Generation of land-cover descriptions for the classification of multisensor remote-sensing images

Author

Pellegretti, Paolo ; Serpico, Sebastiano B. ; Vernazza, Gianni

Author_Institution

Dept. of Biophys. & Electron. Eng., Genoa Univ., Italy

fYear

1993

fDate

18-21 Aug 1993

Firstpage

1701

Abstract

The paper deals with a learning system to acquire automatically the descriptions of objects to be recognized in remotely sensed images. These descriptions are in a symbolic form and use contextual properties and fuzzy logic descriptors to describe spectral properties. The system was tested on an Airborn Thematic Mapper (ATM) image of agricultural crops. The satisfactory results obtained in terms of classification accuracy witnessed the goodness of the approach and that the acquired descriptions are reliable. In particular, they can be employed as knowledge base for an expert classification system

Keywords

environmental science computing; expert systems; farming; fuzzy logic; image recognition; learning (artificial intelligence); remote sensing; ATM image; Airborn Thematic Mapper image; agricultural crops; classification; contextual properties; expert classification system; fuzzy logic descriptors; knowledge base; land-cover descriptions; learning system; multisensor remote-sensing images; spectral properties; Crops; Fuzzy logic; Image classification; Image recognition; Learning systems; Machine learning; Pattern recognition; Remote sensing; Supervised learning; System testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 1993. IGARSS '93. Better Understanding of Earth Environment., International

Conference_Location

Tokyo

Print_ISBN

0-7803-1240-6

Type

conf

DOI

10.1109/IGARSS.1993.322435

Filename

322435