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Spatial statistics

In the context of spatial statistics (Cressie 1991), the estimation algorithm in PDF codes is data dense. In other words, the number of statistically independent data points is much larger than the number of parameters that must be estimated. [Pg.371]

Mecke, K.R. (2000) Additivity, convexity, and beyond Applications of Minkowski functionals in statistical physics, in Statistical Physics and Spatial Statistics The Art of Analyzing and Modeling Spatial Structures and Pattern Formation, K.R. Mecke and D. Stoyan (eds.), Springer, Berlin, pp. 111-184... [Pg.320]

Cheng, Q. (1999a). Multifractality and spatial statistics. Comput. Geos a. 25(10), 946—961. [Pg.171]

Robinson and Ayuso (2004) used spatial statistical tests and lead isotope tracers to measure the influence of arsenical pesticide use on stream sediment chemistry in New England. Factor analysis on metal concentrations in 1600 stream sediment samples were grouped according to their agricultural-index value (areas inferred to have used arsenical pesticides extensively). Pb and As contents were correlated, and... [Pg.289]

One problem encountered when assessing exposure of human populations to contaminated land is spatial heterogeneity of pollution. To overcome this problem, Gay and Korre (2006) propose the combinations of spatial statistical methods for mapping soil concentrations, and probabilistic human health risk assessment methods. They applied geostatistical methods to map As concentrations in soil. Subsequently, an age-stratified human population was mapped across the contaminated area, and the intake of As by individuals was calculated using a modified version of the Contaminated Land Exposure Assessment (CLEA) model. This approach allowed a... [Pg.32]

Anselin, L. Spatial statistical modeling in a GIS environment. In Maguire, D., Batty, M., Goodchild, M., editors. GIS, spatial analysis, and modeling. Redlands, CA ESRI Press 2005. p. 498. [Pg.84]

On average, the correct shape of the Voronoi cell is spherical. Thus, the correct overall material model for the assumption of a random distribution is a collection of spherical cells of different sizes, each containing a single sphere. Strictly speaking, any overall property of the material should be obtained by summing the contributions from the different cell sizes. This summing may be carried out by application of a dispersion factor to the property value found for the cell describing the overall volume fraction (12). The results presented here were obtained for the cells that describe the overall volume fraction. The application of the spatial statistical model to take into account the effect of the variable cell size is the subject of current work. [Pg.15]

Contents indude combining data and data uncertainty, spatial statistics, models and data interpretation, environmental management, geographical information systems, and environmental statistics. [Pg.72]

Spatial Statistics and Geographic Information Systems in Epidemiology and Public Health... [Pg.404]

Harlow, D. G., Cawley, N. R., and Wei, R. P., Spatial Statistics of Particles and Corrosion Pits in 2024-T3 Aluminum Alloy, Proceedings of Canadian Congress of Applied Mechanics, May 28-June 2 (1995), Victoria, British Columbia, 116-117. [Pg.209]

One additional aspect of odor concentration and its meaning to animals may be related to the spatial statistics of odor-concentration distribution. The concentration may convey information about the distance of the animal from the odor source. " in spite of studies that show that animals will perform... [Pg.213]

Spatial Statistics. Understanding areas of space requires the analysis of large amounts of data. Spatial statistics are used in fields such as climatology, agricultural science, and geology. Statistical methods... [Pg.1522]

Stein, Alfred, Ben Gorte, and Freek van der Meer, eds. Spatial Statistics for Remote Sensing. Boston Kluwer Academic, 2002. A guidebook on reliability that shows where errors occur and how to experiment effectively, and explains interpolation, interpretation, and decision support. [Pg.1608]

Pegel S, POtschke P, Villmow T, Stoyan D and Heinrich G (2009) Spatial statistics of carbon nanotube polymer composites. Polymer 50 2123-2132. [Pg.188]

K. Jacobs, R. Seemann, and K. Mecke, Dynamics of structure formation in thin films a special spatial analysis. In eds., K. R. Mecke and D. Stoyan, Statistical Physics and Spatial Statistics. Vol. 554. Lecture Notes in Physics, Berlin Springer. 72-91 (2000). ISBN 3-540-67750-X. [Pg.149]

Besag J., York J., Mollie A. (1991). Bayesian Image Restoration with Two Applications In Spatial Statistics. Annals of the Institute of Statistical Mathematics, 43,1-59. Bobbio A., Codetta D. (2004). Parametric fault trees with dynamic gates and repair boxes, in Proc. Annual Symposium on Reliability and Maintainability . 459 65. [Pg.556]

Science Technology of Land Water Use Economy, and Temporal Spatial Statistics... [Pg.67]

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See also in sourсe #XX -- [ Pg.140 ]



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Spatial point statistics

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