European Forest Types: toward an automated classification

  • Francesca Giannetti
  • Anna Barbati
  • Leone Davide Mancini
  • Davide Travaglini
  • Annemarie Bastrup-Birk
  • Roberto Canullo
  • Susanna Nocentini
  • Gherardo Chirici
Original Paper
Part of the following topical collections:
  1. ICP Forests

Abstract

Key message

The outcome of the present study leads to the application of a spatially explicit rule-based expert system (RBES) algorithm aimed at automatically classifying forest areas according to the European Forest Types (EFT) system of nomenclature at pan-European scale level. With the RBES, the EFT system of nomenclature can be now easily implemented for objective, replicable, and automatic classification of field plots for forest inventories or spatial units (pixels or polygons) for thematic mapping.

Context

Forest Types classification systems are aimed at stratifying forest habitats. Since 2006, a common scheme for classifying European forests into 14 categories and 78 types (European Forest Types, EFT) exists.

Aims

This work presents an innovative method and automated classification system that, in an objective and replicable way, can accurately classify a given forest habitat according to the EFT system of nomenclature.

Methods

A rule-based expert system (RBES) was adopted as a transparent approach after comparison with the well-known Random Forest (RF) classification system. The experiment was carried out based on the information acquired in the field in 2010 ICP level I plots in 17 European countries. The accuracy of the automated classification is evaluated by comparison with an independent classification of the ICP plots into EFT carried out during the BioSoil project field survey. Finally, the RBES automated classifier was tested also for a pixel-based classification of a pan-European distribution map of beech-dominated forests.

Results

The RBES successfully classified 94% of the plots, against a 92% obtained with RF. When applied to the mapped domain, the accuracy obtained with the RBES for the beech forest map classification was equal to 95%.

Conclusion

The RBES algorithm successfully automatically classified field plots and map pixels on the basis of the EFT system of nomenclature. The EFT system of nomenclature can be now easily and objectively implemented in operative transnational European forest monitoring programs.

Keywords

European Forest Type Expert system Classification GIS Vegetation Algorithm ICP forests 

Notes

Acknowledgements

This research was carried out in the context of ICP Forest group “Upscaling & Spatially explicit estimation of biophysical variables with remote sensing”, coordinated by Prof. Gherardo Chirici. The authors wish to thank the guest editor Walter Seidling and the two anonymous reviewers for their positive contribution to improving the manuscript.

This research was cofunded by the Accademia Italiana di Scienze Forestali and by geoLAB—Laboratory of Forest Geomatics at the Department of Agriculture, Alimentary and Forest Systems of the Università degli Studi di Firenze in the framework of a PhD Student Scholarship to Francesca Giannetti.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© INRA and Springer-Verlag France SAS, part of Springer Nature 2017

Authors and Affiliations

  • Francesca Giannetti
    • 1
  • Anna Barbati
    • 2
  • Leone Davide Mancini
    • 2
  • Davide Travaglini
    • 1
  • Annemarie Bastrup-Birk
    • 3
  • Roberto Canullo
    • 4
  • Susanna Nocentini
    • 1
  • Gherardo Chirici
    • 1
  1. 1.Department of Agricultural, Food and Forestry SystemUniversità degli Studi di FirenzeFlorenceItaly
  2. 2.Department for Innovation in Biological, Agro-Food and Forest SystemUniversità degli Studi della TusciaViterboItaly
  3. 3.European Environmental AgencyCopenhagenDenmark
  4. 4.Plant Diversity and Ecosystems Management Unit, School of Biosciences and Veterinary MedicineUniversity of CamerinoCamerinoItaly

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