Selecting Optimal Residential Locations Using Fuzzy GIS Modeling Page: 51
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is not the only evaluation standard, when the evaluated values of other factors
are all very high, they can make up the fallen value in evaluating factor of school.
At this point, using Boolean logic to evaluate factor of school, the most suitable
locations can be guaranteed falling in the attendance zones of recognized
elementary schools. In future studies with similar factors, an alternative criterion
using Boolean logic will be able to meet the specific requirements of certain
users.
Moreover, it should be noted that the resolution of raster layers is an
important factor affecting the results from the model. The spatial distributions of
elements or phenomena have a close relationship with geographical scales. The
distribution may be homogenous at one scale, but heterogeneous at another
scale (Dong, 2000a, 2000b; Malczewski 2000). For example, the slope of the
land may remain the same in a piece of land of 30m by 30m, however in a land
of 1 km2, the slope of the land may vary distinctly. Furthermore, the best
geographical scale for different elements or phenomena may be different
(Malczewski 2000). For example, per square kilometer is usually used in
representing population density, but it may not be suitable to represent the
topographic slope using a cell size of 1 km by 1 km. In general, data with higher
resolution matches the geographical realities better, and using high resolution
data can lessen the bias of evaluation result. But using high resolution data is
limited by many factors such as individual data accessibility, the effectiveness
and efficiency of data processing. When using the model to evaluate51
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Tang, Zongpei. Selecting Optimal Residential Locations Using Fuzzy GIS Modeling, thesis, December 2006; Denton, Texas. (https://digital.library.unt.edu/ark:/67531/metadc5396/m1/56/: accessed April 19, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; .