Use this URL to cite or link to this record in EThOS:
Title: Analysis of Landsat MSS data for land cover mapping of large areas
Author: Hubbard, Neil K.
Awarding Body: University of Aberdeen
Current Institution: University of Aberdeen
Date of Award: 1985
Availability of Full Text:
Access through EThOS:
Full text unavailable from EThOS. Please try the link below.
Access through Institution:
One of the principal advantages of satellite data is the ability to provide terrain information over large areas, but past analyses of Landsat MSS data have tended to concentrate on developing techniques for small study areas. A method is developed for producing such large area land cover mapping from Landsat MSS data of Scotland. A stratified, interactive approach to image analysis produced the best results, incorporating a hybrid classification method involving a thorough selection process for training data pixels. Classification is implemented by either a minimum distance or a maximum likelihood technique which is further improved by post-classification editing and smoothing procedures. Results from a training and testing area produced a final classification statistically assessed as 87.3% correct. The method has subsequently been used to produce 3 maps of primary land cover types for Highland, Grampian and Tayside regions (total area 41,330 km2).
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Pattern recognition & image processing Pattern recognition systems Pattern perception Image processing Photography Photography Photocopying Geography