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Urban land use mapping with multi-spectral and SAR satellite data using neural networks
- Source :
- IGARSS'97. 1997 IEEE International Geoscience and Remote Sensing Symposium Proceedings. Remote Sensing - A Scientific Vision for Sustainable Development.
- Publication Year :
- 2002
- Publisher :
- IEEE, 2002.
-
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.
- Subjects :
- Synthetic aperture radar
Artificial neural network
Contextual image classification
business.industry
Computer science
Decision tree learning
Feature extraction
Multispectral image
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Image processing
Feature selection
Pattern recognition
Sensor fusion
Rprop
Backpropagation
ComputingMethodologies_PATTERNRECOGNITION
Image texture
Multilayer perceptron
Radar imaging
Artificial intelligence
business
Remote sensing
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- IGARSS'97. 1997 IEEE International Geoscience and Remote Sensing Symposium Proceedings. Remote Sensing - A Scientific Vision for Sustainable Development
- Accession number :
- edsair.doi...........231ead7579078e5586204f0b3add3e8b