Global change research has placed new demands on methods of spatial analysis. In particular, spherical methods for spatial interpolation are required when spatial analyses are performed over large areas of the Earth's surface. In this article, spherical spatial interpolation procedures are reviewed, compared, and evaluated. Three classesof spherical interpolants are evaluated in detail: distanc...

Two computing approaches, based on linear and conic splines, are proposed here in reviewed and extended for vectorizing image outlines. Both of the approaches have various phases including extracting outlines of images, detecting corner points from the detected outlines, and curve fitting. Interpolation splines are the bases of the two approached. Linear spline approach is straight forward as i...

The original theory of splines grew out of the study of simple variational problems. A spline was a function that minimized some notion of energy subject to a set of interpolation constraints. A more recent method for creating splines is subdivision. In this framework, a spline is the limit of a sequence of functions, each related by some simple averaging rule. This paper shows that the two ide...

Fuzzy inference systems provide a simple yet effective solution to complex non-linear problems, which have been applied to numerous real-world applications with great success. However, conventional fuzzy inference systems may suffer from either too sparse, too complex or imbalanced rule bases, given that the data may be unevenly distributed in the problem space regardless of its volume. Fuzzy i...

annihilation or reduction of each kind of noise blended in correct data signals is a field that has attracted many researchers. it is a fact that fuzzy theory presents full capability in this field. fuzzy filters are often strong in smoothing corrupted signals, whereas they have simple structures. in this paper, a new powerful yet simple fuzzy procedure is introduced for sharpness reduction in ...

A classical approach to interpolation of sampled data is polynomial interpolation. However, from the sampling theorem it follows that the ideal approach to interpolation is to convolve the given samples with the sinc function. In this paper we study the properties of the sinc-approximating kernels that can be derived from the Lagrange central interpolation scheme. Both the finite-extent propert...

Four spatial estimation techniques available in commercial computational packages are evaluated and compared, namely: regularized splines interpolation, tension splines interpolation, inverse distance weighted interpolation, and ordinary Kriging estimation, in order to establish the best representation for the shallow stratigraphic configuration in the city of Aguascalientes, in Central Mexico....

Uwe Keller, Donald Reay, Roy Leitch Intelligent Systems Laboratory Dept. of Computing & Electrical Engineering Heriot-Watt University, Edinburgh EH14 4AS, Scotland, UK [email protected] Abstract In this paper Fuzzy Region Simulation (FRenSi), which provides solutions for fuzzy dynamical models, is applied to qualitative adaptive control. FRenSi, combines fuzzy model parameters and fuzzy initial...

Spatial interpolation is an important feature of a Geographic Information System, which is the procedure used to estimate values at unknown locations within the area covered by existing observations. In this paper, we propose a conservative spatial interpolation technique that incorporates the advantages of local interpolation, Euclidean interpolation, and conservative fuzzy reasoning. The main...