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Fuzzy k-means clustering of fields in an elementary catchment and extrapolation to a larger area

Abstract : A practical problem in land management in southern France is the classification of cultivated fields according to their hydrological properties as a function of soil and topography. Lack of spatial contiguity and overlap in data space render conventional numerical methods for soil and landscape classification unreliable. Fuzzy k-means with extragrades have been used to create a spatially coherent classification of fields for a test area in Roujan (H(~xdt, Langu~_oSoc_) . Several different classifications were tested for geographical coherency using the Geary contiguity coefficient. The stability of the classes was also tested using a less precise data set for charactedzing the same fields. To test the usefulness of this ~ h , the best classification was used to allocate fields from a larger area adjacent to the test site to the established classes. The increase in exttagrade sites is used as a measure of robustness, representativity and transfer-ability of the classification. Our results show that a fuzzy classification gives systematically better mappable and less error-sensitive clusters than a classical crisp classification. Furthermore, it provides more information, particularly concerning the representativity of the elementary catchment.
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Contributor : Philippe Lagacherie <>
Submitted on : Thursday, September 9, 2021 - 5:19:58 PM
Last modification on : Tuesday, September 14, 2021 - 3:35:12 AM


  • HAL Id : hal-03339900, version 1


Philippe Lagacherie, D.R. Cazemier, Pauline van Gaans, Peter Burrough. Fuzzy k-means clustering of fields in an elementary catchment and extrapolation to a larger area. Geoderma, Elsevier, 1997, 77, pp.197-216. ⟨hal-03339900⟩



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