Automated labeling of schematic maps by optimization with knowledge acquired from existing maps

Abstract

Schematic maps are simplified representations of line networks, aiming to help people quickly and accurately perform route planning and orientation tasks. The automated generation of such maps is generally treated as an optimization problem. Most researchers prefer to optimize network layouts and name labels separately, because optimizing them simultaneously is still intractable. It is found that optimizing network layouts is extensively studied, while optimizing name labels is rarely considered. In the optimization of name labels, constraints can be established with rules from cartographic experts, literature (e.g., specification and technical documents), and/or existing maps. However, some rules from experts and literature cannot be explicitly and mathematically expressed. This study aims to develop an automated labeling method with rules from existing maps. We first acquire the rules (i.e., the potential positions and the preferences of these positions) from some existing schematic maps and then integrate them into an optimization algorithm. Experimental evaluation is conducted by a questionnaire in terms of “ease level of finding name labels,” “congestion level,” and “satisfaction level” using Tianjin and Hong Kong metro schematic maps and the labels of our method. The results show that the proposed method can automatically generate effective labels.

Drawing metro maps in concentric circles: A designer‐in‐the‐loop approach with visual examples

“…Aside from the various constraints that need to be solved in order to produce a complete metro map, another issue that needs to be resolved is the issue of station labels. While there are various techniques that can be used to place station labels in the drawing, these might not be ideal for a circular style (e.g., Lan et al, 2020Lan et al, , 2022. To promote a widespread use of concentric circles maps, the map-drawing algorithm in this study creates a designer-in-theloop prototype to maximize its usability and aesthetic of concentric circles maps.…”

“…Aside from the various constraints that need to be solved in order to produce a complete metro map, another issue that needs to be resolved is the issue of station labels. While there are various techniques that can be used to place station labels in the drawing, these might not be ideal for a circular style (e.g., Lan et al, 2020Lan et al, , 2022.…”

“…Schematic maps are traditionally drawn manually, which can be a difficult and time‐consuming process. Although increasing attention has recently been given to automated map‐generation methods, these are typically based on an optimization approach (e.g., Jacobsen et al, 2021; Lan et al, 2019, 2020; Li, 2015; Mark Ware et al, 2006; Sester, 2005; Stott et al, 2011; Wang & Chi, 2011), which may not satisfy both the psychological and aesthetic needs of users simultaneously. To date, work in this area has advanced in parallel.…”

Multiple Geographical Feature Label Placement Based on Multiple Candidate Positions in Two Degrees of Freedom Space

“…( 15), which is the final definition of the quality evaluation model in the 2-DOF space. 𝑆 = ∑ 𝑆 * 𝑊 (15) Where 𝑆 represents the score value of each quality factor, 𝑊 represents the weight of each corresponding factor, and 𝑆 represents the score of the quality evaluation model for the cartographic label placement.…”

“…In equation (15), the range value of the weight of each influencing factor is [0, 1], and the sum of the weight of all five factors is 1. The smaller the value of 𝑆 is, the better the feature label placement result is based on label placement rules.…”