Integrated transport, land-use and air quality monitoring are prioritized especially in metropolitan areas. The complexity is straight forward, since data, indicators, variables, methods and approaches vary and isolated. The Spatial Information Sciences (SIS) provides mature solutions for data and policy integration, since the nature of problem is specific to geo-spatial distribution. The inter...

Image inpainting is the art of predicting damaged regions of an image. The manual way of image inpainting is a time consuming. Therefore, there must be an automatic digital method for image inpainting that recovers the image from the damaged regions. In this paper, a novel statistical image inpainting algorithm based on Kriging interpolation technique was proposed. Kriging technique automatical...

In this paper, we perform an experimental study to investigate directional variograms in punctual kriging and consequently its effect on image restoration. We employ punctual kriging in conjunction with fuzzy logic typeII and fuzzy smoothing based approaches to remove white Gaussian noise from corrupted images. Images degraded with Gaussian white noise are restored by first utilizing fuzzy logi...

This paper develops a new modified Bayesian Kriging (MBKG) surrogate modeling method for problems in which simulation analyses are inherently noisy and thus standard Kriging approaches fail to properly represent the responses. The purpose is to develop a method that can be used to carry out reliability analysis to predict probability of failure. The formulation of the MBKG surrogate modeling me...

Geostatistical techniques have gained widespread use in ecology and environmental science. Variograms are commonly used to describe and examine spatial autocorrelation, and kriging has become the method of choice for interpolating spatially-autocorrelated variables. To date, most applications of geostatistics have defined the separation between sample points using simple Euclidean distance. In ...

rainfall spatial analysis methods are very helpful since there are not enough rainfall gauge stations and watersheds are scattered in large extent. there are many different methods for estimating average precipitation such as; arithmetic method and thiessen polygon. however, the arrangement and location of data and their correlations are not considered by classic methods. thus, geostatistical t...

accurate analysis and interpolation of heavy metals, especially arsenic concentrationin ground watercan play a significant role in planning and continuous monitoring of water resources. the analysis may also prevent human health issues.the purpose of this paper was to evaluate newly published sugeno type fuzzy inference system as an interpolation method for estimating the amount of arsenic in k...

To analyze the input/output behavior of simulation models with multiple responses, we may apply either univariate or multivariate Kriging (Gaussian process) metamodels. In multivariate Kriging we face a major problem: the covariance matrix of all responses should remain positive-definite; we therefore use the recently proposed “nonseparable dependence” model. To evaluate the performance of univ...

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...

We report an intelligent image restoration approach by combining the geostatistical interpolation technique of punctual kriging and the machine learning approach of adaptive learning. Digital images degraded from Gaussian white noise are restored by first utilizing fuzzy logic for selecting pixels that need to be kriged. The concept of punctual kriging is then used to estimate the intensity of ...