Community Ecology

, Volume 10, Issue 1, pp 53–64 | Cite as

A classificatory approach integrating fuzzy set theory and permutation techniques for land cover analysis: a case study on a degrading area of the Rift Valley (Ethiopia)

  • E. Feoli
  • L. Gallizia-Vuerich
  • P. Ganis
  • Zerihun Woldu


We suggest a classificatory approach for land cover analysis that integrates fuzzy set theory with permutation techniques. It represents a non parametric alternative and/or a complement of traditional multivariate statistics when data are scarce, missing, burdened with high degree of uncertainty and originated from different sources and/or times. According to this approach, the Operational Geographic Units (OGUs) in which landscape is subdivided and sampled are classified with hierarchical clustering methods. The clusters of a classification which are significantly sharp are used to define fuzzy sets. In this way, the original data scores are transformedbydegreesofbelonging. Weintroduce the conceptsof endogenous and exogenous fuzzy sets and we suggest to apply the Mantel test between the similarity matrices of these fuzzy sets to test the predictivity of internal variables with respect to external variables. The approach is applied to OGUs corresponding to the smallest administrative units (kebeles) of the Ethiopian Rift Valley, a degrading area with high risk of further degradation. We found that: 1) there is a high correlation between geo-physical features of the landscape (geology, rainfall and elevation) and some indicators of the human pressure such as land use/cover, land management for livestock breeding and human, household and livestock densities, 2) there is a high correlation between land degradation, measured with relative loss of Normalized Difference Vegetation Index (NDVI) and the human pressure. However, the correlation is higher when the human pressure is considered in the geo-physical context of the landscape. The approach can be easily applied to produce maps useful for planning purposes thanks to geographical information system (GIS) technology that is becoming available at low cost even to small administrative units of developing countries.


Classification Correlation Ethiopia Fuzzy sets GIS Land degradation Permutation tests Planning Rift valley 



Correspondence between Classifications


Correlation between Similarity Matrices


Digital Elevation Model


Lanscape Unit


Normalized Difference Vegetation Index


Operational Geographic Unit


Sharpness of Exogenous classifications


Universal Soil Loss Equation


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© Akadémiai Kiadó, Budapest 2008

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Authors and Affiliations

  • E. Feoli
    • 1
  • L. Gallizia-Vuerich
    • 1
  • P. Ganis
    • 1
  • Zerihun Woldu
    • 2
  1. 1.Department of BiologyUniversity of TriesteItaly
  2. 2.Department of Biology, The National HerbariumAddis Ababa UniversityAddis AbabaEthiopia

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