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

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5 Author(s)
Heikkonen, J. ; Lab. of Comput. Eng., Helsinki Univ. of Technol., Espoo, Finland ; Kanellopoulos, I. ; Varfis, A. ; Steel, A.
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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

Published in:
Geoscience and Remote Sensing, 1997. IGARSS '97. Remote Sensing - A Scientific Vision for Sustainable Development., 1997 IEEE International  (Volume:4 )

Date of Conference: 3-8 Aug 1997

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