engleski

Multispectral Classification of Landsat TM Images by Neural Networks

This work presents the results of experiments with the use of artificial neural networks for land cover classification. The goal of this research was to examine the operation of back-propagation neural network and its application in the classification of remotely sensed data. A back-propagation network with one hidden layer is used to classify a Landsat TM image. The results are compared to Gaussian maximum likelihood classifier. We show that neural network is better in performing than the maximum likelihood classifier.

neural network; back-propagation; classification; multispectral images; remote sensing; Landsat TM

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