Predicting air pollution is an important prerequisite for estimating, monitoring and mapping unknown pollution values. We can use fuzzy spatial prediction techniques to determine pollution concentration areas in practical situations where our observations are imprecise and vague. Fuzzy membership kriging with a semi-statistical membership function is an example of this type of technique. The im...

drought monitoring is a fundamental component of drought risk management. it is normally performed usingvarious drought indices that are effectively continuous functions of rainfall and other hydrometeorological variables.in many instances, drought indices are used for monitoring purposes. geostatistical methods allow the interpolationof spatially referenced data and the prediction of values fo...

     Drought monitoring is a fundamental component of drought risk management. It is normally performed using various drought indices that are effectively continuous functions of rainfall and other hydrometeorological variables. In many instances, drought indices are used for monitoring purposes. Geostatistical methods allow the interpolation of spatially referenced data and the prediction of v...

Because of the rapid economic growth in China, many regions are subjected to severe particulate matter pollution. Thus, improving the methods of determining the spatiotemporal distribution and uncertainty of air pollution can provide considerable benefits when developing risk assessments and environmental policies. The uncertainty assessment methods currently in use include the sequential indic...

Article history: Received 2 February 2006 Received in revised form 8 May 2006 Accepted 20 May 2006 The exact area calculation of irregularly distributed data is in the focus of all territorial geochemical balancingmethods or definition of protection zones. Especially in the deep-sea environment the interpolation ofmeasurements into surfaces represents an important gain of information, because o...

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...

The Kriging method is an interpolation scheme that can be used for modeling deter-ministic computer analyses as the realization of a stochastic process. The technique has been recognized as an alternative to the traditional Response Surface method in generating approximation models of computationally expensive CFD analyses. This is due to its ability to interpolate sample data and to model a fu...

nowadays, air pollution in cities with regard to its harmful outcomes has been turned into one of the serious challenges in urban management. pollutants as carbon monoxide, sulfur dioxide, and the aerosols that are known to be among the most important factors related to heart, vascular, and lung disease, have underlined public welfare and health, and the organizations concerned with community h...