A combined approach to cartographic displacement for buildings based on skeleton and improved elastic beam algorithm

PLoS One. 2014 Dec 3;9(12):e113953. doi: 10.1371/journal.pone.0113953. eCollection 2014.


Scale reduction from source to target maps inevitably leads to conflicts of map symbols in cartography and geographic information systems (GIS). Displacement is one of the most important map generalization operators and it can be used to resolve the problems that arise from conflict among two or more map objects. In this paper, we propose a combined approach based on constraint Delaunay triangulation (CDT) skeleton and improved elastic beam algorithm for automated building displacement. In this approach, map data sets are first partitioned. Then the displacement operation is conducted in each partition as a cyclic and iterative process of conflict detection and resolution. In the iteration, the skeleton of the gap spaces is extracted using CDT. It then serves as an enhanced data model to detect conflicts and construct the proximity graph. Then, the proximity graph is adjusted using local grouping information. Under the action of forces derived from the detected conflicts, the proximity graph is deformed using the improved elastic beam algorithm. In this way, buildings are displaced to find an optimal compromise between related cartographic constraints. To validate this approach, two topographic map data sets (i.e., urban and suburban areas) were tested. The results were reasonable with respect to each constraint when the density of the map was not extremely high. In summary, the improvements include (1) an automated parameter-setting method for elastic beams, (2) explicit enforcement regarding the positional accuracy constraint, added by introducing drag forces, (3) preservation of local building groups through displacement over an adjusted proximity graph, and (4) an iterative strategy that is more likely to resolve the proximity conflicts than the one used in the existing elastic beam algorithm.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Geographic Information Systems*
  • Geographic Mapping*
  • Image Enhancement / methods
  • Image Processing, Computer-Assisted / methods
  • Pattern Recognition, Automated / methods*
  • Reproducibility of Results

Grant support

This research was supported in part by the National Natural Science Foundation of China (Grant No. 41471384, No. 41171350). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.