JOURNAL ARTICLE

Using contextual information to improve land use classification of satellite images in central Spain

F. GONZÁLEZ ALONSOS. LÓPEZ SORIA

Year: 1991 Journal:   International Journal of Remote Sensing Vol: 12 (11)Pages: 2227-2235   Publisher: Taylor & Francis

Abstract

The classification accuracy obtained from the classification of satellite images using pixel-by-pixel conventional methods can be improved if the contextual information is considered jointly with the spectral information in the same strategy of classification. A computer program has been developed to implement a contextual classifier algorithm. The accuracy improvement was evaluated and tested in two pilot zones of central Spain. Two indices were defined in order to analyse the homogeneity effect produced by the contextual classifier. © 1991 Taylor & Francis Ltd.

Keywords:
Classifier (UML) Computer science Pixel Homogeneity (statistics) Artificial intelligence Contextual image classification Remote sensing Satellite imagery Satellite Pattern recognition (psychology) Data mining Machine learning Geography Image (mathematics)

Metrics

11
Cited By
0.00
FWCI (Field Weighted Citation Impact)
11
Refs
0.34
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Remote-Sensing Image Classification
Physical Sciences →  Engineering →  Media Technology
Remote Sensing in Agriculture
Physical Sciences →  Environmental Science →  Ecology
Geochemistry and Geologic Mapping
Physical Sciences →  Computer Science →  Artificial Intelligence

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