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similar statistical properties” (Kittler, P.323). Kittler divides image processing into<br />
six sections; (1) the sensor and (2) data collection, (4) image preprocessing, (5)<br />
segmentation and classification and (6) image interpretation. The work undertaken<br />
in this thesis relates to part five of this system, although it will differ from the<br />
work considered by Kittler’s paper in that some image interpretation will have<br />
taken palace beforehand.<br />
Kittler has identified the first part (of the segmentation and classification step<br />
described above) as analyzing remotely sensed data in order to “identify<br />
homogeneous segments in the image” (Kittler, P.324). He introduced a method for<br />
pixel-by-pixel classification to achieve this. For this method he suggests<br />
identifying and classifying all the pixels on a pixel by pixel basis and then linking<br />
identical pixels to form connected segments. In many ways this is probably the<br />
holy grail of image interpretation as if perfected a machine could automatically<br />
identify change and update maps. Kittler also proposes that segments of pixels<br />
exhibiting similar properties could be used for this purpose. This thesis does not<br />
suppose an identical method, instead it attempts to identify the proportion of<br />
pixels corresponding to hard ground in a small area polygon, subtract buildings,<br />
roads and water polygons and attach a value for impermeable surface to the area<br />
data. Kittler suggests that a Bayesian probability formula can be used to determine<br />
the class of a segment. He suggests using what he terms “ground truth data”<br />
(Kittler, P.325) for the probability function to assign pixels to a class and<br />
determine the composition of a segment. He cites the class homogeneity of land<br />
surface covers as the means to initially segment and classify the pixels. This work<br />
can be made difficult by weather conditions and instrumental scanning errors<br />
(Note: Kittler’s paper is from a time when GPS controlled measurements were not<br />
readily available and such errors are less of a factor today, though small<br />
inconsistencies can occur, particularly at high altitude).<br />
Kittler further suggests a method for partitioning the image into segments (initially<br />
into cells of 2*2 pixels as suggested by Ketting & Landgrebe, 1976). In this way<br />
he estimates that the larger size of land cover would allow an analysis to identify<br />
neighboring pixels with similar properties. He also suggests another method for<br />
identifying segments of the image which he terms “two dimensional spatial<br />
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