The use of digital map data in the segmentation and classification of remotely-sensed images |
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| Authors: | D C MASON D G CORR A CROSS D C HOGG D H LAWRENCE M PETROU |
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| Institution: | 1. Department of Geography , Natural Environment Research Council Unit for Thematic Information Systems, University of Reading, Whiteknights , PO Box 227, Reading, RG6 2AB, England;2. Systems Designers Scientific , Pembroke House, Pembroke Broadway, Camberley, Surrey, GU15 3XD, England;3. University of Sussex , Arts Building, Falmer, Brighton, Sussex, BN1 9QN, England |
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| Abstract: | Abstract Remotely-sensed data constitute a major potential source of input to geographical information systems (GIS)However, these data often have a relatively poor classification accuracy compared with that of the cartographic data from maps with which they may be combined in the course of GIS analysis. The possibility exists of using data sets (in the form of digital maps) resident within a GIS in order to improve this accuracy, before the classified image is incorporated into the GIS. Results are discussed from a British Alvey Information Technology project to develop a system for the knowledge-based segmentation and classification of remotely-sensed terrain images, in which the knowledge contained in digital map |
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