Fuzzy Surfaces in GIS and Geographical Analysis

Regular price €235.60
Quantity:
Ships in 10-20 days
Delivery/Collection within 10-20 working days
Shipping & Delivery
advanced spatial algorithms
Air Pollution
arithmetic
Category=PBT
Convex Hull Property
Cubic Splines
data
Data Model
Data Set
DEM Uncertainty
environmental data interpolation
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
function
Fuzzy Area
Fuzzy Arithmetic
Fuzzy Numbers
Fuzzy Query
Fuzzy Set
Fuzzy Subset
fuzzy surface uncertainty analysis
Fuzzy Surfaces
geostatistical analysis
interval
Interval Arithmetic
Map Algebra Operations
membership
Membership Function
number
Object Data Model
Possibilistic Uncertainties
Pseudo Code
raster
Raster Data Structure
Regions Ri
Semi-infinite Optimization Problem
set
spatial uncertainty modeling
structure
surface visualization techniques
triangular
Triangular Fuzzy Numbers
uncertainty quantification GIS
Vague Environment
Vector Data Structure

Product details

  • ISBN 9780849363955
  • Weight: 476g
  • Dimensions: 156 x 234mm
  • Publication Date: 13 Dec 2007
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
Secure checkout Fast Shipping Easy returns

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.

Weldon Lodwick