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.
W. Lodwick, M. Anile, and S. Spinella
Interpolation with Data Containing Interval, Fuzzy,
and Possibilistic Uncertainty
M. Anile and S. Spinella
Introduction to Geographical Information Systems
C. Fonte, J. Santos, and G. Gonçalves
Geographical Entities as Surfaces
Visualization and Analysis on Surfaces
C. Fonte, J. Santos, G. Gonçalves, S. Spinella,
and M. Anile
Algorithms— Pseudo Code
C. Fonte, J. Santos, and S. Spinella
Appendices — Fuzzy Arithmetic and Fuzzy Query
"This text should be of interest to anybody dealing with geographical surfaces, but especially to those already familiar with the capture, storage, analysis and display of surface data in the geographic information sciences who wish to explore in more depth how to mathematically treat error and uncertainty inherent in most, if not all, digital abstractions of reality."
– Peter Keller, in Geomatica, 2008, Vol. 62, No. 3