Call for Papers: Automated map generalization: emerging techniques and new trends

Call for Papers: Topical collection of the Journal of Geovisualization and Spatial Analysis

“Automated map generalization: emerging techniques and new trends”

Guest Editors: Xiang Zhang, Guillaume Touya and Martijn Meijers

Automated map generalization has been a major area of research for decades but has still not reached maturity. Besides the needs for more adaptive algorithms, a fundamental question remains: can we transfer human generalization knowledge into a computational system? Previous efforts do not seem capable to fully overcome the ‘knowledge acquisition bottleneck.’ As new theories and technologies have emerged in artificial intelligence, especially deep neural networks, computers are now able to solve human level tasks, showing great potential in automated generalization.

In the meantime, crowdsourced geographic information is growing at an increasing speed, and the needs for visualizing and analyzing the data at various scales are numerous. It is therefore necessary to adapt map generalization to new contexts (e.g., online maps, 3D models or crowd-sourced geo-data).

On the other hand, map generalization today also functions as a pattern analysis and mining tool. For example, the ‘overview first, zoom and filter, then details-on-demand’ method in information visualization is essentially the same as the generalization approach to data analysis. This highlights the potential of applying generalization techniques, such as simplification and aggregation, in the visual, interactive, and exploratory analysis of abstract (e.g., hierarchical relations) and physical (e.g., movement trajectories) data.

Therefore, we believe that it is now important to showcase the latest developments and trends in map generalization to a wider and interdisciplinary audience. The Special Issue is open for contributions related but not limited to the following topics:                

  • Deep/Machine learning techniques for data enrichment and generalization
  • Continuous/variable/multi scale representations
  • Adaptive generalization algorithms
  • 3D generalization and LOD models
  • Generalization and integration of crowd-sourced geographic data
  • Generalization practices for map production 
  • Changing map requirements/specifications
  • Generalization in web mapping and map mashups
  • Generalization of trajectory/flow/spatial interaction data
  • Use cases of generalization for data analysis and mining in other domains
  • Quality or cognitive evaluation of generalization

Manuscripts can be submitted under the following link:

The topical collection (special issue) will be closed on 30 June 2021.

You can find the instructions for authors here. Please direct any questions regarding the Special Issue to one of the guest editors:

Dr. Xiang Zhang, School of Resource and Environmental Sciences, Wuhan University, Wuhan, China

Dr. Guillaume Touya, LASTIG, Univ Gustave Eiffel, ENSG, IGN, Saint-Mandé, France

Dr. Martijn Meijers, Delft University of Technology, Delft, the Netherlands