Characterisation of forestry species-a comparison using singular value decomposition (SVD) and artificial neural networks (ANN)

Singular value decomposition, which has previously been applied to the problem of signal extraction from marine data is currently being implemented for land use classification. Neural networks are becoming increasingly popular for the characterisation of multispectral remote sensing data. There are a number of significant problems with using ANN as classifiers for this type of data. A comparison of these two procedures is performed and there merits and difficulties discussed. The authors introduce the Levenberg Marquardt technique as an advanced method for finding the global minima during a backpropagation training scenario. These techniques are applied to simulated data generated from Landsat TM and SPOT satellite data of the County Wicklow area of Ireland. This data comprises five classes including Sitka spruce and Scots pine