A MULTI-SCALE DATA STRUCTURE FOR CARTOGRAPHIC OBJECTS

Abstract

Geographic Information Systems manage data with respect to spatial location and that data is presented graphically as a map or sketch. Typically GIS tasks require graphical presentations at different levels of detail, ranging from overview scenes to detailed views. This is a general problem of visualization of information. Map generalization would solve this problem and efforts to achieve automated cartographic generalization were successful for specific aspects, but no complete solution is known. In this paper we propose to store renderings of objects at different levels of detail in a database, which can then be used to compose a map. This is a trade-off between storage and computation. 1. WHY A MULTI-SCALE DATA STRUCTURE FOR CARTOGRAPHIC OBJECTS Graphical sketches have become increasingly important as ad-hoc means of visual output from Geographic Information Systems (GIS). The requirements for these graphics are low in cartographic terms, namely fast visualization and presentation of the pertinent data only. In contrast, traditional maps have always been very sophisticated multi-purpose instruments. Typically GIS tasks require graphical representations at different levels of detail, ranging from overview scene to detailed views [12]. They also call for a single database as basis for the tasks to perform [3]. Automated cartographic generalization would fulfill these requirements. Unfortunately no complete solution is known, although efforts were successful for specific aspects [6]. Generalization in cartography is a complex set of operations on graphical representations of objects, not on the object itself. The result is a commonly accepted or standardized representation of the object in a certain scale. In this paper we propose to store renderings of objects at different levels of detail in a database. The proposed structure is a directed acyclic graph (dag). The renderings can then be used to compose a map. We restrict ourselves to the task of zooming and to the topographic scales (1:5000 - 1:100 000). The method is a trade-off between storage and computation.