Confidence Regions for Local Maxima of Reconstructed Surfaces

There are several methods of surface reconstruction from a finite number of spatial data. The reconstruction is an estimate of the true surface, and it is often used to estimate topographical characteristics, e.g. to identify areas of extreme values. The uncertainty of an estimate depends both on uncertainties introduced by the reconstruction and on observation errors.We present a method to approximately evaluate the reliability of the estimates of the locations of local maxima (or minima) of the true surface. The true surface is modeled as a continuous parameter Gaussian random field, and the reliability is presented as confidence regions around the local maxima of the reconstruction.The method applies for general finite dimension of the spatial parameter, and for any reconstruction method that gives a differentiable surface with an explicit covariance function as result.