Kriging or Gaussian Process Regression is applied in many fields as a non-linear regression model as well as a surrogate model in the field of evolutionary computation. However, the computational and space complexity of Kriging, that is cubic and quadratic in the number of data points respectively, becomes a major bottleneck with more and more data available nowadays. In this paper, we propose ...

Image denoising is a critical issue in the field of digital image processing. This paper proposes a novel Salt & Pepper noise suppression by developing a Kriging Interpolation Filter (KIF) for image denoising. Gray-level images degraded with Salt & Pepper noise have been considered. A sequential search for noise detection was made using kk window size to determine nonnoisy pixels only. The non...

Kriging is a widely employed technique, in particular for computer experiments, in machine learning or in geostatistics. An important challenge for Kriging is the computational burden when the data set is large. We focus on a class of methods aiming at decreasing this computational cost, consisting in aggregating Kriging predictors based on smaller data subsets. We prove that aggregations based...

New remote sensing technologies have emerged to quantitatively assess submersed aquatic vegetation abundance and distribution. We evaluated a hydroacoustics global positioning system to map the percent of the water column occupied by submersed vegetation (referred to here as biovolume) in three Minnesota (USA) lakes. We evaluated the relative accuracy and precision of digital biovolume maps pro...

Papers published in Hydrology and Earth System Sciences Discussions are under open-access review for the journal Hydrology and Earth System Sciences Abstract Spatial patterns of water chemistry along stream networks can be quantified using synoptic or " snapshot " sampling. The basic idea is to sample stream water at many points over a relatively short period of time. Even for intense sampling ...

Though one of the most significant driving forces behind ecological processessuch as biogeochemical cycles and energy flows, solar radiation data are limited or non-existent by conventional ground-based measurements, and thus, often estimated from othermeteorological data through (geo)statistical models. In this study, spatial and temporalpatterns of monthly average daily solar radiation on a h...

Accurate methods quantifying whole landfill surface flux of methane are important for regulatory and research purposes. This paper presents the results from the analysis of chamber measurements utilizing geospatial techniques [kriging and inverse distance weighting (IDW)] to arrive at an estimation of the whole landfill surface flux from the spatially distributed chamber measurement points. The...

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...

Kriging is a powerful spatial interpolation technique, especially for irregularly spaced data points, and is widely used throughout the earth and environmental sciences. The estimation at an unsampled location is given as the weighted sum of the circumjacent observed points. The weighting factors depend on a model of spatial correlation. Calculation of the weighting factors is done by minimizin...

  Background : Noise pollution and workers' noise exposure are common in industrial factories in Iran. In order to reduce this noise pollution, evaluation and investigation of noise emission are both necessary. In this study, different noise mapping methodsare used for determining the distribution of noise.   Materials and Methods : In the present study, for preparing a noise map i...