AffiliationMilitary University of Technology
Paper titleUsing Artificial Neural Networks to Topographic Maps Labeling
AbstractThe purpose of this article was to present the methodology which enables the automatic maps labelling.This topic is particularly important in the context of the ongoing research into the full automation of visualization process of the spatial data which is stored in the currently used topographic databases (e.g. BDOT10k, VML2).To carry out this task the artificial neural networks were used, specifically one of their type – multilayer perceptron. The Vector Map Level 2 was used as a test database, while the data teaching neural networks (the reference label localization) was obtained from the military topographic map at scale 1:50 000. In the article the universal method of applying artificial neural networks to the map labelingwas presented. Detailed research was carried out on the basis of the labels from the feature class "built-up area". The results of the analyses revealed that it is possible to use the artificial intelligence computational methods to automate the process of labels placement on maps. The results showed that 65% of the labels were placed on the topographic map in the same place as in the case of the labelling which was donemanually by a map editor. The obtained results can contribute to both the enhancement of the quality of cartographic visualization (e.g. in geoportals) and the partial elimination of the human factor in this process.
Co-authorsBorkowska, S.
TopicGeoinformation infrastructures and ecosystems