A formal approach to the automated labeling of groups of features

Abstract

A variety of recurring geographic entities form collections of point, line, or area features. Examples are groups of islands (Archipelago), relief features in deserts, periglacial lakes or geomorphological forms, such as drumlins and sinkholes. All these groups of features might be best identified with a single label. Surprisingly, the (automated) labeling of groups of features has received little attention so far. We propose a framework to determine formal measures that describe the geometric aspects of the cartographic design space for labeling feature groups. Our framework gives rise to a large variety of geometrically optimal labels. We list the optimal label positions and shapes for which labels can already be computed using existing algorithms. However, in many of the cases computing optimal label placements is still an open algorithmic question which can readily be investigated in future work. Once the necessary algorithms are developed, our framework provides an objective basis to investigate the geometric measures used by cartographers to label groups of features. We preliminarily explore the applicability of our framework using one of the geometric optimality choices.

Circles in the Water: Towards Island Group Labeling

“…To support our visual inspection we also perform a comparison in the line of the research outlined by Reimer et al [12]. They suggest to analyze what criteria cartographers may subconsciously use when placing island labels, by comparing manually placed island labels from atlases with automatically generated labels according to geometric criteria.…”

“…Since only straight labels are handled, the solution is not so general. The other exception is the work of Reimer et al [12], who review what existing geometric algorithms can be adapted directly to island label placement.…”

“…In this paper we expand on the research in Reimer et al [12] by solving several of the algorithmic problems in label placement for groups of features. In particular, we focus on min-max distance measures that minimize the maximum distance to the closest point of each feature.…”

“…Only few of them, namely the simpler ones, can be solved directly with known methods. Reimer et al [12] conclude that new algorithms are needed to advance the state-of-the-art in automated label placement for feature groups.…”

“…To generate such guidelines for groups of features, Reimer et al [12] propose a framework of possible geometric quality measures for the labeling of feature groups. The framework includes the shape of the label, whether it may intersect the features or not, and how the distance between a label and the features is measured.…”