Temporal Map Labeling: A New Unified Framework with Experiments
Lukas Barth, Benjamin Niedermann, Martin N\"ollenburg, Darren Strash

TL;DR
This paper introduces a unified, flexible framework for dynamic map labeling that adapts to map operations over time, supporting various applications and demonstrating near-optimal solutions with simple algorithms.
Contribution
It generalizes previous models into a versatile framework that abstracts map operations and applies to fixed and moving features, validated through extensive experiments.
Findings
Simple algorithms achieve near-optimal solutions
The model supports both fixed and moving map features
Extensive experiments validate the framework's effectiveness
Abstract
The increased availability of interactive maps on the Internet and on personal mobile devices has created new challenges in computational cartography and, in particular, for label placement in maps. Operations like rotation, zoom, and translation dynamically change the map over time and make a consistent adaptation of the map labeling necessary. In this paper, we consider map labeling for the case that a map undergoes a sequence of operations over a specified time span. We unify and generalize several preceding models for dynamic map labeling into one versatile and flexible model. In contrast to previous research, we completely abstract from the particular operations (e.g., zoom, rotation, etc.) and express the labeling problem as a set of time intervals representing the labels' presences, activities, and conflicts. The model's strength is manifested in its simplicity and broad range…
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Taxonomy
TopicsData Management and Algorithms · Geographic Information Systems Studies · Constraint Satisfaction and Optimization
