Surfaces are a central to geographical analysis. Their generation
and manipulation are a key component of geographical information
systems (GISs). However, geographical surface data is often not
precise. When surfaces are used to model geographical entities, the
data inherently contains uncertainty in terms of both position and
attribute. Fuzzy Surface in GIS and Geographical Analysis sets out
a process to identify the uncertainty in geographic entities. It
describes how to successfully obtain, model, analyze, and display
data, as well as interpret results within the context of GIS.
Focusing on uncertainty that arises from transitional
boundaries, the book limits its study to three types of
uncertainties: intervals, fuzzy sets, and possibility
distributions. The book explains that uncertainty in geographical
data typically stems from these three and it is only natural to
incorporate them into the analysis and display of surface data. The
book defines the mathematics associated with each method for
analysis, then develops related algorithms, and moves on to
illustrate various applications.
Fuzzy Surface in GIS and Geographical Analysis clearly defines
how to develop a routine that will adequately account for the
uncertainties inherent in surface data.
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