Urban land use mapping with multi-spectral and SAR satellite data using neural networks

Author

Heikkonen, Jukka ; Kanellopoulos, Ioannis ; Varfis, Aristide ; Steel, Alan ; Fullerton, Karen

Author_Institution

Lab. of Comput. Eng., Helsinki Univ. of Technol., Espoo, Finland

Volume

4

fYear

1997

fDate

3-8 Aug 1997

Firstpage

1660

Abstract

Statistical, textural and Gabor features were extracted from integrated multitemporal multispectral TM data and ERS-1 SAR imagery for urban land use mapping. The computed features are first normalised using the SOM algorithm and then a decision tree algorithm is applied for feature selection. The classification procedure was carried out with a multilayer perceptron, trained with the resilient backpropagation algorithm. The authors´ results demonstrate the potential of the proposed methodology

Keywords

backpropagation; feature extraction; geophysical signal processing; geophysical techniques; geophysics computing; image classification; image sequences; image texture; multilayer perceptrons; radar imaging; remote sensing; remote sensing by radar; sensor fusion; spaceborne radar; synthetic aperture radar; Gabor feature; RES-1; SAR; SOM algorithm; backpropagation; data fusion; decision tree algorithm; feature extraction; feature selection; geophysical measurement technique; image classification; image processing; image texture; land surface; multilayer perceptron; multispectral imaging; multitemporal data; neural net; neural network; optical imaging; radar remote sensing; sensor fusion; spaceborne radar; terrain mapping; urban land use; Data mining; Feature extraction; Filtering; Multilayer perceptrons; Neural networks; Remote sensing; Satellites; Space technology; Synthetic aperture radar; Urban areas;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing, 1997. IGARSS '97. Remote Sensing - A Scientific Vision for Sustainable Development., 1997 IEEE International

Print_ISBN

0-7803-3836-7

Type

conf

DOI

10.1109/IGARSS.1997.609012

Filename

609012