Tree Symbols Detection for Green Space Estimation

  • Adrian Sroka
  • Marcin Luckner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8192)


Geodetic base maps are very detailed sources of information. However, such maps are created for specialists and incomprehensible to non–professionals. An example of information that can be useful for citizen is change of urban green spaces. Such spaces, valuable for a local society can be destroyed by developers or a local government. Therefore, a monitoring of green areas is an important task that can be done on the basis of maps from Geodetic Documentation Centres. Unfortunately, the most popular form of digital documentations is a bitmap. This work presents a feasibility study of green areas estimation from scanned maps. The solution bases on symbols detection. Two kinds of symbols (coniferous and deciduous trees) are recognised by the following algorithm. Dots from centres of symbols are detected and their neighbourhood is extracted. Specific features are calculated as an input for neural networks that detect tree symbols. The accuracy of the detection is 90 percent, which is good enough to estimate green areas.


Maps understanding image understanding image processing pattern recognition 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Adrian Sroka
    • 1
  • Marcin Luckner
    • 1
  1. 1.Faculty of Mathematics and Information ScienceWarsaw University of TechnologyWarsawPoland

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