By Dirk Burghardt, Cécile Duchêne, William Mackaness
Research within the box of automatic generalisation has confronted new demanding situations lately because of technological advancements in web-based processing, new visualisation paradigms and entry to huge volumes of multi-source info generated by means of sensors and people. In those contexts, map generalisation must underpin ‘on-demand mapping’, a sort of mapping that responds to person consumer requisites within the thematic choice and visualisation of geographic info. it truly is this new impetus that drives the study of the ICA fee on Generalisation and a number of illustration (for instance via its annual workshops, biannual tutorials and guides in overseas journals). This booklet has a coherent constitution, every one bankruptcy concentrating on middle thoughts and projects within the map generalisation in the direction of on-demand mapping. every one bankruptcy offers a state of the art evaluation, including case experiences that illustrate the applying of pertinent generalisation methodologies. The publication addresses concerns from info collecting to multi scaled outputs. hence there are chapters dedicated to defining consumer standards in dealing with necessities, and within the program and evaluate of map generalisation algorithms. It explores the appliance of generalisation methodologies within the context of turning out to be volumes of information and the expanding approval for person generated content.
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Additional info for Abstracting Geographic Information in a Data Rich World: Methodologies and Applications of Map Generalisation
Expert cartographers are the primary source of this knowledge. They describe the map specifications they judge usable for certain user requirements, but also compliant with the standards of cartographic design. Usability surveys are the second source of knowledge. 28 S. Balley et al. They must be carefully interpreted: as pointed out by Harding et al. (2009), data usability is sometimes difficult to distinguish from the usability of systems and interfaces used to manipulate the data (Haklay 2010).
3 Typology of cartographic constraints for automated generalisation (Burghardt et al. g. ‘‘cycle itineraries follow roads’’). However, in their generalisation form, many of these constraints are expressed through a maximum degree of variation between original and final states. This may not be adapted to on-demand mapping, where the source data is not supposed to be known in advance. It appears that more categories of constraints—they could be generically called representation constraints—are needed to express the other specification elements (thematic modelling, data schema and symbol specification) in order to support more of the steps in the map derivation process.
G. being able to create the same type of map in different countries). Thirdly, for the same independence purpose as above, map specifications should not refer to implemented feature types but to constructs from higher abstraction levels. In standardised contexts such as the INSPIRE infrastructure, 2 Map Specifications and User Requirements 23 these constructs can be feature concepts taken from a feature concept dictionary (ISO 2009). Feature concepts can be seen as interfaces for feature types proposing a meaning and a set of properties.