Dynland software identifies natural land cover classes from EO imagery using a human-intelligence-based, non-parametric, unsupervised image analysis algorithm created by the Institute of Electronics and Computer Science.


Our Team

Ints Mednieks

Group Leader, Senior Researcher, Dr. sc. comp.

Juris Siņica-Siņavskis

Researcher, Mg. math.

Romāns Dinuls

Researcher, Mg. math.

Mārtiņš Puķītis

Assistant Researcher, Mg. math.

Gatis Bolinskis

Business Leader, BBA

Arnis Kadakovskis

Project Manager, BSc. Finance & Economics

Supported by


Dynland is endorsed by international conferences and supported by universities.

  • Dynland was presented at the International Conference on Mathematics and Statistics ICOMS 2018, July 15–17, in Porto, Portugal.
  • Letters of support for further development were received from Technical University
    Bergakademie Freiberg in Germany (Prof. Dr. Swanhild Bernstein) and the ProFamilia
    Hungarian Scientific Society in Hungary (Prof. emeritus Gyógy Bártfai).
  • Dynland was among the finalists in the Copernicus Masters international challenge.


  • Romans Dinuls, Ints Mednieks “Nonparametric Classification of Satellite Images.” Proceedings of the 2018 International Conference on Mathematics and Statistics. ACM, New York, NY, USA, 2018, pp. 64-68. DOI:10.1145/3274250.3274260.

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