Exploring Semi-Automatic Map Labeling

TL;DR

This paper presents a semi-automatic map labeling approach that combines initial automatic placement with interactive user modifications, improving label quality through iterative human-algorithm collaboration.

Contribution

It introduces a human-in-the-loop method for map label placement, allowing iterative refinement and demonstrating its effectiveness with a prototype and performance analysis.

Findings

Interactive editing improves label placement quality

Heuristic algorithms offer faster updates with acceptable accuracy

The approach balances automation and expert input for better map aesthetics

Abstract

Label placement in maps is a very challenging task that is critical for the overall map quality. Most previous work focused on designing and implementing fully automatic solutions, but the resulting visual and aesthetic quality has not reached the same level of sophistication that skilled human cartographers achieve. We investigate a different strategy that combines the strengths of humans and algorithms. In our proposed method, first an initial labeling is computed that has many well-placed labels but is not claiming to be perfect. Instead it serves as a starting point for an expert user who can then interactively and locally modify the labeling where necessary. In an iterative human-in-the-loop process alternating between user modifications and local algorithmic updates and refinements the labeling can be tuned to the user's needs. We demonstrate our approach by performing different possible modification steps in a sample workflow with a prototypical interactive labeling editor. Further, we report computational performance results from a simulation experiment in QGIS, which investigates the differences between exact and heuristic algorithms for semi-automatic map labeling. To that end, we compare several alternatives for recomputing the labeling after local modifications and updates, as a major ingredient for an interactive labeling editor.