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| Volume 105(2) 2005, pages: 39-47. | | Lasse Møller-Jensen, Richard Y. Kofie & Paul W. K. Yankson: | Large-area urban growth observations – a hierarchical kernel approach based on image texture | | A multi-scale classification algorithm based entirely on computation
of image texture in moving windows is presented and discussed.
The rationale for using kernel-based methods as opposed to segment-
based methods for texture-based land cover classification is
discussed, as well as, the need for identifying strategies that may
limit the effects of the inherent weaknesses of the kernel-based
methods. Part of the proposed solution to this problem is to omit the
search for an optimum kernel size and rather use different sizes concurrently
followed by a weighted summary overlay process based
on associated scores. The spatial growth pattern of the city of Accra,
Ghana, is assessed over a 17 years period using the algorithm.
Land-cover maps showing the extension of the new residential areas
on the fringe of Accra are produced from Landsat ETM satellite
imagery. These areas constitute the rapidly expanding frontier of
urban Accra into its rural surroundings. The classification discriminates
between new residential areas that have a distinct urban appearance
and areas that are in a transition phase between rural and
urban use. Finally, comparisons are made to a previous satellitebased
study of land cover changes for the period 1985 – 1991. | | >> download as pdf |
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