Results 201 to 210 of about 7,767 (249)

Soil Lead Risks Associated With Urbanization Histories in Springfield MA and Hartford CT, USA. [PDF]

Geohealth
Perdrial N, Walser SL, Sirkovich EC, Richardson JB, Cope M.   +4 more
europepmc   +1 more source

Seasonal variation and structural influences on indoor radon exposure in residential buildings of Khuzestan Province. [PDF]

Sci Rep
Talepour N, Mesdaghinia A, Nadafi K, Yaghmaeian K, Shahsavani A, Yunesian M, Ahmadi M, Jorfi S, Khafaie MA, Hosainzadeh M, Rahmat ZG, Yousefi Z, Yarahmadi M, Kaydi N, Mousavi SK, Ghasabzadeh S, Jahedi F, Fard MP, Hashemi Z, Mengelizadeh N, Saki H, Shamsedini N, Bazafkan MH, Gourani A, Ghanbari S, Jaafarzadeh N.   +25 more
europepmc   +1 more source

Estimating PM_2.5 concentrations at public schools in North Carolina using multiple data sources and interpolation methods. [PDF]

Sci Rep
Carroll R, Bailey P, Pandey S, McCalla D, Snyder T.   +4 more
europepmc   +1 more source

Geostatistical analysis and multivariate assessment of groundwater quality. [PDF]

Sci Rep
A Alshahrani M, Ahmad M, Laiq M, Nabi M.
europepmc   +1 more source

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Stream Kriging: Incremental and recursive ordinary Kriging over spatiotemporal data streams

Computers and Geosciences, 2016
Ordinary Kriging is widely used for geospatial interpolation and estimation. Due to the O(n3) time complexity of solving the system of linear equations, ordinary Kriging for a large set of source points is computationally intensive. Conducting real-time Kriging interpolation over continuously varying spatiotemporal data streams can therefore be ...
Xu Zhong, Allison Kealy, Matt Duckham
exaly   +3 more sources

Application of Ordinary Kriging for In Situ Site Characterization

, 2021
Application of geostatistical techniques for in situ site characterization has received much attention in the last couple of decades. Kriging is one of the popular and accurate geostatistical techniques for the interpolation of spatially varied random variables.
J. Rojimol, K. B. V. N. Phanindra, B. Umashankar   +2 more
openaire   +3 more sources

Comparing the robustness of ordinary kriging and lognormal kriging: Outlier resistance

Mathematical Geosciences, 1988
Ordinary kriging is well-known to be optimal when the data have a multivariate normal distribution (and if the variogram is known), whereas lognormal kriging presupposes the multivariate lognormality of the data. But in practice, real data never entirely satisfy these assumptions.
Armstrong M
exaly   +2 more sources

Assessing uncertainty in estimates with ordinary and indicator kriging

Computers and Geosciences, 2001
The objective of this paper is to examine the applicability of three geostatistical approaches, ordinary kriging (OK), kriging with a trend model (KT), and indicator kriging (IK), to the assessment of uncertainty in estimates. This paper uses the OK and KT standard error and the conditional standard error of the conditional cumulative distribution ...
Christopher D Lloyd, Peter M Atkinson
exaly   +3 more sources