Maps of Czech Lands in the Period 1518–1720 from the Map Collection of Charles University in Prague

  • Miroslav ČábelkaEmail author
  • Markéta Potůčková
  • Tomáš Bayer
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)


Preliminary results of research on old maps of Czech Lands deposited at the Map Collection of Charles University in Prague are presented. The extensive cartographic collection belongs among the most important collections in the Czech Republic. The goal of the research was to document the development of cartography during the period 1518 (Claudianus’s map) to 1720 (Müller’s map). More than 50 originals or facsimiles of different maps were found during inventory phase of the work. The paper concentrates on a description of most interesting maps discovered from the point of view of their content, map symbols and cartometric characteristics.


old maps map collection map analysis 


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Our special thanks go to Ing. Petr Jánský – the administrator of the Map Collection of the Charles University in Prague – for granting us access to the collection, for his help in choosing maps and his willingness to answer all our questions.

This article was enabled by the GAČR grant no. 205/07/0385 “Cartometric and semiotic analysis and visualization of the old Czech Lands maps in the period 1518 –1720”.


  1. Kuchař K (1959) Mapy českých zemí do poloviny 18. století. ÚSGK, PrahaGoogle Scholar
  2. Kuchař K (1958) Naše mapy odedávna do dneška. Nakladatelství Čs. Akademie věd, PrahaGoogle Scholar
  3. Semotánová E (2001) Mapy Čech, Moravy a Slezska v zrcadle staletí. Libri, PrahaGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Miroslav Čábelka
    • 1
    Email author
  • Markéta Potůčková
    • 1
  • Tomáš Bayer
    • 1
  1. 1.Department of Applied Geoinformatics and CartographyCharles University in PraguePragueCzech Republic

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