Dionissios T. Hristopulos

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INTAMAP is a Web Processing Service for the automatic spatial interpolation of measured point data. Requirements were (i) using open standards for spatial data such as developed in the context of the Open Geospatial Consortium (OGC), (ii) using a suitable environment for statistical modelling and computation, and (iii) producing an integrated, open source(More)
Random fields are useful models of spatially variable quantities, such as those occurring in environmental processes and medical imaging. The fluctuations obtained in most natural data sets are typically anisotropic. The parameters of anisotropy are often determined from the data by means of empirical methods or the computationally expensive method of(More)
Marc Laurent Serre Environmental Spatiotemporal Mapping and Ground Water Flow Modelling Using the BME and ST Methods (Under the direction of George Christakos) Modelling the natural processes that shape our environment is a difficult task, both numerically and theoretically. The numerical solution of physical laws describing natural processes, such the flow(More)
Spartan spatial random fields (SSRFs) are generalized Gibbs random fields, equipped with a coarse-graining kernel that acts as a low-pass filter for the fluctuations. SSRFs are defined by means of physically motivated spatial interactions and a small set of free parameters (interaction couplings). This paper focuses on the fluctuation-gradient-curvature(More)
This paper addresses the spatial interpolation of scattered data in <i>d</i> dimensions. The problem is approached using the theory of Spartan spatial random fields (SSRFs), focusing on a specific Gaussian SSRF, i.e., the fluctuation-gradient-curvature (FGC) model. A family of spatial interpolators (predictors) is formulated by maximizing the FGC-SSRF(More)
Dionissios T. Hristopulos Department of Mineral Resources Engineering Technical University of Crete Chania 73100, Greece Abstract The spatial structure of fluctuations in spatially inhomogeneous processes can be modeled in terms of Gibbs random fields. A local low energy estimator (LLEE) is proposed for the interpolation (prediction) of such processes at(More)