The Space-Scale Cube (SSC) model stores the result of a generalization process, that supports smooth scale transitions for map objects. The third dimension is used to describe geometrically the smooth transitions between objects at different levels of detail. Often-used map generalization operators fit in this SSC model. The 3D SSC model to derive 2D maps can be used in a mobile web client, where these days powerful graphics hardware is available. This article shows the steps needed for producing and disseminating SSC data with smooth transitions over the web. Firstly, we explain how SSC data can be obtained and subsequently be rendered by making effective use of the GPU. Secondly, we show how we organize data in chunks and how this ‘chunked’ data can be used for efficient communication between client and server. In the third place, we describe which operations can be used on the client side for deriving maps. Fourthly, the SSC also allows for (a) mixed abstraction slicing surfaces useful for highlighting specific regions by showing more detail and (b) near-intersection blending, which helps to prevent abrupt transitions while the slicing surface is in motion. Finally, we show how animated pan and zoom functionalities may be realized. A set of prototypes allows us to disseminate the data with smooth transitions on the web and in practice judge the effect of continuous generalization and animating the map image.

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Traditionally, the content for vario-scale maps has been created using a ‘one fits all’ approach equal for all scales. Initially only the delete/merge operation was used to create the vario-scale data using the importance and the compatibility functions defined at class level (and evaluated at instance level) to create the tGAP structure with planar partition as basis. In order to improve the generalization quality other operators and techniques have been added during the past years; e. g. simplify, collapse (change area to line representation), split, attractiveness regions and the introduction of the concept of linear network topology. However, the decision which operation to apply has been hard coded in our software, making it not very flexible. Further, we want to include awareness of the current scale when deciding what generalization operation to apply. For this purpose we propose the scale dependent framework (SDF), which at its core contains the encoding of the generalization knowledge in the SDF conceptual model. This SDF model covers the representation of scale dependent class importance, scale dependent class compatibility values, scale dependent attractiveness regions and last but not least specification of generalization operations that are scale and class dependent. By changing the settings in the SDF configuration and re-running the vario-scale generalization process, we can easily experiment in order to find best settings (for specific map user needs). In this paper we design the SDF conceptual model and explicitly motivate and define the scope of its expressiveness. We further present the improved scale dependent tGAP creation software and present initial results in the form of better created vario-scale map content.

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Zo’n vijf jaar gelden is voor het eerst in Geo-Info het concept van vario-schaal geo-informatie beschreven (Van Oosterom en Meijers, 2012). In dit eerdere artikel werd de eerste echt geleidelijke vario-schaal structuur gepresenteerd: een delta schaal geeft een delta in de kaart (en hoe kleiner de delta schaal hoe kleiner de delta kaart). De afgelopen vijf jaar is er veel R&D verricht om het concept van vario-schaal geo-informatie te realiseren: ontwikkelen van prototypen en testen met echte data. In het kader van het Open Technologieprogramma (OTP van STW, Stichting Technische Wetenschappen [1]) project 11185 ‘Vario-scale geoinformation’ is er de afgelopen jaren veel vooruitgang geboekt. De belangrijkste resultaten zullen in een serie beknopte artikelen worden gepresenteerd. Dit is het eerste artikel in de serie.@en

Zo’n vijf jaar geleden is in Geo-Info het concept van vario-schaal geo-informatie beschreven (Van Oosterom en Meijers, 2012). In dit eerdere artikel werd de eerste echt geleidelijke vario-schaal structuur gepresenteerd: een delta schaal geeft een delta in de kaart (en hoe kleiner de delta schaal hoe kleiner de delta kaart). De afgelopen vijf jaar is er veel R&D verricht om het concept van vario-schaal geoinformatie te realiseren: ontwikkelen van prototypen en testen met echte data. In het kader van het Open Technologieprogramma (OTP van STW, Stichting Technische Wetenschappen) project 11185 ‘Vario-scale geo-information’ is er de afgelopen jaren veel vooruitgang geboekt. De belangrijkste resultaten zullen in een serie beknopte artikelen worden behandeld. Dit is het derde artikel in de serie.@en

Zo’n vijf jaar geleden is in Geo-Info het concept van vario-schaal geo-informatie beschreven (Van Oosterom en Meijers, 2012). In dit eerdere artikel werd de eerste echt geleidelijke vario-schaal structuur gepresenteerd: een delta schaal geeft een delta in de kaart (en hoe kleiner de delta schaal hoe kleiner de delta kaart). De afgelopen vijf jaar is er veel R&D verricht om het concept van vario- schaal geoinformatie te realiseren: ontwikkelen van prototypen en testen met echte data. In het kader van het Open Technologieprogramma (OTP van STW, Stichting Technische Wetenschappen) project 11185 ‘Vario-scale geo- information’ is er de afgelopen jaren veel vooruitgang geboekt. De belangrijkste resultaten zullen in een serie beknopte artikelen worden behandeld. Dit is het vierde artikel in de serie.@en

Zo’n vijf jaar gelden is in Geo-Info het concept van vario-schaal geo-informatie beschreven (Van Oosterom en Meijers, 2012). In dit eerdere artikel werd de eerste echt geleidelijke varioschaal structuur gepresenteerd: een delta schaal geeft een delta in de kaart (en hoe kleiner de delta schaal hoe kleiner de delta kaart). De afgelopen vijf jaar is er veel R&D verricht om het concept van vario-schaal geo-informatie te realiseren: ontwikkelen van prototypen en testen met echte data. In het kader van het Open Technologieprogramma (OTP van STW, Stichting Technische Wetenschappen) project 11185 ‘Vario-scale geo-information’ is er de afgelopen jaren veel vooruitgang geboekt (zie bronnen). De belangrijkste resultaten zullen in een serie beknopte artikelen worden behandeld. Dit is het tweede artikel in de serie.@en

Vario-scale data structures have been designed to support gradual content zoom and the progressive transfer of vector data, for use with arbitrary map scales. The focus to date has been on the server side, especially on how to convert geographic data into the proposed vario-scale structures by means of automated generalisation. This paper contributes to the ongoing vario-scale research by focusing on the client side and communication, particularly on how this works in a web-services setting. It is claimed that these functionalities are urgently needed, as many web-based applications, both desktop and mobile, require gradual content zoom, progressive transfer and a high performance level. The web-client prototypes developed in this paper make it possible to assess the behaviour of vario-scale data and to determine how users will actually see the interactions. Several different options of web-services communication architectures are possible in a vario-scale setting. These options are analysed and tested with various web-client prototypes, with respect to functionality, ease of implementation and performance (amount of transmitted data and response times). We show that the vario-scale data structure can fit in with current web-based architectures and efforts to standardise map distribution on the internet. However, to maximise the benefits of vario-scale data, a client needs to be aware of this structure. When a client needs a map to be refined (by means of a gradual content zoom operation), only the ‘missing’ data will be requested. This data will be sent incrementally to the client from a server. In this way, the amount of data transferred at one time is reduced, shortening the transmission time. In addition to these conceptual architecture aspects, there are many implementation and tooling design decisions at play. These will also be elaborated on in this paper. Based on the experiments conducted, we conclude that the vario-scale approach indeed supports gradual content zoom and the progressive web transfer of vector data. This is a big step forward in making vector data at arbitrary map scales available to larger user groups.@en

Until now, road network generalization has mainly been applied to the task of generalizing from one fixed source scale to another fixed target scale. These actions result in large differences in content and representation, e.g., a sudden change of the representation of road segments from areas to lines, which may confuse users. Therefore, we aim at the continuous generalization of a road network for the whole range, from the large scale, where roads are represented as areas, to mid- and small scales, where roads are represented progressively more frequently as lines. As a consequence of this process, there is an intermediate scale range where at the same time some roads will be represented as areas, while others will be represented as lines. We propose a new data model together with a specific data structure where for all map objects, a range of valid map scales is stored. This model is based on the integrated and explicit representation of: (1) a planar area partition; and (2) a linear road network. This enables the generalization process to include the knowledge and understanding of a linear network. This paper further discusses the actual generalization options and algorithms for populating this data structure with high quality vario-scale cartographic content.@en