Clutter Reduction Methods for Point Symbols in Map Mashups

Korpi, Jari; Ahonen-Rainio, Paula

doi:10.1179/1743277413y.0000000065

Cited by 25 publications

(12 citation statements)

References 25 publications

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“…Issues des techniques et des méthodes de visualisation d'informations (infovis), ces approches permettent d'interpoler, d'agréger et de résumer de gros volumes de données pour faciliter leur interprétation (Fekete et Plaisant, 2002 ;Keim et al, 2008 ;Slocum et al, 2009). Comme le soulignent Korpi et Ahonen-Rainio (2013), les applications de cartographie en ligne possèdent à la fois des caractéristiques relevant de la cartographie et de la visualisation d'informations. En ce sens, les méthodes des deux disciplines doivent être prises en compte dans leur construction.…”

Section: L'agrégation Des Données Spatiales Volumineuses Comme Enjeu De Géovisualisationunclassified

The geovisualisation of big data on the Web: technological advances and cartographic evolutions

Mericskay¹

2021

mappemonde

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La géovisualisation de données massives sur le Web : entre avancées technologiques et évolutions cartographiquesThe geovisualisation of big data on the Web: technological advances and cartographic evolutions La geovisualización de macrodatos (o big data) en la Web : entre los avances tecnológicos y la evolución cartográfica Boris MericskayLa géovisualisation de données massives sur le Web : entre avancées technolog...

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Section: L'agrégation Des Données Spatiales Volumineuses Comme Enjeu De Géovisualisationunclassified

The geovisualisation of big data on the Web: technological advances and cartographic evolutions

Mericskay¹

2021

mappemonde

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“…From an information visualization perspective, Ellis and Dix (2007) proposed a taxonomy of techniques for the purpose of point clutter reduction. Korpi and Ahonen-Rainio (2013) presented a synthesis of cartographic and information visualization operations and demonstrated a significant overlap. With the focus on the problem of point clutter, the following generalization operations (or combinations of these) are of major importance: aggregation, simplification, selection, displacement, spatial distortion, data classification.…”

Section: Previous Workmentioning

confidence: 99%

Conceptual framework for enhancing visual change point analysis in generalized multi-temporal displays

Schiewe

2019

Proc. Int. Cartogr. Assoc.

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Abstract. Large amounts of point data are being generated and depicted in web maps, in particular promoted by the availability of Volunteered Geographic Information (VGI). This data volume causes usability problems for the visual presentation and exploration, especially by decreasing rendering performance and increasing geometric or semantic point clutter. Typically, generalization techniques are applied in order to overcome these clutter problems. Appropriate constraint-based approaches have been developed for static and single displays.Due to the increasing amount and relevance of multi-temporal point data, the aim of this contribution is to present a so far missing conceptual framework that consists of constraints related to change point analysis. These constraints describe the effects of the generalization on preservation and legibility of change information. Here, different types of change point analysis are differentiated, namely: existential changes, changes of semantic properties, and changes of spatial properties. For this purpose, difference frames between two given frames of the multi-temporal data set are used as a model of the mental representation of change information.The resulting constraints can be used to describe and to compare the suitability of various generalization operations for specific tasks. However, in a later stage they can also trigger the generalization processes as such. This could lead to a new way of thinking, since the optimization of generalization processes should work on difference frames rather than on single views.

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“…There are several techniques proposed for creating map mashups in a multi-scale context. Most of those studies have concentrated on thematic point data; see Korpi and Ahonen-Rainio (2013) for an overview. One example is Bereuter and Weibel (2013), who proposed a quad-tree based method for real-time generalisation supporting progressive levels of detail in the zooming process.…”

Section: Synchronisation Of Geometric Representations In Map Mashupsmentioning

confidence: 99%

Synchronising geometric representations for map mashups using relative positioning and Linked Data

Huang

Mansourian

Abdolmajidi

et al. 2018

International Journal of Geographical Information Science

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Map mashups, as a common way of presenting geospatial information on the Web, are generally created by spatially overlaying thematic information on top of various base maps. This simple overlay approach often raises geometric deficiencies due to geometric uncertainties in the data. This issue is particularly apparent in a multi-scale context because the thematic data seldom have synchronised level of detail with the base map. In this study, we propose, develop, implement and evaluate a relative positioning approach based on shared geometries and relative coordinates to synchronise geometric representations for map mashups through several scales. To realise the relative positioning between datasets, we adopt a Linked Data-based technical framework in which the data are organised according to ontologies that are designed based on the GeoSPARQL vocabulary. A prototype system is developed to demonstrate the feasibility and usability of the relative positioning approach. The results show that the approach synchronises and integrates the geometries of thematic data and the base map effectively, and the thematic data are automatically tailored for multi-scale visualisation. The proposed framework can be used as a new way of modelling geospatial data on the Web, with merits in terms of both data visualisation and querying.

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Clutter Reduction Methods for Point Symbols in Map Mashups

Cited by 25 publications

References 25 publications

The geovisualisation of big data on the Web: technological advances and cartographic evolutions

The geovisualisation of big data on the Web: technological advances and cartographic evolutions

Conceptual framework for enhancing visual change point analysis in generalized multi-temporal displays

Synchronising geometric representations for map mashups using relative positioning and Linked Data

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