on Multi-Sources Spatiotemporal Data (Short Paper)
Abstract
When serious emergency events happen in metropolitan cities where pedestrians and vehicles are in high-density, single modal-transport cannot meet the requirements of quick evacuations. Existing mixed modes of transportation lacks spatiotemporal collaborative ability, which cannot work together to accomplish evacuation tasks in a safe and efficient way. It is of great scientific significance and application value for emergency response to adopt multimodal-transport evacuations and improve their spatial-temporal collaboration ability. However, multimodal-transport evacuation strategies for urban serious emergency event are great challenge to be solved. The reasons lie in that: (1) large-scale urban emergency environment are extremely complicated involving many geographical elements (e.g., road, buildings, over-pass, square, hydrographic net, etc.); (2) Evacuated objects are dynamic and hard to be predicted. (3) the distributions of pedestrians and vehicles are unknown. To such issues, this paper reveals both collaborative and competitive mechanisms of multimodal-transport, and further makes global optimal evacuation strategies from the macro-optimization perspective. Considering detailed geographical environment, pedestrian, vehicle and urban rail transit, a multi-objective multi-dynamic-constraints optimization model for multimodal-transport collaborative emergency evacuation is constructed. Take crowd incidents in Shenzhen as example, empirical experiments with real-world data are conducted to evaluate the evacuation strategies and path planning. It is expected to obtain innovative research achievements on theory and method of urban emergency evacuation in serious emergency events. Moreover, this research results provide spatial-temporal decision support for urban emergency response, which is benefit to constructing smart and safe cities.
Cite as
Jincheng Jiang, Yang Yue, and Shuai He. Multimodal-Transport Collaborative Evacuation Strategies for Urban Serious Emergency Incidents Based on Multi-Sources Spatiotemporal Data (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 35:1-35:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{jiang_et_al:LIPIcs.GISCIENCE.2018.35,
author = {Jiang, Jincheng and Yue, Yang and He, Shuai},
title = {{Multimodal-Transport Collaborative Evacuation Strategies for Urban Serious Emergency Incidents Based on Multi-Sources Spatiotemporal Data}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {35:1--35:8},
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.2018.35},
URN = {urn:nbn:de:0030-drops-93630},
doi = {10.4230/LIPIcs.GISCIENCE.2018.35},
annote = {Keywords: evacuation, multimodal-transport, path planning, disaster system modeling, time geography}
}
Document
Short Paper
A New Map Symbol Design Method for Real-Time Visualization of Geo-Sensor Data (Short Paper)
Abstract
Maps are an excellent way to present data with spatial components. For the large-scale geo-sensors being utilized in recent years, the map-based management and visualization of geo-senor data have become ubiquitous. Without a doubt, managing and visualizing geo-sensor data on maps will have vastly more future applications. However, current maps typically do not support real-time communication in the Internet of Things (IoT), and it is difficult to implement real-time visualization of sensor data on a map. Map symbols are the language of maps. In this paper, we describe a new map symbol design method for geo-sensor data acquisition and visualization on maps. We refer to the sensor data visual method in supervisory control and data acquisition system (SCADA) and apply it to the design process of map symbols. Based on the traditional vector map symbol, the mapping relationship between the sensor data and the graphic element is defined in the map symbol design process. When the map symbol is rendered in the map, the map symbol is integrated into the map layer. The communication module in the map that communicates with the sensor device receives real-time sensor data and triggers a refresh of the map layer according to the mapping profile. All the methods and processes shown herein have been verified in GeoTools.
Cite as
Donglai Jiao and Jintao Sun. A New Map Symbol Design Method for Real-Time Visualization of Geo-Sensor Data (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 36:1-36:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{jiao_et_al:LIPIcs.GISCIENCE.2018.36,
author = {Jiao, Donglai and Sun, Jintao},
title = {{A New Map Symbol Design Method for Real-Time Visualization of Geo-Sensor Data}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {36:1--36:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.36},
URN = {urn:nbn:de:0030-drops-93647},
doi = {10.4230/LIPIcs.GISCIENCE.2018.36},
annote = {Keywords: Sensor, real-time visualization, Internet of Things, map symbols}
}
Document
Short Paper
How Do Texture and Color Communicate Uncertainty in Climate Change Map Displays? (Short Paper)
Abstract
We report on an empirical study with over hundred online participants where we investigated how texture and color value, two popular visual variables used to convey uncertainty in maps, are understood by non-domain-experts. Participants intuit denser dot textures to mean greater attribute certainty; irrespective of whether the dot pattern is labeled certain or uncertain. With this additional empirical evidence, we hope to further improve our understanding of how non-domain experts interpret uncertainty information depicted in map displays. This in turn will allow us to more clearly and legibly communicate uncertainty information in climate change maps, so that these displays can be unmistakably understood by decision-makers and the general public.
Cite as
Irene M. Johannsen, Sara Irina Fabrikant, and Mariele Evers. How Do Texture and Color Communicate Uncertainty in Climate Change Map Displays? (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 37:1-37:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{johannsen_et_al:LIPIcs.GISCIENCE.2018.37,
author = {Johannsen, Irene M. and Fabrikant, Sara Irina and Evers, Mariele},
title = {{How Do Texture and Color Communicate Uncertainty in Climate Change Map Displays?}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {37:1--37:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.37},
URN = {urn:nbn:de:0030-drops-93655},
doi = {10.4230/LIPIcs.GISCIENCE.2018.37},
annote = {Keywords: uncertainty visualization, empirical study, visual variables, climate change}
}
Document
Short Paper
An Analytical Framework for Understanding Urban Functionality from Human Activities (Short Paper)
Abstract
The intertwined relationship between urban functionality and human activity has been widely recognized and quantified with the assistance of big geospatial data. In specific, urban land uses as an important facet of urban structure can be identified from spatiotemporal patterns of aggregate human activities. In this article, we propose a space, time and activity cuboid based analytical framework for clustering urban spaces into different categories of urban functionality based on the variation of activity intensity (T-fiber), mixture (A-fiber) and interaction (I- and O-fiber). The ability of the proposed framework is empirically evaluated by three case studies.
Cite as
Chaogui Kang and Yu Liu. An Analytical Framework for Understanding Urban Functionality from Human Activities (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 38:1-38:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{kang_et_al:LIPIcs.GISCIENCE.2018.38,
author = {Kang, Chaogui and Liu, Yu},
title = {{An Analytical Framework for Understanding Urban Functionality from Human Activities}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {38:1--38:8},
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.2018.38},
URN = {urn:nbn:de:0030-drops-93668},
doi = {10.4230/LIPIcs.GISCIENCE.2018.38},
annote = {Keywords: Urban functionality, Human activity, STA cuboid, Spatiotemporal distribution, Clustering}
}
Document
Short Paper
Application of Style Transfer in the Vectorization Process of Floorplans (Short Paper)
Abstract
As the market for indoor spatial information burgeons, the construction of indoor spatial databases consequently gain attention. Since floorplans are portable records of buildings, they are an indispensable source for the efficient construction of indoor environments. However, as previous research on floorplan information retrieval usually targeted specific formats, a system for constructing spatial information must include heuristic refinement steps. This study aims to convert diverse floorplans into an integrated format using the style transfer by deep networks. Our deep networks mimic a robust perception of human that recognize the cell structure of floorplans under various formats. The integrated format ensures that unified post-processing steps are required to the vectorization of floorplans. Through this process, indoor spatial information is constructed in a pragmatic way, using a plethora of architectural floorplans.
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Seongyong Kim, Seula Park, and Kiyun Yu. Application of Style Transfer in the Vectorization Process of Floorplans (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 39:1-39:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{kim_et_al:LIPIcs.GISCIENCE.2018.39,
author = {Kim, Seongyong and Park, Seula and Yu, Kiyun},
title = {{Application of Style Transfer in the Vectorization Process of Floorplans}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {39:1--39:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.39},
URN = {urn:nbn:de:0030-drops-93672},
doi = {10.4230/LIPIcs.GISCIENCE.2018.39},
annote = {Keywords: Floorplan, Vectorising, Style Transfer, Generative Adversarial Networks}
}
Document
Short Paper
Estimating Building Age from Google Street View Images Using Deep Learning (Short Paper)
Abstract
Building databases are a fundamental component of urban analysis. However such databases usually lack detailed attributes such as building age. With a large volume of building images being accessible online via API (such as Google Street View), as well as the fast development of image processing techniques such as deep learning, it becomes feasible to extract information from images to enrich building databases. This paper proposes a novel method to estimate building age based on the convolutional neural network for image features extraction and support vector machine for construction year regression. The contributions of this paper are two-fold: First, to our knowledge, this is the first attempt for estimating building age from images by using deep learning techniques. It provides new insight for planners to apply image processing and deep learning techniques for building database enrichment. Second, an image-base building age estimation framework is proposed which doesn't require information on building height, floor area, construction materials and therefore makes the analysis process simpler and more efficient.
Cite as
Yan Li, Yiqun Chen, Abbas Rajabifard, Kourosh Khoshelham, and Mitko Aleksandrov. Estimating Building Age from Google Street View Images Using Deep Learning (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 40:1-40:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{li_et_al:LIPIcs.GISCIENCE.2018.40,
author = {Li, Yan and Chen, Yiqun and Rajabifard, Abbas and Khoshelham, Kourosh and Aleksandrov, Mitko},
title = {{Estimating Building Age from Google Street View Images Using Deep Learning}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {40:1--40:7},
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.2018.40},
URN = {urn:nbn:de:0030-drops-93682},
doi = {10.4230/LIPIcs.GISCIENCE.2018.40},
annote = {Keywords: Building database, deep learning, CNN, SVM, Google Street View}
}
Document
Short Paper
Center Point of Simple Area Feature Based on Triangulation Skeleton Graph (Short Paper)
Abstract
In the area of cartography and geographic information science, the center points of area features are related to many fields. The centroid is a conventional choice of center point of area feature. However, it is not suitable for features with a complex shape for the center point may be outside the area or not fit the visual center so well. This paper proposes a novel method to calculate the center point of area feature based on triangulation skeleton graph. This paper defines two kinds of centrality of vertices in skeleton graph according to the centrality theory in graph and network analysis. Through the measurement of vertices centrality, the center points of polygon area features are defined as the vertices with maximum centrality.
Cite as
Wei Lu and Tinghua Ai. Center Point of Simple Area Feature Based on Triangulation Skeleton Graph (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 41:1-41:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{lu_et_al:LIPIcs.GISCIENCE.2018.41,
author = {Lu, Wei and Ai, Tinghua},
title = {{Center Point of Simple Area Feature Based on Triangulation Skeleton Graph}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {41:1--41:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.41},
URN = {urn:nbn:de:0030-drops-93699},
doi = {10.4230/LIPIcs.GISCIENCE.2018.41},
annote = {Keywords: Shape Center, Triangulation Skeleton Graph, Graph Centrality}
}
Document
Short Paper
The Use of Particle Swarm Optimization for a Vector Cellular Automata Model of Land Use Change (Short Paper)
Abstract
Cellular automata (CA) is an important area of research in GIScience, with recent research developing vector-based models in addition to the traditional raster data formats. One active area of research is the calibration of transition rules, particularly when applied to vector CA. Here we evaluate a particle swarm optimization (PSO) process to calibrate a vector CA model of land use change for a sub-region of Ipswich in Queensland, Australia, for the period 1999-2016. We compare the results with those for a raster CA of the same dataset. The spatial indices of the vector PSO-CA model exceed that of the raster model, with spatial accuracies being 82.45% and 76.47%, respectively. In addition, the vector PSO-CA model achieved a higher kappa coefficient. Vector-based PSO-CA model can be used for the exploration of urbanization process and provide a better understanding of land use change.
Cite as
Yi Lu and Shawn Laffan. The Use of Particle Swarm Optimization for a Vector Cellular Automata Model of Land Use Change (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 42:1-42:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{lu_et_al:LIPIcs.GISCIENCE.2018.42,
author = {Lu, Yi and Laffan, Shawn},
title = {{The Use of Particle Swarm Optimization for a Vector Cellular Automata Model of Land Use Change}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {42:1--42:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.42},
URN = {urn:nbn:de:0030-drops-93702},
doi = {10.4230/LIPIcs.GISCIENCE.2018.42},
annote = {Keywords: Vector cellular automata (CA), Particle swarm optimization (PSO), Land use simulation, Ipswich}
}
Document
Short Paper
Towards a Comprehensive Temporal Classification of Footfall Patterns in the Cities of Great Britain (Short Paper)
Abstract
The temporal fluctuations of footfall in the urban areas have long been a neglected research problem, and this mainly has to do with the past technological limitations and inability to consistently collect large volumes of data at fine intra-day temporal resolutions. This paper makes use of the extensive set of footfall measurements acquired by the Wi-Fi sensors installed in the retail units across the British town centres, shopping centres and retail parks. We present the methodology for classifying the diurnal temporal signatures of human activity at the urban microsite locations and identify characteristic profiles which make them distinctive regarding when people visit them. We conclude that there exist significant differences regarding the time when different locations are the busiest during the day, and this undoubtedly has a substantial impact on how retailers should plan where and how their businesses operate.
Cite as
Karlo Lugomer and Paul Longley. Towards a Comprehensive Temporal Classification of Footfall Patterns in the Cities of Great Britain (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 43:1-43:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{lugomer_et_al:LIPIcs.GISCIENCE.2018.43,
author = {Lugomer, Karlo and Longley, Paul},
title = {{Towards a Comprehensive Temporal Classification of Footfall Patterns in the Cities of Great Britain}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {43:1--43:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.43},
URN = {urn:nbn:de:0030-drops-93718},
doi = {10.4230/LIPIcs.GISCIENCE.2018.43},
annote = {Keywords: temporal classification, temporal profiles, time series cluster analysis, Wi-Fi sensors, retail analytics}
}
Document
Short Paper
Is This Statement About A Place? Comparing two perspectives (Short Paper)
Abstract
Text often includes references to places by name; in prior work, more than 20% of a sample of event-related tweets were found to include place names. Research has addressed the challenge of leveraging the geographic data reflected in text statements, with well-developed methods to recognize location mentions in text and related work on automated toponym resolution (deciding which place in the world is meant by a place name). A core issue that remains is to distinguish between text that mentions a place or places and text that is about a place or places. This paper presents the first step in research to address this challenge. The research reported here sets the conceptual and practical groundwork for subsequent supervised machine learning research; that research will leverage human-produced training data, for which a judgment is made about whether a statement is or is not about a place (or places), to train computational methods to do this classification for large volumes of text. The research step presented here focuses on three questions: (1) what kinds of entities are typically conceptualized as places, (2) what features of a statement prompt the reader to judge a statement to be about a place (or not about a place) and (3) how do judgments of whether or not a statement is about a place compare between a group of experts who have studied the concept of "place" from a geographic perspective and a cross-section of individuals recruited through a crowdsourcing platform to make these judgments.
Cite as
Alan M. MacEachren, Richard Caneba, Hanzhou Chen, Harrison Cole, Emily Domanico, Nicholas Triozzi, Fangcao Xu, and Liping Yang. Is This Statement About A Place? Comparing two perspectives (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 44:1-44:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{maceachren_et_al:LIPIcs.GISCIENCE.2018.44,
author = {MacEachren, Alan M. and Caneba, Richard and Chen, Hanzhou and Cole, Harrison and Domanico, Emily and Triozzi, Nicholas and Xu, Fangcao and Yang, Liping},
title = {{Is This Statement About A Place? Comparing two perspectives}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {44:1--44:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.44},
URN = {urn:nbn:de:0030-drops-93720},
doi = {10.4230/LIPIcs.GISCIENCE.2018.44},
annote = {Keywords: geographic information retrieval, spatial language, crowdsourcing}
}
Document
Short Paper
Geospatial Semantics for Spatial Prediction (Short Paper)
Abstract
In this paper the potential of geospatial semantics for spatial predictions is explored. Therefore data from the LinkedGeoData platform is used to predict landcover classes described by the CORINE dataset. Geo-objects obtained from LinkedGeoData are described by an OWL ontology, which is utilized for the purpose of spatial prediction within this paper. This prediction is based on an association analysis which computes the collocations between the landcover classes and the semantically described geo-objects. The paper provides an analysis of the learned association rules and finally concludes with a discussion on the promising potential of geospatial semantics for spatial predictions, as well as potentially fruitful future research within this domain.
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Marvin Mc Cutchan and Ioannis Giannopoulos. Geospatial Semantics for Spatial Prediction (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 45:1-45:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{mccutchan_et_al:LIPIcs.GISCIENCE.2018.45,
author = {Mc Cutchan, Marvin and Giannopoulos, Ioannis},
title = {{Geospatial Semantics for Spatial Prediction}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {45:1--45:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.45},
URN = {urn:nbn:de:0030-drops-93731},
doi = {10.4230/LIPIcs.GISCIENCE.2018.45},
annote = {Keywords: Geospatial semantics, spatial prediction, machine learning, Linked Data}
}
Document
Short Paper
Docked vs. Dockless Bike-sharing: Contrasting Spatiotemporal Patterns (Short Paper)
Abstract
U.S. urban centers are currently experiencing explosive growth in commercial dockless bike-sharing services. Tens of thousands of bikes have shown up across the country in recent months providing limited time for municipal governments to set regulations or assess their impact on government-funded dock-based bike-sharing programs. Washington, D.C. offers an unprecedented opportunity to examine the activity patterns of both docked and dockless bike-sharing services given the history of bike-sharing in the city and the recent availability of dockless bike data. This work presents an exploratory step in understanding how dockless bike-sharing services are being used within a city and the ways in which the activity patterns differ from traditional dock station-based programs.
Cite as
Grant McKenzie. Docked vs. Dockless Bike-sharing: Contrasting Spatiotemporal Patterns (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 46:1-46:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{mckenzie:LIPIcs.GISCIENCE.2018.46,
author = {McKenzie, Grant},
title = {{Docked vs. Dockless Bike-sharing: Contrasting Spatiotemporal Patterns}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {46:1--46:7},
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.2018.46},
URN = {urn:nbn:de:0030-drops-93746},
doi = {10.4230/LIPIcs.GISCIENCE.2018.46},
annote = {Keywords: bike-share, dockless, bicycle, transportation, spatiotemporal patterns}
}
Document
Short Paper
OpenPOI: An Open Place of Interest Platform (Short Paper)
Abstract
Places of Interest (POI) are a principal component of how human behavior is captured in today's geographic information. Increasingly, access to POI datasets are being restricted - even silo-ed - for commercial use, with vendors often impeding access to the very users that contribute the data. Open mapping platforms such as OpenStreetMap (OSM) offer access to a plethora of geospatial data though they can be limited in the attribute resolution or range of information associated with the data. Nuanced descriptive information associated with POI, e.g., ambience, are not captured by such platforms. Furthermore, interactions with a POI, such as checking in, or recommending a menu item, are inherently place-based concepts. Many of these interactions occur with high temporal volatility that involves frequent interaction with a platform, arguably inappropriate for the "changeset" model adopted by OSM and related datasets. In this short paper we propose OpenPOI, an open platform for storing, serving, and interacting with places of interests and the activities they afford.
Cite as
Grant McKenzie and Krzysztof Janowicz. OpenPOI: An Open Place of Interest Platform (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 47:1-47:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{mckenzie_et_al:LIPIcs.GISCIENCE.2018.47,
author = {McKenzie, Grant and Janowicz, Krzysztof},
title = {{OpenPOI: An Open Place of Interest Platform}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {47:1--47:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.47},
URN = {urn:nbn:de:0030-drops-93752},
doi = {10.4230/LIPIcs.GISCIENCE.2018.47},
annote = {Keywords: place, point of interest, open data, gazetteer, check-in}
}
Document
Short Paper
Exploring Shifting Densities through a Movement-based Cartographic Interface (Short Paper)
Abstract
Animated maps are widely used for representing shifting densities. Though there is evidence that animations can provide better memory recall than static charts, it could be a consequence of using better techniques for animation than for static representations. However, the lack of control makes them frustrating for users, while animated choropleth maps can cause change blindness. In this paper, we propose an interactive animation technique which employs the lenticular printing metaphor and benefits from the user's proprioceptive sense to explore density changes over time. We hypothesized that using a tangible interface based on the body movement would improve memory recall and, consequently, animated map reading.
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Aline Menin, Sonia Chardonnel, Paule-Annick Davoine, and Luciana Nedel. Exploring Shifting Densities through a Movement-based Cartographic Interface (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 48:1-48:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{menin_et_al:LIPIcs.GISCIENCE.2018.48,
author = {Menin, Aline and Chardonnel, Sonia and Davoine, Paule-Annick and Nedel, Luciana},
title = {{Exploring Shifting Densities through a Movement-based Cartographic Interface}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {48:1--48:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.48},
URN = {urn:nbn:de:0030-drops-93764},
doi = {10.4230/LIPIcs.GISCIENCE.2018.48},
annote = {Keywords: proprioceptive interaction, lenticular technique, shifting densities, tangible interfaces, mobility analysis}
}
Document
Short Paper
Geotagging Location Information Extracted from Unstructured Data (Short Paper)
Abstract
Location information is an essential element of location-based services and is used in various ways. Unstructured data contain different types of location information, but coordinate values are required to determine the exact location. In Twitter, a typical social network service (SNS) platform of unstructured data, the number of geotagged tweets is low. If we can estimate the location of text by geotagging a large number of unstructured data, we can estimate the location of the event in real-time. This study is a base study on extracting the location information by using the named entity recognizer provided by the Exobrain API and applying geotagging to unstructured data in Hangul (Korean). We used Chosun news articles, which are grammatically correct and well organized, instead of tweets to extract three location-related categories, namely "location," "organization," and "artifact". We used the named entity recognizer and geotagged each sentence in combination of the fields in each category. The results of the study showed that 61% of the 800 test sentences did not have the location-related information, thus hindering geotagging. In 11.75% of the test sentences, geotagging was possible with only the given location information extracted using the named entity recognizer. The remaining 27.25% of the sentences contained information on more than two locations from the same subcategories and hence required location estimation from candidate locations. In future research, we plan to apply the results of this study to develop location estimation algorithm that makes use of the extracted location-related entities from purely unstructured data such as that on SNSs.
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Kyunghyun Min, Jungseok Lee, Kiyun Yu, and Jiyoung Kim. Geotagging Location Information Extracted from Unstructured Data (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 49:1-49:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{min_et_al:LIPIcs.GISCIENCE.2018.49,
author = {Min, Kyunghyun and Lee, Jungseok and Yu, Kiyun and Kim, Jiyoung},
title = {{Geotagging Location Information Extracted from Unstructured Data}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {49:1--49:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.49},
URN = {urn:nbn:de:0030-drops-93778},
doi = {10.4230/LIPIcs.GISCIENCE.2018.49},
annote = {Keywords: Location Estimation, Information Extraction, Geo-Tagging, Location Information, Unstructured Data}
}
Document
Short Paper
Linked Open Data Vocabularies for Semantically Annotated Repositories of Data Quality Measures (Short Paper)
Abstract
The fitness for purpose concerns many different aspects of data quality. These aspects are usually assessed independently by different data quality measures. However, for the assessment of the fitness for purpose, a holistic understanding of these aspects is needed. In this paper we discuss two Linked Open Data vocabularies for formally describing measures and their relations. These vocabularies can be used to semantically annotate repositories of data quality measures, which accordingly adhere to common standards even if being distributed on multiple servers. This allows for a better understanding of how data quality measures relate and mutually constrain. As a result, it becomes possible to improve intrinsic data quality measures by evaluating their effectivity and by combining them.
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Franz-Benjamin Mocnik. Linked Open Data Vocabularies for Semantically Annotated Repositories of Data Quality Measures (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 50:1-50:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{mocnik:LIPIcs.GISCIENCE.2018.50,
author = {Mocnik, Franz-Benjamin},
title = {{Linked Open Data Vocabularies for Semantically Annotated Repositories of Data Quality Measures}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {50:1--50:7},
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.2018.50},
URN = {urn:nbn:de:0030-drops-93786},
doi = {10.4230/LIPIcs.GISCIENCE.2018.50},
annote = {Keywords: data quality, measure, semantics, Linked Open Data (LOD), vocabulary, repository, reproducibility, OpenStreetMap (OSM)}
}
Document
Short Paper
Need A Boost? A Comparison of Traditional Commuting Models with the XGBoost Model for Predicting Commuting Flows (Short Paper)
Abstract
Commuting models estimate the number of commuting trips from home to work locations in a given area. Since their infancy, they have been increasingly used in a variety of fields to reduce traffic and pollution, drive infrastructure choices, and solve a variety of other problems. Traditional commuting models, such as gravity and radiation models, typically have a strict structural form and limited number of input variables, which may limit their ability to predict commuting flows as well as machine learning models that might better capture the complex dynamics of the commuting process. To determine whether machine learning models might add value to the field of commuter flow prediction, we compare and discuss the performance of two standard traditional models with the XGBoost machine learning algorithm for predicting home to work commuter flows from a well-known United States commuting dataset. We find that the XGBoost model outperforms the traditional models on three commonly used metrics, indicating that machine learning models may add value to the field of commuter flow prediction.
Cite as
April Morton, Jesse Piburn, and Nicholas Nagle. Need A Boost? A Comparison of Traditional Commuting Models with the XGBoost Model for Predicting Commuting Flows (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 51:1-51:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{morton_et_al:LIPIcs.GISCIENCE.2018.51,
author = {Morton, April and Piburn, Jesse and Nagle, Nicholas},
title = {{Need A Boost? A Comparison of Traditional Commuting Models with the XGBoost Model for Predicting Commuting Flows}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {51:1--51:7},
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.2018.51},
URN = {urn:nbn:de:0030-drops-93793},
doi = {10.4230/LIPIcs.GISCIENCE.2018.51},
annote = {Keywords: Machine learning, commuting modeling}
}
Document
Short Paper
Modeling Road Traffic Takes Time (Short Paper)
Abstract
To model dynamic road traffic environment, it is imperative to integrate spatial and temporal knowledge about its evolution into a single model. This paper introduces temporal dimension which provides a method to reason about time-varying spatial information in a spatio-temporal graph-based model. Two types of evolution, topological and attributed, of time-varying graph (TVG) are considered which require the time domain to be discrete and/or continuous, and the TVG proposed includes time-varying node/edge presence and labeling functions. Theoretical concepts presented in this paper will guide us through the process of application development in future.
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Kamaldeep Singh Oberoi, Géraldine Del Mondo, Yohan Dupuis, and Pascal Vasseur. Modeling Road Traffic Takes Time (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 52:1-52:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{oberoi_et_al:LIPIcs.GISCIENCE.2018.52,
author = {Oberoi, Kamaldeep Singh and Del Mondo, G\'{e}raldine and Dupuis, Yohan and Vasseur, Pascal},
title = {{Modeling Road Traffic Takes Time}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {52:1--52:7},
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.2018.52},
URN = {urn:nbn:de:0030-drops-93806},
doi = {10.4230/LIPIcs.GISCIENCE.2018.52},
annote = {Keywords: Qualitative Spatio-temporal Model, Time Varying Graph, Road Traffic, Intelligent Transportation Systems}
}
Document
Short Paper
Diversity in Spatial Language Within Communities: The Interplay of Culture, Language and Landscape in Representations of Space (Short Paper)
Abstract
Significant diversity exists in the way languages structure spatial reference, and this has been shown to correlate with diversity in non-linguistic spatial behaviour. However, most research in spatial language has focused on diversity between languages: on which spatial referential strategies are represented in the grammar, and to a lesser extent which of these strategies are preferred overall in a given language. However, comparing languages as a whole and treating each language as a single data point provides a very partial picture of linguistic spatial behaviour, failing to recognise the very significant diversity that exists within languages, a largely under-investigated but now emerging field of research. This paper focuses on language-internal diversity, and on the central role of a range of sociocultural and demographic factors that intervene in the relationship between humans, languages, and the physical environments in which communities live.
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Bill Palmer, Alice Gaby, Jonathon Lum, and Jonathan Schlossberg. Diversity in Spatial Language Within Communities: The Interplay of Culture, Language and Landscape in Representations of Space (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 53:1-53:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{palmer_et_al:LIPIcs.GISCIENCE.2018.53,
author = {Palmer, Bill and Gaby, Alice and Lum, Jonathon and Schlossberg, Jonathan},
title = {{Diversity in Spatial Language Within Communities: The Interplay of Culture, Language and Landscape in Representations of Space}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {53:1--53:8},
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.2018.53},
URN = {urn:nbn:de:0030-drops-93810},
doi = {10.4230/LIPIcs.GISCIENCE.2018.53},
annote = {Keywords: spatial language, Frame of Reference, landscape, sociotopography}
}
Document
Short Paper
Flexible Patterns of Place for Function-based Search of Space (Short Paper)
Abstract
Place is a human interpretation of space; it augments the latter with information related to human activities, services, emotions and so forth. Searching for places rather than traditional space-based search represents significant challenges. The most prevalent method of addressing place-related queries is based on placenames but has limited potential due to the vagueness of natural language and its tendency to lead to ambiguous interpretations. In previous work we proposed a system-oriented formalization of place that goes beyond placenames by introducing composition patterns of place. In this study, we introduce flexibility into these patterns in terms of what is necessarily or possibly included when describing the spatial composition of a place and propose a novel automated process of extracting these patterns relying on both theoretical and empirical knowledge. The proposed methodology is exemplified through the use case of locating all the shopping areas within London, UK.
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Emmanuel Papadakis, Andreas Petutschnig, and Thomas Blaschke. Flexible Patterns of Place for Function-based Search of Space (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 54:1-54:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{papadakis_et_al:LIPIcs.GISCIENCE.2018.54,
author = {Papadakis, Emmanuel and Petutschnig, Andreas and Blaschke, Thomas},
title = {{Flexible Patterns of Place for Function-based Search of Space}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {54:1--54:7},
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.2018.54},
URN = {urn:nbn:de:0030-drops-93825},
doi = {10.4230/LIPIcs.GISCIENCE.2018.54},
annote = {Keywords: Functions, Place, Patterns, Function-based search, Place-based GIS}
}
Document
Short Paper
Novel Models for Multi-Scale Spatial and Temporal Analyses (Short Paper)
Abstract
Multi-scale analysis for spatio-temporal data forms a fundamental challenge for many analytic systems. In geographic information systems, analysis and modeling at pre-defined spatial and temporal scales may miss critical relationships in other scales. Previous studies have investigated the uses of the triangle model as a multi-scale framework in analyzing temporal data. This article demonstrates the utilities of the triangle model and pyramid model for multi-scale spatial analysis through real-world analytical tasks and discusses the potential of developing a unified modeling framework that integrates the two models.
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Yi Qiang, Barbara P. Buttenfield, Nina Lam, and Nico Van de Weghe. Novel Models for Multi-Scale Spatial and Temporal Analyses (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 55:1-55:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{qiang_et_al:LIPIcs.GISCIENCE.2018.55,
author = {Qiang, Yi and Buttenfield, Barbara P. and Lam, Nina and Van de Weghe, Nico},
title = {{Novel Models for Multi-Scale Spatial and Temporal Analyses}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {55:1--55:7},
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.2018.55},
URN = {urn:nbn:de:0030-drops-93832},
doi = {10.4230/LIPIcs.GISCIENCE.2018.55},
annote = {Keywords: Triangle Model, Pyramid Model, multi-scale spatial and temporal analysis, GIS}
}
Document
Short Paper
Geosocial Media Data as Predictors in a GWR Application to Forecast Crime Hotspots (Short Paper)
Abstract
In this paper we forecast hotspots of street crime in Portland, Oregon. Our approach uses geosocial media posts, which define the predictors in geographically weighted regression (GWR) models. We use two predictors that are both derived from Twitter data. The first one is the population at risk of being victim of street crime. The second one is the crime related tweets. These two predictors were used in GWR to create models that depict future street crime hotspots. The predicted hotspots enclosed more than 23% of the future street crimes in 1% of the study area and also outperformed the prediction efficiency of a baseline approach. Future work will focus on optimizing the prediction parameters and testing the applicability of this approach to other mobile crime types.
Cite as
Alina Ristea, Ourania Kounadi, and Michael Leitner. Geosocial Media Data as Predictors in a GWR Application to Forecast Crime Hotspots (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 56:1-56:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{ristea_et_al:LIPIcs.GISCIENCE.2018.56,
author = {Ristea, Alina and Kounadi, Ourania and Leitner, Michael},
title = {{Geosocial Media Data as Predictors in a GWR Application to Forecast Crime Hotspots}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {56:1--56:7},
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.2018.56},
URN = {urn:nbn:de:0030-drops-93845},
doi = {10.4230/LIPIcs.GISCIENCE.2018.56},
annote = {Keywords: spatial crime prediction, street crime, population at risk, geographically weighted regression, geosocial media}
}
Document
Short Paper
Who Masks? Correlates of Individual Location-Masking Behavior in an Online Survey (Short Paper)
Abstract
Geomasking traditionally refers to a set of techniques employed by a data steward to protect the privacy of data subjects by altering geographic coordinates. Data subjects themselves may make efforts to obfuscate their location data and protect their geoprivacy. Among these individual-level strategies are providing incorrect address data, limiting the precision of address data, or map-based location masking. This study examines the prevalence of these three location-masking behaviors in an online survey of California residents, finding that such behavior takes place across social groups. There are no significant differences across income level, education, ethnicity, sex, and urban locations. Instead, the primary differences are linked to intervening variables of knowledge and attitudes about location privacy.
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Dara E. Seidl and Piotr Jankowski. Who Masks? Correlates of Individual Location-Masking Behavior in an Online Survey (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 57:1-57:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{seidl_et_al:LIPIcs.GISCIENCE.2018.57,
author = {Seidl, Dara E. and Jankowski, Piotr},
title = {{Who Masks? Correlates of Individual Location-Masking Behavior in an Online Survey}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {57:1--57:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.57},
URN = {urn:nbn:de:0030-drops-93850},
doi = {10.4230/LIPIcs.GISCIENCE.2018.57},
annote = {Keywords: privacy, geoprivacy, geomasking, obfuscation, accuracy}
}
Document
Short Paper
Dynamically-Spaced Geo-Grid Segmentation for Weighted Point Sampling on a Polygon Map Layer (Short Paper)
Abstract
Geo-grid algorithms divide a large polygon area into several smaller polygons, which are important for studying or executing a set of operations on underlying topological features of a map. The current geo-grid algorithms divide a large polygon in to a set of smaller but equal size polygons only (e.g. is ArcMaps Fishnet). The time to create a geo-grid is typically proportional to number of smaller polygons created. This raises two problems - (i) They cannot skip unwanted areas (such as water bodies, given about 71% percent of the Earth's surface is water-covered); (ii) They are incognizant to any underlying feature set that requires more deliberation. In this work, we propose a novel dynamically spaced geo-grid segmentation algorithm that overcomes these challenges and provides a computationally optimal output for borderline cases of an uneven polygon. Our method uses an underlying topological feature of population distributions, from the LandScan Global 2016 dataset, for creating grids as a function of these weighted features. We benchmark our results against available algorithms and found our approach improves geo-grid creation. Later on, we demonstrate the proposed approach is more effective in harvesting Points of Interest data from a crowd-sourced platform.
Cite as
Kelly Sims, Gautam Thakur, Kevin Sparks, Marie Urban, Amy Rose, and Robert Stewart. Dynamically-Spaced Geo-Grid Segmentation for Weighted Point Sampling on a Polygon Map Layer (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 58:1-58:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{sims_et_al:LIPIcs.GISCIENCE.2018.58,
author = {Sims, Kelly and Thakur, Gautam and Sparks, Kevin and Urban, Marie and Rose, Amy and Stewart, Robert},
title = {{Dynamically-Spaced Geo-Grid Segmentation for Weighted Point Sampling on a Polygon Map Layer}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {58:1--58:7},
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.2018.58},
URN = {urn:nbn:de:0030-drops-93860},
doi = {10.4230/LIPIcs.GISCIENCE.2018.58},
annote = {Keywords: geofence, geo-grid, quadtree, points of interest (POI), volunteered geographic information (VGI)}
}
Document
Short Paper
The Landform Reference Ontology (LFRO): A Foundation for Exploring Linguistic and Geospatial Conceptualization of Landforms (Short Paper)
Abstract
The landform reference ontology (LFRO) formalizes ontological distinctions underlying naïve geographic cognition and reasoning about landforms. The LFRO taxonomy is currently based only on form-based distinctions. In this significantly revised version, several new categories have been added to explicate ontological distinctions related to material-spatial dependence and physical support. Nuances of common natural language landform terms and implications for their mapping are discussed.
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Gaurav Sinha, Samantha T. Arundel, Torsten Hahmann, E. Lynn Usery, Kathleen Stewart, and David M. Mark. The Landform Reference Ontology (LFRO): A Foundation for Exploring Linguistic and Geospatial Conceptualization of Landforms (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 59:1-59:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{sinha_et_al:LIPIcs.GISCIENCE.2018.59,
author = {Sinha, Gaurav and Arundel, Samantha T. and Hahmann, Torsten and Usery, E. Lynn and Stewart, Kathleen and Mark, David M.},
title = {{The Landform Reference Ontology (LFRO): A Foundation for Exploring Linguistic and Geospatial Conceptualization of Landforms}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {59:1--59:7},
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.2018.59},
URN = {urn:nbn:de:0030-drops-93873},
doi = {10.4230/LIPIcs.GISCIENCE.2018.59},
annote = {Keywords: landform, reference ontology, terrain reasoning, dependence, support}
}
Document
Short Paper
Abstract Data Types for Spatio-Temporal Remote Sensing Analysis (Short Paper)
Abstract
Abstract data types are a helpful framework to formalise analyses and make them more transparent, reproducible and comprehensible. We are revisiting an approach based on the space, time and theme dimensions of remotely sensed data, and extending it with a more differentiated understanding of space-time representations. In contrast to existing approaches and implementations that consider only fixed spatial units (e.g. pixels), our approach allows investigations of the spatial units' spatio-temporal characteristics, such as the size and shape of their geometry, and their relationships. Five different abstract data types are identified to describe geographical phenomenon, either directly or in combination: coverage, time series, trajectory, composition and evolution.
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Martin Sudmanns, Stefan Lang, Dirk Tiede, Christian Werner, Hannah Augustin, and Andrea Baraldi. Abstract Data Types for Spatio-Temporal Remote Sensing Analysis (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 60:1-60:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{sudmanns_et_al:LIPIcs.GISCIENCE.2018.60,
author = {Sudmanns, Martin and Lang, Stefan and Tiede, Dirk and Werner, Christian and Augustin, Hannah and Baraldi, Andrea},
title = {{Abstract Data Types for Spatio-Temporal Remote Sensing Analysis}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {60:1--60:7},
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.2018.60},
URN = {urn:nbn:de:0030-drops-93881},
doi = {10.4230/LIPIcs.GISCIENCE.2018.60},
annote = {Keywords: Big Earth Data, Semantic Analysis, Data Cube}
}
Document
Short Paper
Towards Vandalism Detection in OpenStreetMap Through a Data Driven Approach (Short Paper)
Abstract
Vandalism is a phenomenon that has affected by now the digital domain, in particular in the context of Volunteered Geographic Information projects. This paper aims at proposing a methodology to detect vandalism in the OpenStreetMap project. First, an analysis of related works sheds light on the lack of consensus when it comes to defining vandalism in VGI from both conceptual and practical points of view. Second, we present experiments on the use of clustering-based outlier detection methods to identify vandalism in OSM. The outcome of this study focuses on choosing the right variables when it comes to detecting vandalism in OSM.
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Quy Thy Truong, Guillaume Touya, and Cyril de Runz. Towards Vandalism Detection in OpenStreetMap Through a Data Driven Approach (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 61:1-61:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{truong_et_al:LIPIcs.GISCIENCE.2018.61,
author = {Truong, Quy Thy and Touya, Guillaume and de Runz, Cyril},
title = {{Towards Vandalism Detection in OpenStreetMap Through a Data Driven Approach}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {61:1--61:7},
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.2018.61},
URN = {urn:nbn:de:0030-drops-93897},
doi = {10.4230/LIPIcs.GISCIENCE.2018.61},
annote = {Keywords: Vandalism, Volunteered Geographic Information, Outlier detection}
}
Document
Short Paper
A Conceptual Framework for Representation of Location-based Social Media Activities (Short Paper)
Abstract
This research develops a conceptual framework for the representation and analysis of location-based social media activities (LBSMA) in GIS. With increasing popularity of location-based social networking, social media platforms have become new channels to observe human activities in physical and virtual worlds. At the same time, there is a shift of some human interactions from the physical space to the virtual social space. Traditional geographical representation in GIS is not sufficient to handle the increased sophistication of human activities related to, or embedded in, location-based social media data. This research proposes an ontology for the location-based social media activity data and a conceptual framework for them to be modeled in a GIS environment so that interconnections of human activities in spatial-temporal-social dimensions can be represented, organized, retrieved, analyzed, and visualized in the system.
Cite as
Xuebin Wei and Xiaobai Angela Yao. A Conceptual Framework for Representation of Location-based Social Media Activities (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 62:1-62:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{wei_et_al:LIPIcs.GISCIENCE.2018.62,
author = {Wei, Xuebin and Yao, Xiaobai Angela},
title = {{A Conceptual Framework for Representation of Location-based Social Media Activities}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {62:1--62:7},
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.2018.62},
URN = {urn:nbn:de:0030-drops-93902},
doi = {10.4230/LIPIcs.GISCIENCE.2018.62},
annote = {Keywords: GIS, Social Media, Ontology, Location-based Social Media Activity}
}
Document
Short Paper
Towards the Statistical Analysis and Visualization of Places (Short Paper)
Abstract
The concept of place recently gains momentum in GIScience. In some fields like human geography, spatial cognition or information theory, this topic already has a longer scholarly tradition. This is however not yet completely the case with statistical spatial analysis and cartography. Despite that, taking full advantage of the plethora of user-generated information that we have available these days requires mature place-based statistical and visualization concepts. This paper contributes to these developments: We integrate existing place definitions into an understanding of places as a system of interlinked, constituent characteristics. Based on this, challenges and first promising conceptual ideas are discussed from statistical and visualization viewpoints.
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René Westerholt, Mathias Gröbe, Alexander Zipf, and Dirk Burghardt. Towards the Statistical Analysis and Visualization of Places (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 63:1-63:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{westerholt_et_al:LIPIcs.GISCIENCE.2018.63,
author = {Westerholt, Ren\'{e} and Gr\"{o}be, Mathias and Zipf, Alexander and Burghardt, Dirk},
title = {{Towards the Statistical Analysis and Visualization of Places}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {63:1--63:7},
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.2018.63},
URN = {urn:nbn:de:0030-drops-93914},
doi = {10.4230/LIPIcs.GISCIENCE.2018.63},
annote = {Keywords: Platial Analysis, Visualization, Statistics, Geosocial Media}
}
Document
Short Paper
An Experimental Comparison of Two Definitions for Groups of Moving Entities (Short Paper)
Abstract
Two of the grouping definitions for trajectories that have been developed in recent years allow a continuous motion model and allow varying shape groups. One of these definitions was suggested as a refinement of the other. In this paper we perform an experimental comparison to highlight the differences in these two definitions on various data sets.
Cite as
Lionov Wiratma, Maarten Löffler, and Frank Staals. An Experimental Comparison of Two Definitions for Groups of Moving Entities (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 64:1-64:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{wiratma_et_al:LIPIcs.GISCIENCE.2018.64,
author = {Wiratma, Lionov and L\"{o}ffler, Maarten and Staals, Frank},
title = {{An Experimental Comparison of Two Definitions for Groups of Moving Entities}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {64:1--64:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.64},
URN = {urn:nbn:de:0030-drops-93928},
doi = {10.4230/LIPIcs.GISCIENCE.2018.64},
annote = {Keywords: Trajectories, grouping algorithms, experimental comparison}
}
Document
Short Paper
Extracting Geospatial Information from Social Media Data for Hazard Mitigation, Typhoon Hato as Case Study (Short Paper)
Abstract
With social media widely used for interpersonal communication, it has served as one important channel for information creation and propagation especially during hazard events. Users of social media in hazard-affected area can capture and upload hazard information more timely by portable and internet-connected electric devices such as smart phones or tablet computers equipped with (Global Positioning System) GPS devices and cameras. The information from social media(e.g. Twitter, facebook, sina-weibo, WebChat, etc.) contains a lot of hazard related information including texts, pictures, and videos. Most important thing is that a fair proportion of these crowd-sourcing information is valuable for the geospatial analysis in Geographic information system (GIS) during the hazard mitigation process. The geospatial information (position of observer, hazard-affected region, status of damages, etc) can be acquired and extracted from social media data. And hazard related information could also be used as the GIS attributes. But social media data obtained from crowd-sourcing is quite complex and fragmented on format or semantics. In this paper, we introduced the method how to acquire and extract fine-grained hazard damage geospatial information. According to the need of hazard relief, we classified the extracted information into eleven hazard loss categories and we also analyzed the public's sentiment to the hazard. The 2017 typhoon "Hato" was selected as the case study to test the method introduced.
Cite as
Jibo Xie, Tengfei Yang, and Guoqing Li. Extracting Geospatial Information from Social Media Data for Hazard Mitigation, Typhoon Hato as Case Study (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 65:1-65:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{xie_et_al:LIPIcs.GISCIENCE.2018.65,
author = {Xie, Jibo and Yang, Tengfei and Li, Guoqing},
title = {{Extracting Geospatial Information from Social Media Data for Hazard Mitigation, Typhoon Hato as Case Study}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {65:1--65:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.65},
URN = {urn:nbn:de:0030-drops-93930},
doi = {10.4230/LIPIcs.GISCIENCE.2018.65},
annote = {Keywords: Social media, hazard mitigation, GIS, information extraction, typhoon}
}
Document
Short Paper
Propagation of Uncertainty for Volunteered Geographic Information in Machine Learning (Short Paper)
Abstract
Although crowdsourcing drives much of the interest in Machine Learning (ML) in Geographic Information Science (GIScience), the impact of uncertainty of Volunteered Geographic Information (VGI) on ML has been insufficiently studied. This significantly hampers the application of ML in GIScience. In this paper, we briefly delineate five common stages of employing VGI in ML processes, introduce some examples, and then describe propagation of uncertainty of VGI.
Cite as
Jin Xing and Renee E. Sieber. Propagation of Uncertainty for Volunteered Geographic Information in Machine Learning (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 66:1-66:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{xing_et_al:LIPIcs.GISCIENCE.2018.66,
author = {Xing, Jin and Sieber, Renee E.},
title = {{Propagation of Uncertainty for Volunteered Geographic Information in Machine Learning}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {66:1--66:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.66},
URN = {urn:nbn:de:0030-drops-93941},
doi = {10.4230/LIPIcs.GISCIENCE.2018.66},
annote = {Keywords: Uncertainty, Machine Learning, Volunteered Geographic Information, Uncertainty Propagation}
}
Document
Short Paper
Satellite Image Spoofing: Creating Remote Sensing Dataset with Generative Adversarial Networks (Short Paper)
Abstract
The rise of Artificial Intelligence (AI) has brought up both opportunities and challenges for today's evolving GIScience. Its ability in image classification, object detection and feature extraction has been frequently praised. However, it may also apply for falsifying geospatial data. To demonstrate the thrilling power of AI, this research explored the potentials of deep learning algorithms in capturing geographic features and creating fake satellite images according to the learned 'sense'. Specifically, Generative Adversarial Networks (GANs) is used to capture geographic features of a certain place from a group of web maps and satellite images, and transfer the features to another place. Corvallis is selected as the study area, and fake datasets with 'learned' style from three big cities (i.e. New York City, Seattle and Beijing) are generated through CycleGAN. The empirical results show that GANs can 'remember' a certain 'sense of place' and further apply that 'sense' to another place. With this paper, we would like to raise both public and GIScientists' awareness in the potential occurrence of fake satellite images, and its impacts on various geospatial applications, such as environmental monitoring, urban planning, and land use development.
Cite as
Chunxue Xu and Bo Zhao. Satellite Image Spoofing: Creating Remote Sensing Dataset with Generative Adversarial Networks (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 67:1-67:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{xu_et_al:LIPIcs.GISCIENCE.2018.67,
author = {Xu, Chunxue and Zhao, Bo},
title = {{Satellite Image Spoofing: Creating Remote Sensing Dataset with Generative Adversarial Networks}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {67:1--67:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.67},
URN = {urn:nbn:de:0030-drops-93952},
doi = {10.4230/LIPIcs.GISCIENCE.2018.67},
annote = {Keywords: Deep Learning and AI, GANs, Fake Satellite Image, Geographic Feature}
}
Document
Short Paper
A Safety Evaluation Method of Evacuation Routes in Urban Areas in Case of Earthquake Disasters Using Ant Colony Optimization and Geographic Information Systems (Short Paper)
Abstract
The present study aims to propose the method for the quantitative evaluation of safety concerning evacuation routes in case of earthquake disasters in urban areas using Ant Colony Optimization (ACO) algorithm and Geographic Information Systems (GIS). Regarding the safety evaluation method, firstly, the similarity in safety was focused on while taking into consideration road blockage probability, and after classifying roads by means of the hierarchical cluster analysis, the congestion rates of evacuation routes using ACO simulations were estimated. Based on these results, the multiple evacuation routes extracted were visualized on digital maps by means of GIS, and its safety was evaluated. Furthermore, the selection of safe evacuation routes between evacuation sites, for cases when the possibility of large-scale evacuation after an earthquake disaster is high, is made possible. As the safety evaluation method is based on public information, by obtaining the same geographic information as the present study, it is effective in other areas regardless of whether the information is of the past and future. Therefore, in addition to spatial reproducibility, the safety evaluation method also has high temporal reproducibility. Because safety evaluations are conducted on evacuation routes based on quantified data, highly safe evacuation routes that are selected have been quantitatively evaluated, and thus serve as an effective indicator when selecting evacuation routes.
Cite as
Kayoko Yamamoto and Ximing Li. A Safety Evaluation Method of Evacuation Routes in Urban Areas in Case of Earthquake Disasters Using Ant Colony Optimization and Geographic Information Systems (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 68:1-68:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{yamamoto_et_al:LIPIcs.GISCIENCE.2018.68,
author = {Yamamoto, Kayoko and Li, Ximing},
title = {{A Safety Evaluation Method of Evacuation Routes in Urban Areas in Case of Earthquake Disasters Using Ant Colony Optimization and Geographic Information Systems}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {68:1--68:7},
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.2018.68},
URN = {urn:nbn:de:0030-drops-93966},
doi = {10.4230/LIPIcs.GISCIENCE.2018.68},
annote = {Keywords: Large-Scale Evacuation, Evacuation Route, Safety Evaluation, Earthquake Disaster, ACO (Ant Colony Optimization), GIS (Geographic Information Systems)}
}
Document
Short Paper
Analysis of Irregular Spatial Data with Machine Learning: Classification of Building Patterns with a Graph Convolutional Neural Network (Short Paper)
Abstract
Machine learning methods such as Convolutional Neural Network (CNN) are becoming an integral part of scientific research in many disciplines, the analysis of spatial data often failed to these powerful methods because of its irregularity. By using the graph Fourier transform and convolution theorem, we try to convert the convolution operation into a point-wise product in Fourier domain and build a learning architecture of graph CNN for the classification of building patterns. Experiments showed that this method has achieved outstanding results in identifying regular and irregular patterns, and has significantly improved in comparing with other methods.
Cite as
Xiongfeng Yan and Tinghua Ai. Analysis of Irregular Spatial Data with Machine Learning: Classification of Building Patterns with a Graph Convolutional Neural Network (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 69:1-69:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{yan_et_al:LIPIcs.GISCIENCE.2018.69,
author = {Yan, Xiongfeng and Ai, Tinghua},
title = {{Analysis of Irregular Spatial Data with Machine Learning: Classification of Building Patterns with a Graph Convolutional Neural Network}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {69:1--69:7},
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.2018.69},
URN = {urn:nbn:de:0030-drops-93973},
doi = {10.4230/LIPIcs.GISCIENCE.2018.69},
annote = {Keywords: Building pattern, Graph CNN, Spatial analysis, Machine learning}
}
Document
Short Paper
Assessing Neighborhood Conditions using Geographic Object-Based Image Analysis and Spatial Analysis (Short Paper)
Abstract
Traditionally, understanding urban neighborhood conditions heavily relies on time-consuming and labor-intensive surveying. As the growing development of computer vision and GIScience technology, neighborhood conditions assessment can be more cost-effective and time-efficient. This study utilized Google Earth Engine (GEE) to acquire 1m aerial imagery from the National Agriculture Image Program (NAIP). The features within two main categories: (i) aesthetics and (ii) street morphology that have been selected to reflect neighborhood socio-economic (SE) and demographic (DG) conditions were subsequently extracted through geographic object-based image analysis (GEOBIA) routine. Finally, coefficient analysis was performed to validate the relationship between selected SE indicators, generated via spatial analysis, as well as actual SE and DG data within region of interests (ROIs). We hope this pilot study can be leveraged to perform cost- and time- effective neighborhood conditions assessment in support of community data assessment on both demographics and health issues.
Cite as
Chi-Feng Yen, Ming-Hsiang Tsou, and Chris Allen. Assessing Neighborhood Conditions using Geographic Object-Based Image Analysis and Spatial Analysis (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 70:1-70:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{yen_et_al:LIPIcs.GISCIENCE.2018.70,
author = {Yen, Chi-Feng and Tsou, Ming-Hsiang and Allen, Chris},
title = {{Assessing Neighborhood Conditions using Geographic Object-Based Image Analysis and Spatial Analysis}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {70:1--70:7},
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.2018.70},
URN = {urn:nbn:de:0030-drops-93983},
doi = {10.4230/LIPIcs.GISCIENCE.2018.70},
annote = {Keywords: neighborhood conditions assessment, geographic object-based image analysis, spatial analysis}
}
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Short Paper
Spatial Information Extraction from Text Using Spatio-Ontological Reasoning (Short Paper)
Abstract
This paper is involved with extracting spatial information from text. We seek to geo-reference all spatial entities mentioned in a piece of text. The focus of this paper is to investigate the contribution of spatial and ontological reasoning to spatial interpretation of text. A preliminary study considering descriptions of cities and geographical regions from English Wikipedia suggests that spatial and ontological reasoning can be more effective to resolve ambiguities in text than a classical text understanding pipeline relying on parsing.
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Madiha Yousaf and Diedrich Wolter. Spatial Information Extraction from Text Using Spatio-Ontological Reasoning (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 71:1-71:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{yousaf_et_al:LIPIcs.GISCIENCE.2018.71,
author = {Yousaf, Madiha and Wolter, Diedrich},
title = {{Spatial Information Extraction from Text Using Spatio-Ontological Reasoning}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {71:1--71:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.71},
URN = {urn:nbn:de:0030-drops-93997},
doi = {10.4230/LIPIcs.GISCIENCE.2018.71},
annote = {Keywords: spatial information extraction, geo-referencing, spatial reasoning}
}
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Short Paper
Scalable Spatial Join for WFS Clients (Short Paper)
Abstract
Web Feature Service (WFS) is a popular Web service for geospatial data, which is represented as sets of features that can be queried using the GetFeature request protocol. However, queries involving spatial joins are not efficiently supported by WFS server implementations such as GeoServer. Performing spatial join at client side is unfortunately expensive and not scalable. In this paper, we propose a simple and yet scalable strategy for performing spatial joins at client side after querying WFS data. Our approach is based on the fact that Web clients of WFS data are often used for query-based visual exploration. In visual exploration, the queried spatial objects can be filtered for a particular zoom level and spatial extent and be simplified before spatial join and still serve their purpose. This way, we can drastically reduce the number of spatial objects retrieved from WFS servers and reduce the computation cost of spatial join, so that even a simple plane-sweep algorithm can yield acceptable performance for interactive applications.
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Tian Zhao, Chuanrong Zhang, and Zhijie Zhang. Scalable Spatial Join for WFS Clients (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 72:1-72:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{zhao_et_al:LIPIcs.GISCIENCE.2018.72,
author = {Zhao, Tian and Zhang, Chuanrong and Zhang, Zhijie},
title = {{Scalable Spatial Join for WFS Clients}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {72:1--72:6},
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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.72},
URN = {urn:nbn:de:0030-drops-94007},
doi = {10.4230/LIPIcs.GISCIENCE.2018.72},
annote = {Keywords: WFS, SPARQL, Spatial Join}
}
Document
Short Paper
Modelling Spatial Patterns Using Graph Convolutional Networks (Short Paper)
Abstract
The understanding of geographical reality is a process of data representation and pattern discovery. Former studies mainly adopted continuous-field models to represent spatial variables and to investigate the underlying spatial continuity/heterogeneity in a regular spatial domain. In this article, we introduce a more generalized model based on graph convolutional neural networks that can capture the complex parameters of spatial patterns underlying graph-structured spatial data, which generally contain both Euclidean spatial information and non-Euclidean feature information. A trainable site-selection framework is proposed to demonstrate the feasibility of our model in geographic decision problems.
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Di Zhu and Yu Liu. Modelling Spatial Patterns Using Graph Convolutional Networks (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 73:1-73:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@InProceedings{zhu_et_al:LIPIcs.GISCIENCE.2018.73,
author = {Zhu, Di and Liu, Yu},
title = {{Modelling Spatial Patterns Using Graph Convolutional Networks}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {73:1--73:7},
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.2018.73},
URN = {urn:nbn:de:0030-drops-94016},
doi = {10.4230/LIPIcs.GISCIENCE.2018.73},
annote = {Keywords: Spatial pattern, Graph convolution, Big geo-data, Deep neural networks, Urban configuration}
}