Introduction Exploring Geovisualization

Dykes, Jason; MacEachren, Alan M.; Kraak, M.J.

doi:10.1016/b978-008044531-1/50419-x

Cited by 124 publications

(112 citation statements)

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“…It is generally recognized that visual displays facilitate effective perception and cognition (McCormick et al 1987), promote ideation (Dykes et al 2005) and support analytical thinking (Thomas & Cook 2005).…”

Section: Introductionmentioning

confidence: 99%

A General Framework for Using Aggregation in Visual Exploration of Movement Data

Andrienko

2010

The Cartographic Journal

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This is the unspecified version of the paper.This version of the publication may differ from the final published version. Permanent AbstractTo be able to explore visually large amounts of movement data, it is necessary to apply methods for aggregation and summarization of the data. The goal of our research has been to systemize the possible approaches to aggregation of movement data into a framework clearly defining what kinds of exploratory tasks each approach is suitable for. On the basis of a formal model of movement of multiple entities, we consider two possible views of movement data, situation-oriented and trajectory-oriented.For each view, we discuss the appropriate methods of data aggregation and the visualization techniques representing the results of aggregation and supporting data exploration. A special attention is given to dynamic aggregation working in combination with interactive filtering and classification of movement data.

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Section: Introductionmentioning

confidence: 99%

A General Framework for Using Aggregation in Visual Exploration of Movement Data

Andrienko

2010

The Cartographic Journal

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“…Albeit our research was not carried out from the perspective of the remote sensing field, and hence LiDAR analysis was not its main interest, further investigation still appears pertinent on the processing of LiDAR data as a single data source for the retrieval of higher-level geographic information Moreover, the lack or even the non-existence of graph analysis functionalities in common GIS packages suggests the development of an interactive tool for the visual representation and analysis of such a spatial data structure. In fact, structured inquiries and spatial analysis are certainly integral to GIS, but they fail to emphasize the power of the human eye in detecting patterns and the role of subjectivity in GIS (Schuurman, 2004;Dykes et al, 2005). As fact of matter, in most automated and semi-automated methods the user is not able to visualise any interim results until the end of the whole process.…”

Section: Motivationmentioning

confidence: 99%

A graph-based algorithm to define urban topology from unstructured geospatial data

Almeida

Morley

Dowman

2013

International Journal of Geographical Information Science

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Interpretation and analysis of urban topology are particularly challenging tasks given the complex spatial pattern of the urban elements, and hence their automation is especially needed. In terms of the urban scene meaning, the starting point in this study is unstructured geospatial data, i.e. no prior knowledge of the geospatial entities is assumed. The aim of translating these data into more meaningful homogeneous regions can be achieved by detecting geographic features within the initial random collection of geospatial objects, and then by grouping them according to their spatial arrangement. The techniques applied to achieve this are those of graph theory applied to urban topology analysis within GIS environment. The role of graph theory in such a task and pre-processing of raw geospatial data were object of another previously published paper; this manuscript focuses primarily on the description of the procedure: "containmentfirst search" (CFS) -based on the well known breadth-first search algorithm for graph traversal, CFS analyzes and interprets the geospatial object arrangements in terms of the extension of the standard notion of the topological relation of adjacency to that of containment, what is defined within this research as "polygon-ring containment". LiDAR data were used as an example scenario for development purposes; in order to test the system proposed as a whole, further tests will entail the use of real world LiDAR datasets with different technical characteristics as well as photogrammetric datasets.

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“…We use this introduction to demonstrate the close links between Information Visualization and Geovisualization and argue that cross-disciplinarity is key to the advancement of our sciences. Indeed, this publication aims to continue and enhance knowledge transfer between communities such as that reported in 'Exploring Geovisualization' (Dykes et al, 2005).…”

Section: Advancing the Geovisualization Of Dynamics Movement And Chamentioning

confidence: 99%

“…Cross-disciplinarity has been reflected not only in the contents of the submissions, but also in the composition of the workshop delegates, which included scientists from a variety of nations with backgrounds in geography, geographic information science, information visualization, data mining and other cognate disciplines. We reflect upon some of these trends in this introduction to the papers.Integration of approaches from multiple disciplines is a characteristic feature of geovisualization -a research domain addressing the visual exploration, analysis, synthesis, and presentation of geographic data, information, and knowledge (Dykes et al 2005). The ICA Commission on Geovisualization works to develop, promote and communicate advances in this multidisciplinary domain -http://geoanalytics.net/ica.…”

mentioning

confidence: 99%

“…Integration of approaches from multiple disciplines is a characteristic feature of geovisualization -a research domain addressing the visual exploration, analysis, synthesis, and presentation of geographic data, information, and knowledge (Dykes et al 2005). The ICA Commission on Geovisualization works to develop, promote and communicate advances in this multidisciplinary domain -http://geoanalytics.net/ica.…”

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confidence: 99%

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Geovisualization of Dynamics, Movement and Change: Key Issues and Developing Approaches in Visualization Research

Andrienko

Dykes

Fabrikant

et al. 2008

Information Visualization

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This issue of Information Visualization showcases research activity involving and contributing to the visual analysis of dynamism, movement and change in phenomena that have a spatial element.The work presented here represents a selection of the contributions made to a workshop coordinated by the International Cartographic Association (ICA) Commission on Geovisualization and the Association of Geographic Information Laboratories in Europe (AGILE) on the Geovisualization of Dynamics, Movement and Change. Theoretical and methodological approaches for exploring and analyzing large datasets with spatial and temporal components were presented, discussed and developed at the meeting in Girona, Catalunya which was held on 5 th May 2008 one day before AGILE's 11th International Conference on Geographic Information Science.The high level of interest raised by the open call for contributions and the ultimate participation of more than 40 scientists suggests that this theme is timely and of relevance to many researchers and research groups. It would also seem to indicate that spatiotemporal data pose plenty of interesting and unsolved research problems. The workshop, and the work subsequently reported here suggest that many of these are complex and can benefit from the application of cross-disciplinary approaches. Cross-disciplinarity has been reflected not only in the contents of the submissions, but also in the composition of the workshop delegates, which included scientists from a variety of nations with backgrounds in geography, geographic information science, information visualization, data mining and other cognate disciplines. We reflect upon some of these trends in this introduction to the papers.Integration of approaches from multiple disciplines is a characteristic feature of geovisualization -a research domain addressing the visual exploration, analysis, synthesis, and presentation of geographic data, information, and knowledge (Dykes et al. 2005). The ICA Commission on Geovisualization works to develop, promote and communicate advances in this multidisciplinary domain -http://geoanalytics.net/ica. One way of so doing is to attract researchers with various disciplinary backgrounds to themed workshops that showcase current multidisciplinary approaches whilst allowing participants to learn about relevant theories and methods existing in related fields. They also create new opportunities for considering problems from different perspectives, and for starting new cross-disciplinary collaborations.

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Introduction Exploring Geovisualization

Cited by 124 publications

References 2 publications

A General Framework for Using Aggregation in Visual Exploration of Movement Data

A General Framework for Using Aggregation in Visual Exploration of Movement Data

A graph-based algorithm to define urban topology from unstructured geospatial data

Geovisualization of Dynamics, Movement and Change: Key Issues and Developing Approaches in Visualization Research

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