European environmental stratifications and typologies: An overview

G. W. Hazeu, M. J. Metzger, C. A. Mucher, M. Perez-Soba, Ch. Renetzeder, E. Andersen

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

A range of new spatial datasets classifying the European environment has been constructed over the last few years. These datasets share the common objective of dividing European environmental gradients into convenient units, within which objects and variables of interest have relatively homogeneous characteristics. The stratifications and typologies can be used as a basis for up-scaling, for stratified random sampling of ecological resources, for the representative selection of sites for studies across the continent and for the provision of frameworks for modeling exercises and reporting at the European scale.

This paper provides an overview of five recent European stratifications and typologies, constructed for contrasting objectives, and differing in spatial and thematic detail. These datasets are: the Environmental Stratification (EnS), the European Landscape Classification (LANMAP), the Spatial Regional Reference Framework (SRRF), the Agri-Environmental Zonation (SEAMzones), and the Foresight Analysis for Rural Areas Of Europe (FARO-EU) Rural Typology. For each classification the objective, background, and construction of the dataset are described, followed by a discussion of its robustness. Finally, applications of each dataset are summarized.

The five stratifications and typologies presented here give an overview of different research objectives for constructing such classifications. In addition they illustrate the most up to date methods for classifying the European environment, including their limitations and challenges. As such, they provide a sound basis for describing the factors affecting the robustness of such datasets. The latter is especially relevant, since there is likely to be further interest in European environmental assessment. In addition, advances in data availability and analysis techniques, will probably lead to the construction of other typologies in the future. (C) 2010 Elsevier B.V. All rights reserved.

Original languageEnglish
Pages (from-to)29-39
Number of pages11
JournalAgriculture, Ecosystems & Environment
Issue number1-2
Publication statusPublished - Jul 2011


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