The purpose of this paper is to construct universal, auto--adaptive,
localized, linear, polynomial (-valued) operators based on scattered data on
the (hyper--)sphere \SS^q (q≥2). The approximation and localization
properties of our operators are studied theoretically in deterministic as well
as probabilistic settings. Numerical experiments are presented to demonstrate
their superiority over traditional least squares and discrete Fourier
projection polynomial approximations. An essential ingredient in our
construction is the construction of quadrature formulas based on scattered
data, exact for integrating spherical polynomials of (moderately) high degree.
Our formulas are based on scattered sites; i.e., in contrast to such well known
formulas as Driscoll--Healy formulas, we need not choose the location of the
sites in any particular manner. While the previous attempts to construct such
formulas have yielded formulas exact for spherical polynomials of degree at
most 18, we are able to construct formulas exact for spherical polynomials of
degree 178.Comment: 24 pages 2 figures, accepted for publication in SIAM J. Numer. Ana