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(1995)Conference PaperDetailed maps derived from geographical data are becoming increasingly desirable for use in forest management. Many types of data are available for use in generating maps, for example, soil and vegetation maps. We look at a method for giving high level classifications that can be used as additional data for the generation of more detailed maps, and compare the results with other currently used techniques. We use multiple techniques to increase the reliability and accuracy of predictions. We describe a simple method of adjusting the balance of false positive and false negative classifications that are produced by the neural network. This allows better integration with non-neural network techniques.
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(1989)ThesisAn investigation of shape analysis methods is presented for application to remotely sensed images. The Method of Moments, in conjunction with linear pattern classification techniques, is shown to be suitable for the recognition of simple polygonal shapes in the absence of noise and in the presence of additive Gaussian noise with positive signal-to- noise ratios. The appropriate weight vectors for linear separation are presented and a suitable decision process is described for the recognition of desired shapes. The Method of Moments is successfully applied to a region which has been extracted from a real remotely sensed image using various segmentation thresholds. Finally, some recommendations are made for further work.
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