The evaluation of fuzzy membership of land cover classes in the suburban zone

Citation data:

Remote Sensing of Environment, Vol: 34, Issue: 2, Page: 121-132

Publication Year:
1990
Usage 30
Abstract Views 30
Repository URL:
https://epubs.scu.edu.au/esm_pubs/878
Author(s):
Fisher, Peter F; Pathirana, Sumith
Tags:
Environmental Sciences
article description
The reflectance values of pixels, recorded by remote sensors, are often generated by more than one ground phenomenon. This, the so-called mixed pixel problem, has always been a property of scanner-type imaging, but its effect on the image classification process is arguably still a major problem to deriving accurate land cover maps, in spite of the increasing spatial resolution of sensors. This paper explores use of a fuzzy classifier to determine the constituent land cover components of pixels in a suburban environment. The classifier derives a measure of the fuzzy membership of a pixel belonging to each land cover class. For some land cover types including water, wetland, and woodland, a high correlation is shown between the fuzzy membership values for a pixel and the portion of the area of that pixel which belongs to a particular land cover type. The correlation for other land cover types is statistically significant but qualitatively poorer, and may indicate a lack of signature purity. The results show that the fuzzy classifier may enable the extraction of information about individual pixels and about subpixel phenomena not addressed by other classifiers.