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Are landscapes as crisp as we may think?

Author

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  • Rocchini, Duccio
  • Ricotta, Carlo

Abstract

Geographic information is traditionally represented by a one-entity–one-class method, assuming that each geographical entity in the map can be unambiguously assigned to a single thematic class. Also, thematic map classes are assumed to be exhaustive and mutually exclusive. By contrast, fuzzy classifications overcome the traditional limitations on the mutually exclusive nature of map classes assigning varying levels of class membership for individual map entities. The aim of this paper is to show that the substitution of fuzzy set theory for classical set theory is an essential improvement for representing geographic information using hierarchical classification schemes.

Suggested Citation

  • Rocchini, Duccio & Ricotta, Carlo, 2007. "Are landscapes as crisp as we may think?," Ecological Modelling, Elsevier, vol. 204(3), pages 535-539.
    • Handle: RePEc:eee:ecomod:v:204:y:2007:i:3:p:535-539
    DOI: 10.1016/j.ecolmodel.2006.12.028
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    Cited by:

    1. Janssen, J.A.E.B. & Krol, M.S. & Schielen, R.M.J. & Hoekstra, A.Y. & de Kok, J.-L., 2010. "Assessment of uncertainties in expert knowledge, illustrated in fuzzy rule-based models," Ecological Modelling, Elsevier, vol. 221(9), pages 1245-1251.
    2. Ali Ghomi-Avili & Moslem Akbarinia & Seyed-Mohsen Hosseini & Mohammad-Hasan Talebian & Hannes Dieter Knapp, 2020. "Fuzzy and Boolean operation based modelling for evaluation of ecological capability in the Hyrcanian Forests," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 66(4), pages 170-184.

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