Experts classifications of spatial data are strongly affected by subjectivity and rigidity of rules. They do not take into account, ina 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 appliedto classification of raster spatial data.
Classification of Digital Terrain Models Through Fuzzy Clustering: An Application
RUSSO F.
2006-01-01
Abstract
Experts classifications of spatial data are strongly affected by subjectivity and rigidity of rules. They do not take into account, ina 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 appliedto classification of raster spatial data.File in questo prodotto:
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