Geostatistics for environmental monitoring and survey design

Zirschky, J.

doi:10.1016/0160-4120(85)90187-4

Cited by 26 publications

(13 citation statements)

References 36 publications

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“…It takes into account the spatial structure of the interpolated variable (here, the electric-field strength), determines the best estimator of the variable (the error is minimized at all points), and it gives us information about the accuracy of the interpolation, by calculating an error estimate, called kriging variance (Matheron, 1963). Because of this, kriging is an often used interpolation technique in environmental research (e.g., Liu and Rossini, 1996;Paniagua et al, 2013;Sanders et al, 2012;Zirschky, 1985). The kriging variance can be used to quantify the model uncertainty, and to assist the sample search strategy in identifying potentially interesting regions in the study area based on a given condition.…”

Section: Sequential Surrogate Modelingmentioning

confidence: 99%

Assessment of outdoor radiofrequency electromagnetic field exposure through hotspot localization using kriging-based sequential sampling

Aerts

Deschrijver

Verloock

et al. 2013

Environmental Research

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Section: Sequential Surrogate Modelingmentioning

confidence: 99%

Assessment of outdoor radiofrequency electromagnetic field exposure through hotspot localization using kriging-based sequential sampling

Aerts

Deschrijver

Verloock

et al. 2013

Environmental Research

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“…The availability of the soil data allows the possibility of geostatistical analysis (Brooker 1991;Journel and Huijbregts 1978;Webster and Oliver 1990;Zirschky 1985), which can provide an enhanced quantitative description of the variables. Although developed for the mining industry, geostatistics, based on the intrinsic hypothesis, is now widely applied in other scientific domains where variables are measured against a spatial position.…”

Section: Analysis Of Spatial Heterogeneity With Geostatisticsmentioning

confidence: 99%

Applying Pedo-transfer Functions to Simulate Spatial Heterogeneity of Cinnamon Soil Water Retention Characteristics in Western Liaoning Province

Liu

Qin

Wang

2007

Water Resour Manage

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In this study, by measuring soil water retention characteristics and fitting them to van Genuchten Equation, three types of pedo-transfer functions (PTFs) were estimated using linear regression (MLR3) and nonlinear regression (ENR3) based on three textural classifications, and using linear regression (MLR7) based on seven textural classification. And their abilities to quantify soil water retention characteristics and spatial heterogeneity in field scale were evaluated as well. By comparisons between fitted and PTFs-estimated parameters, the parameters from MLR7 and ENR3 were closer to fitted values than ones from MLR3. The results showed that some complex mathematical approaches such as nonlinear regression, and detailed soil classification may obtain more accurate PTFs. The analysis on spatial heterogeneity of retention characteristics using geostatistics indicated that PTFs-estimated parameters' semivariances were fitted a spherical model. Great autocorrelation range and proportion of structural variance for MLR3 and MLR7 shows linear regression could express suitably the spatial heterogeneity, but detailed soil textual classification didn't improve structure of variability.

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“…A model of this type can develop concentration isopleths over an area from weather data averaged over a variety of time periods such as a day, month or year. The corollary approach is to use a spatial interpolation method such as kriging (Carletti et al 2000; Zirschky 1985) to formulate concentration isopleths from measurements derived from time-integrated samplers. However, this review focuses on the instruments available for measuring gases, particulates, and odor, and on plume dispersion models applicable to the determination of contaminants in the vicinity of CAFOs.…”

Section: Background and Recent Developmentsmentioning

confidence: 99%

Monitoring and Modeling of Emissions from Concentrated Animal Feeding Operations: Overview of Methods

Bunton

O’Shaughnessy

Fitzsimmons

et al. 2007

Environ Health Perspect

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Accurate monitors are required to determine ambient concentration levels of contaminants emanating from concentrated animal feeding operations (CAFOs), and accurate models are required to indicate the spatial variability of concentrations over regions affected by CAFOs. A thorough understanding of the spatial and temporal variability of concentration levels could then be associated with locations of healthy individuals or subjects with respiratory ailments to statistically link the presence of CAFOs to the prevalence of ill health effects in local populations. This workgroup report, which was part of the Conference on Environmental Health Impacts of Concentrated Animal Feeding Operations: Anticipating Hazards—Searching for Solutions, describes instrumentation currently available for assessing contaminant concentration levels in the vicinity of CAFOs and reviews plume dispersion models that may be used to estimate concentration levels spatially. Recommendations for further research with respect to ambient air monitoring include accurately determining long-term average concentrations for a region under the influence of CAFO emissions using a combination of instruments based on accuracy, cost, and sampling duration. In addition, development of instruments capable of accurately quantifying adsorbed gases and volatile organic compounds is needed. Further research with respect to plume dispersion models includes identifying and validating the most applicable model for use in predicting downwind concentrations from CAFOs. Additional data are needed to obtain reliable emission rates from CAFOs.

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Geostatistics for environmental monitoring and survey design

Cited by 26 publications

References 36 publications

Assessment of outdoor radiofrequency electromagnetic field exposure through hotspot localization using kriging-based sequential sampling

Assessment of outdoor radiofrequency electromagnetic field exposure through hotspot localization using kriging-based sequential sampling

Applying Pedo-transfer Functions to Simulate Spatial Heterogeneity of Cinnamon Soil Water Retention Characteristics in Western Liaoning Province

Monitoring and Modeling of Emissions from Concentrated Animal Feeding Operations: Overview of Methods

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