Methods based on two-point geostatistics have been routinely used to interpolate random variables such as groundwater level and concentration and to estimate their values at un-sampled locations. These methods use the observed data to analyze spatial two-point correlations and ignore the higher order moments that may play a key role in the characterization of complex patterns. In this work, a m...

Automatic methods used in geosciences to interpolate between orientation data have often limited applicability and strength, in particular where large ranges of orientations occur. In this paper, we show that geostatistical methods yield rather strong and powerful results when applied to directional data. The procedure involves the calculation of variograms, followed by a kriging interpolation ...

14 Indoor air distributions, such as the distributions of air temperature, air velocity, and 15 contaminant concentrations, are very important to occupants’ health and comfort in 16 enclosed spaces. When point data is collected for interpolation to form field 17 distributions, the sampling locations (the locations of the point sensors) have a 18 significant effect on time invested, labor costs ...

The present paper proposes a new diagnostic tool for the structural health monitoring that employs a Kriging Interpolation. Structural health monitoring is a noticeable technology for aged civil structures. Most of the structural health monitoring systems adopts parametric method based on modeling or non-parametric method such as artificial neural networks or response surfaces. The conventional...

The shuttle radar topography mission (SRTM), was flow on space shuttle endeavour in February 2000, with the objective of acquiring a digital elevation model of all land between 60u north latitude and 56u south latitude, using interferometric synthetic aperture radar (InSAR) techniques. The SRTM data are distributed at horizontal resolution of 1 arc-second (,30 m) for areas within the USA and at...

This study aims at quantifying spatio-temporal dynamics of monthly mean dailyincident photosynthetically active radiation (PAR) over a vast and complex terrain such asTurkey. The spatial interpolation method of universal kriging, and the combination ofmultiple linear regression (MLR) models and map algebra techniques were implemented togenerate surface maps of PAR with a grid resolution of 500 ...

Model reduction has significant potential in design, optimization and probabilistic analysis applications, but including the parameter dependence in the reduced-order model (ROM) remains challenging. In this work, interpolation among reduced-order matrices is proposed as a means to obtain parameterized ROMs. These ROMs are fast to evaluate and solve, and can be constructed without reference to ...

spatial autocorrelation (sa) is the correlations of the observed data of an area in the form of spatial pattern. the criterion of sa phenomenon occurrence is when the distribution of one observed variable value follows a particular pattern systematically. the sa analysis is most useful and an important tool for investigating the spatial database, this analysis not only itself gives useful infor...

The Wiener filter is the well-known solution for linear minimum mean square error (LMMSE) signal estimation. This filter assumes the mean to be known and usually constant. On the other hand, the Kriging filter is an incremental theory, developed within the Geostatistical community, with respect to that of Wiener filters. The extension relies on adopting a parametric model for the mean (usually ...

A high fidelity simulation is preferred for its remarkable accuracy for engineering problems. However, it requires long computational time, which leads to significant overhead and eventually hinders its application to design study. To overcome such impediments, a reduced-order method is utilized. Reducedorder method can effectively represent a simulation output as a linear combination of a basi...