Classification of digital terrain models through fuzzy clustering

An application

G. Antoniol, Michele Ceccarelli, A. Maratea, F. Russo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Experts classifications of spatial data are strongly affected by subjectivity and rigidity of rules. They do not take into account, in a quantitative way, the overlap of classes and as a major consequence, their classifications are often not reproducibles. To overcome this subjectivity, exploratory techniques can suggest a coherent set of rules that will produce suitable polythetic and overlapping classes. The aim of this paper is to validate the unsupervised method of fuzzy clustering applied to classification of raster spatial data.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages174-182
Number of pages9
Volume2955 LNAI
Publication statusPublished - 1 Dec 2005
Externally publishedYes
Event5th International Workshop on Fuzzy Logic and Applications, WILF 2003 - Naples, Italy
Duration: 9 Oct 200311 Oct 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2955 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other5th International Workshop on Fuzzy Logic and Applications, WILF 2003
CountryItaly
CityNaples
Period9/10/0311/10/03

Fingerprint

Fuzzy clustering
Fuzzy Clustering
Cluster Analysis
Spatial Data
Rigidity
Overlapping
Overlap
Model
Class

Keywords

  • Digital Terrain Model
  • Fuzzy Clustering
  • Validity Index

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Antoniol, G., Ceccarelli, M., Maratea, A., & Russo, F. (2005). Classification of digital terrain models through fuzzy clustering: An application. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2955 LNAI, pp. 174-182). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2955 LNAI).

Classification of digital terrain models through fuzzy clustering : An application. / Antoniol, G.; Ceccarelli, Michele; Maratea, A.; Russo, F.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 2955 LNAI 2005. p. 174-182 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2955 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Antoniol, G, Ceccarelli, M, Maratea, A & Russo, F 2005, Classification of digital terrain models through fuzzy clustering: An application. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 2955 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2955 LNAI, pp. 174-182, 5th International Workshop on Fuzzy Logic and Applications, WILF 2003, Naples, Italy, 9/10/03.
Antoniol G, Ceccarelli M, Maratea A, Russo F. Classification of digital terrain models through fuzzy clustering: An application. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 2955 LNAI. 2005. p. 174-182. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Antoniol, G. ; Ceccarelli, Michele ; Maratea, A. ; Russo, F. / Classification of digital terrain models through fuzzy clustering : An application. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 2955 LNAI 2005. pp. 174-182 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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