Classification in Geographical Information Systems
Identifieur interne : 000E09 ( Main/Merge ); précédent : 000E08; suivant : 000E10Classification in Geographical Information Systems
Auteurs : Salvatore Rinzivillo [Italie] ; Franco Turini [Italie]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2004.
Abstract
Abstract: The paper deals with the problem of knowledge discovery in spatial databases. In particular, we explore the application of decision tree learning methods to the classification of spatial datasets. Spatial datasets, according to the Geographic Information System approach, are represented as stack of layers, where each layer is associated with an attribute. We propose an ID3-like algorithm based on an entropy measure, weighted on a specific spatial relation (i.e. overlap). We describe an application of the algorithm to the classification of geographical areas for agricultural purposes.
Url:
DOI: 10.1007/978-3-540-30116-5_35
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<front><div type="abstract" xml:lang="en">Abstract: The paper deals with the problem of knowledge discovery in spatial databases. In particular, we explore the application of decision tree learning methods to the classification of spatial datasets. Spatial datasets, according to the Geographic Information System approach, are represented as stack of layers, where each layer is associated with an attribute. We propose an ID3-like algorithm based on an entropy measure, weighted on a specific spatial relation (i.e. overlap). We describe an application of the algorithm to the classification of geographical areas for agricultural purposes.</div>
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