The management of vegetation classifications with fuzzy clustering

Journal of Vegetation Science

Volumn 21, Issue 6, 2010, Pages 1138-1151

  de Cáceres, Miquel ^a   Font, Xavier ^b   Oliva, Francesc ^b  

^a Centre Tecnologic Forestal de Catalunya   (Spain)

^b UNIVERSITY OF BARCELONA   (Spain)

Author keywords

Fuzzy C means; Noise clustering; Phytosociological data; Possibilistic C means; Syntaxonomy

Indexed keywords

CLUSTER ANALYSIS; ECOLOGICAL MODELING; FUZZY MATHEMATICS; MANAGEMENT PRACTICE; NUMERICAL METHOD; PASTURE; PERFORMANCE ASSESSMENT; SENSITIVITY ANALYSIS; SPECIES DIVERSITY; TAXONOMY; VEGETATION CLASSIFICATION; VEGETATION TYPE;

CATALONIA; SPAIN;

EID: 78049283809     PISSN: 11009233     EISSN: 16541103     Source Type: Journal    
DOI: 10.1111/j.1654-1103.2010.01211.x     Document Type: Article

References (57)

1. Aho, K., Roberts, D.W. & Weaver, T. 2008. Using geometric and non-geometric internal evaluators to compare eight vegetation classification methods. Journal of Vegetation Science 19: 549-562.
2. Beni, G. & Liu, X. 1994. A least biased fuzzy clustering method. IEEE Transactions on Pattern Analysis and Machine Intelligence 16: 954-960.
3. Bezdek, J.C. 1981. Pattern recognition with fuzzy objective functions. Plenum Press, New York, NY, US.
4. Bolòs, O. de, Vigo, J., Masalles, R.M. & Ninot, J.M. 1990. Flora Manual des Països Catalans. 2nd edn. Pòrtic, Barcelona, ES.
5. Braun-Blanquet, J. 1964. Pflanzensoziologie. Grundzüge der Vegetationskunde. 3rd ed. Springer, Wien, AT.
6. Bruelheide, H. 2000. A new measure of fidelity and its application to defining species groups. Journal of Vegetation Science 11: 167-178.
7. černá, L. & Chytrỳ, M. 2005. Supervised classification of plant communities with artificial neural networks. Journal of Vegetation Science 16: 407-414.
8. Dale, M.B. 1988. Some fuzzy approaches to phytosociology. Ideals and instances. Folia Geobotanica et Phytotaxonomica 23: 239-274.
9. Dale, M.B. 1995. Evaluating classification strategies. Journal of Vegetation Science 6: 437-440.
10. Davé, R.N. 1991. Characterization and detection of noise in clustering. Pattern Recognition Letters 12: 657-664.
11. Davé, R.N. & Krishnapuram, R. 1997. Robust clustering methods: a unified view. IEEE Transactions on Fuzzy Systems 5: 270-293.
12. De Cáceres, M. 2005. La classificaci ó num è rica de la vegetaci ó basada en la composici ó flor í stica. Ph.D. thesis, University of Barcelona (in Catalan).
13. De Cáceres, M., Oliva, F. & Font, X. 2006. On relational possibilistic clustering. Pattern Recognition 39: 2010-2024.
14. De Cáceres, M., Font, X., Vicente, P. & Oliva, F. 2009. Numerical reproduction of traditional classifications and automated vegetation identification. Journal of Vegetation Science 20: 620-628.
15. Dengler, J., Chytrỳ, M. & Ewald, J. 2008. Phytosociology. In: Jørgensen, S.E. & Fath, B.D. (eds.) Encyclopedia of ecology. pp. 2767-2779. Elsevier, Oxford, UK.
16. De Oliveira, J.V. & Pedrycz, W. 2007. Advances in fuzzy clustering and its applications. Wiley & Sons, Chichester, UK.
17. Dierschke, H. 1988. Zur Benennung zentraler Syntaxa ohne eigene Kenn- und Trennarten. Tuexenia 8: 381-382.
18. Duda, R.O., Hart, P.E. & Stork, D.G. 2001. Pattern classification. 2nd ed. Wiley & Sons, New York, NY, US.
19. Equihua, M. 1990. Fuzzy clustering of ecological data. Journal of Ecology 78: 519-534.
20. Escudero, A. & Pajarón, S. 1994. Numerical syntaxonomy of the Asplenietalia petrarchae in the Iberian Peninsula. Journal of Vegetation Science 5: 205-214.
21. Feoli, E. & Zuccarello, V. 1988. Syntaxonomy: a source of useful fuzzy sets for environmental analysis. Coenoses 3: 141-147.
22. Feoli, E., Ferro, G. & Ganis, P. 2006. Validation of phytosociological classifications based on a fuzzy set approach. Community Ecology 7: 99-108.
23. Font, X. 1988. Les pelouses de l'alliance Xerobromion du versant meridional des pyrénées. Colloques Phytosociologiques 16: 681-693.
24. Font, X. 1993. Estudis geobotànics sobre els prats xeròfils de l'estatge montà dels pirineus. Institut d'Estudis Catalans, Barcelona, ES.
25. Font, X. 2009. Mòdul Flora i Vegetació. Banc de Dades de Biodiversitat de Catalunya. Generalitat de Catalunya i Universitat de Barcelona, Barcelona, ES.
26. Frigui, H. & Krishnapuram, R. 1996. A robust algorithm for automatic extraction of an unknown number of clusters from noisy data. Pattern Recognition Letters 17: 1223-1232.
27. Gath, I. & Geva, A.B. 1989. Unsupervised optimal fuzzy clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence 11: 773-781.
28. Hennekens, S.M. & Schaminée, J.H.J. 2001. TURBOVEG, a comprehensive data base management system for vegetation data. Journal of Vegetation Science 12: 589-591.
29. Hill, M.O. 1979. TWINSPAN - a FORTRAN program for arranging multivariate data in an ordered two-way table by classification of the individuals and attributes. Cornell University, Ithaca, NY, US.
30. Hubert, L. & Arabie, P. 1985. Comparing partitions. Journal of Classification 2: 193-218.
31. Jennings, M.D., Faber-Langendoen, D., Loucks, O.L., Peet, R.K. & Roberts, D. 2009. Standards for associations and alliances of the US National Vegetation Classification. Ecological Monographs 79: 173-199.
32. Kenkel, N.C., Juhász-Nagy, P. & Podani, J. 1989. On sampling procedures in population and community ecology. Vegetatio 83: 195-207.
33. Kočí, M., Chytrỳ, M. & Tichỳ, L. 2003. Formalized reproduction of an expert-based phytosociological classification: a case study of subalpine tall-forb vegetation. Journal of Vegetation Science 14: 601-610.
34. Krishnapuram, R. & Keller, J.M. 1993. A possibilistic approach to clustering. IEEE Transactions on Fuzzy Systems 1: 98-110.
35. Krishnapuram, R. & Keller, J.M. 1996. The possibilistic c-means algorithm: insights and recommendations. IEEE Transactions on Fuzzy Systems 4: 385-393.
36. Legendre, P. & Gallagher, E.D. 2001. Ecologically meaningful transformations for ordination of species data. Oecologia 129: 271-280.
37. Marsili-Libelli, S. 1989. Fuzzy clustering of ecological data. Coenoses 4: 95-106.
38. Moraczewski, I.R. 1993. Fuzzy logic for phytosociology: 1. Syntaxa as vague concepts. Vegetatio 106: 1-11.
39. Moravec, J. 1989. Influences of the individualistic concept of vegetation on syntaxonomy. Vegetatio 81: 29-39.
40. Mucina, L. 1997. Classification of vegetation: past, present and future. Journal of Vegetation Science 8: 751-760.
41. Mucina, L. & Van Der Maarel, E. 1989. Twenty years of numerical syntaxonomy. Vegetatio 81: 1-15.
42. Olano, J.M., Loidi, J.J., Gonzalez, A. & Escudero, A. 1998. Improving the interpretation of fuzzy partitions in vegetation science with constrained ordinations. Plant Ecology 134: 113-118.
43. Ostermann, O.P. 1998. The need for management of nature conservation sites designated under Natura 2000. Journal of Applied Ecology 35: 968-973.
44. Pignatti, S. 1980. Reflections on the phytosociological approach and the epistemological basis of vegetation science. Vegetatio 42: 181-185.
45. Pillar, V.D. 1999. How sharp are classifications? Ecology 80: 2508-2516.
46. Podani, J. 1990. Comparison of fuzzy classifications. Coenoses 5: 17-21.
47. Podani, J. 2000. Introduction to the exploration of multivariate biological data. Backhuys, Leiden, NL.
48. Podani, J. 2005. Multivariate exploratory analysis of ordinal data in ecology: pitfalls, problems and solutions. Journal of Vegetation Science 16: 497-510.
49. Roberts, D.W. 2008. Statistical analysis of multidimensional fuzzy set ordinations. Ecology 89: 1246-1260.
50. Rodwell, J.S., Pignatti, S., Mucina, L. & Schaminée, J.H.J. 1995. European Vegetation Survey: update on progress. Journal of Vegetation Science 6: 759-762.
51. Roleček, J., Chytrỳ, M., Hájek, M., Lvončík, S. & Tichỳ, L. 2007. Sampling in large-scale vegetation studies: do not sacrifice ecological thinking to statistical puritanism. Folia Geobotanica 42: 199-208.
52. Tao, C.W. 2002. Unsupervised fuzzy clustering with multi-center clusters. Fuzzy Sets and Systems 128: 305-322.
53. Van Der Maarel, E. 1979. Transformation of cover-abundance values in phytosociology and its effects on community similarity. Vegetatio 39: 97-114.
54. Van Tongeren, O., Gremmen, N. & Hennekens, S.M. 2008. Assignment of relevés to predefined classes by supervised clustering of plant communities using a new composite index. Journal of Vegetation Science 19: 525-536.
55. Wallace, C.S. & Dale, M.B. 2005. Hierarchical clusters of vegetation types. Community Ecology 6: 57-74.
56. Ward, J.H. 1963. Hierarchical grouping to optimize an objective function. Journal of the American Statistical Association 58: 236-244.
57. Zadeh, L.A. 1965. Fuzzy sets. Information and Control 8: 338-353.