Geostatistical Estimation of Spatial Structure GESS
Author | : R. E. Knighton |
Publisher | : |
Total Pages | : 60 |
Release | : 1987 |
Genre | : GESS (Computer program) |
ISBN | : |
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Author | : R. E. Knighton |
Publisher | : |
Total Pages | : 60 |
Release | : 1987 |
Genre | : GESS (Computer program) |
ISBN | : |
Author | : Simon Houlding |
Publisher | : Springer Science & Business Media |
Total Pages | : 180 |
Release | : 2000-06-08 |
Genre | : Mathematics |
ISBN | : 9783540668206 |
Presents a set of linked HTML documents on the application of geostatistical theory, designed to be viewed and navigated with an Internet browser.
Author | : Vera Pawlowsky-Glahn |
Publisher | : Oxford University Press |
Total Pages | : 304 |
Release | : 2004-06-03 |
Genre | : Science |
ISBN | : 0190291370 |
Geostatistical Analysis of Compositional Data provides a comprehensive coverage of the theory and practice of analysis of data that have both spatial and compositional dependence, characteristics of most earth science and environmental measurements.
Author | : P. K. Kitanidis |
Publisher | : Cambridge University Press |
Total Pages | : 276 |
Release | : 1997-05-13 |
Genre | : Science |
ISBN | : 9780521587471 |
Engineers and applied geophysicists routinely encounter interpolation and estimation problems when analysing data from field observations. Introduction to Geostatistics presents practical techniques for the estimation of spatial functions from sparse data. The author's unique approach is a synthesis of classic and geostatistical methods with a focus on the most practical linear minimum-variance estimation methods, and includes suggestions on how to test and extend the applicability of such methods. The author includes many useful methods (often not covered in other geostatistics books) such as estimating variogram parameters, evaluating the need for a variable mean, parameter estimation and model testing in complex cases (e.g. anisotropy, variable mean, and multiple variables), and using information from deterministic mathematical models. Well illustrated with exercises and worked examples taken from hydrogeology, Introduction to Geostatistics assumes no background in statistics and is suitable for graduate-level courses in earth sciences, hydrology, and environmental engineering, and also for self-study.
Author | : Shahrokh Rouhani |
Publisher | : ASTM International |
Total Pages | : 281 |
Release | : 1996 |
Genre | : Environmental geology |
ISBN | : 0803124147 |
Author | : Jaime Gómez-Hernández |
Publisher | : Springer Science & Business Media |
Total Pages | : 562 |
Release | : 2013-11-27 |
Genre | : Science |
ISBN | : 9401592977 |
The Second European Conference on Geostatistics for Environmental Ap plications took place in Valencia, November 18-20, 1998. Two years have past from the first meeting in Lisbon and the geostatistical community has kept active in the environmental field. In these days of congress inflation, we feel that continuity can only be achieved by ensuring quality in the papers. For this reason, all papers in the book have been reviewed by, at least, two referees, and care has been taken to ensure that the reviewer comments have been incorporated in the final version of the manuscript. We are thankful to the members of the scientific committee for their timely review of the scripts. All in all, there are three keynote papers from experts in soil science, climatology and ecology and 43 contributed papers providing a good indication of the status of geostatistics as applied in the environ mental field all over the world. We feel now confident that the geoENV conference series, seeded around a coffee table almost six years ago, will march firmly into the next century.
Author | : Christopher D. Lloyd |
Publisher | : |
Total Pages | : |
Release | : 2020 |
Genre | : Geography |
ISBN | : 9781529748420 |
This entry introduces some key principles around spatial data (i.e., mappable data) in the social sciences and geostatistical methods for their analysis. It takes as its main focus areal data. An example of such data is counts of people within census areas. The results of analysis of such data are dependent on the size and shape of the areas, and this entry considers the implications of the choice of areas for spatial analysis. It also introduces key concepts such as spatial dependence - the tendency for neighbouring data values (e.g., unemployment rates in census areas) to be similar. Methods for analysing spatial dependence are outlined next. The analysis of spatially varying relationships is then discussed, allowing for the possibility that relationships between variables (e.g., poor health and deprivation) may not be the same at all locations. Next, the entry details geostatistical methods for analysing the spatial structure of variables (e.g., the scales over which unemployment rates are concentrated). Finally, methods for overcoming scale effects by reallocating data from one set of areal units to another are detailed.
Author | : Philippe Renard |
Publisher | : Springer Science & Business Media |
Total Pages | : 481 |
Release | : 2005-12-06 |
Genre | : Science |
ISBN | : 354026535X |
The science of geostatistics is now being employed in an increasing number of disciplines in environmental sciences. This book surveys the latest applications of Geostatistics in a broad spectrum of fields including air quality, climatology, ecology, groundwater hydrology, surface hydrology, oceanography, soil contamination, epidemiology and health, natural hazards, and remote sensing.
Author | : Raimon Tolosana-Delgado |
Publisher | : Springer Nature |
Total Pages | : 275 |
Release | : 2021-11-19 |
Genre | : Mathematics |
ISBN | : 303082568X |
This book provides a guided approach to the geostatistical modelling of compositional spatial data. These data are data in proportions, percentages or concentrations distributed in space which exhibit spatial correlation. The book can be divided into four blocks. The first block sets the framework and provides some background on compositional data analysis. Block two introduces compositional exploratory tools for both non-spatial and spatial aspects. Block three covers all necessary facets of multivariate spatial prediction for compositional data: variogram modelling, cokriging and validation. Finally, block four details strategies for simulation of compositional data, including transformations to multivariate normality, Gaussian cosimulation, multipoint simulation of compositional data, and common postprocessing techniques, valid for both Gaussian and multipoint methods. All methods are illustrated via applications to two types of data sets: one a large-scale geochemical survey, comprised of a full suite of geochemical variables, and the other from a mining context, where only the elements of greatest importance are considered. R codes are included for all aspects of the methodology, encapsulated in the R package "gmGeostats", available in CRAN.
Author | : Daniel Simpson Long |
Publisher | : |
Total Pages | : 418 |
Release | : 1993 |
Genre | : Agronomy |
ISBN | : |