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Classifying and Mapping Potential Distribution of Forest Types Using a Finite Mixture Model

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Abstract

The present paper presents the application of a finite mixture model (FMM) to analyze spatially explicit data on forest composition and environmental variables to produce a high-resolution map of their current potential distribution. FMM provides a convenient yet formal setting for model-based clustering. Within this framework, forest data are assumed to come from an underlying FMM, where each mixture component corresponds to a cluster and each cluster is characterized by a different composition of tree species. An important extension of this model is based on including a set of covariates to predict class membership. These covariates can be climatic and topographical parameters as well as geographical coordinates and the class membership of neighbouring plots. FMM was applied to a national forest inventory of Italy consisting of 6,714 plots with a measure of abundance for 27 tree species. In this way, a map of potential forest types was produced. The limitations and usefulness of the proposed modelling approach were analyzed and discussed, comparing the results with an independently derived expert map.

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Acknowledgments

This work has been funded by the Italian Ministry of Environment in collaboration with CONECOFOR (CONtrollo ECOsistemi FORestali), the intensive monitoring program of forest ecosystems in Italy. The program falls under the Pan-European Level II Monitoring of Forest Ecosystems and is co-sponsored by the European Union under the Regulation nr. 2152/2003 “Forest Focus”.

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Authors and Affiliations

  1. Environmental Biology Department, Sapienza University of Rome, P.le A. Moro 5, 00185, Rome, Italy

    Fabio Attorre, Fabio Francesconi, Michele De Sanctis, Marco Alfò, Francesca Martella, Roberto Valenti & Marcello Vitale

  2. Dipartimento di Scienze Statistiche, Sapienza University of Rome, P. le A. Moro 5, 00185, Rome, Italy

    Marco Alfò & Francesca Martella

Authors
  1. Fabio Attorre
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  2. Fabio Francesconi
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  3. Michele De Sanctis
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  4. Marco Alfò
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  5. Francesca Martella
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  6. Roberto Valenti
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  7. Marcello Vitale
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Correspondence to Fabio Attorre.

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Attorre, F., Francesconi, F., De Sanctis, M. et al. Classifying and Mapping Potential Distribution of Forest Types Using a Finite Mixture Model. Folia Geobot 49, 313–335 (2014). https://doi.org/10.1007/s12224-012-9139-8

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  • DOI: https://doi.org/10.1007/s12224-012-9139-8

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