Application of Indicator Kriging and Ordinary Kriging to Map Spatial Distribution of Trees Species PDF Download

Author: 黃仁梅
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Author: Jacques Rivoirard
Publisher:
ISBN:
Category : Science
Languages : en
Pages : 200

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Linear geostatistics is a fast developing field of research and its principles are extended over other fields of activity. Tools such as the variogram and kriging are now in everyday use for estimating the mean grade of material in an area from values achieved from measured samples. Non-linear geostatistics is at the fore-front of statistical development, it has a potential application over a wide range of practical problems and is likely to occupy an important place in the statutory monitoring and control of air, water, and land pollution. This book provides a comprehensive introduction to the field for geographers and engineers.

Author: S. Rouhani
Publisher:
ISBN:
Category : Environmental geology
Languages : en
Pages : 12

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Geostatistics offers a variety of spatial estimation procedures which are known as kriging. These techniques are commonly used for interpolation of point values at unsampled locations and estimation of average block values. Kriging techniques provide a measure of accuracy in the form of an estimation variance. These estimates are dependent on the model of spatial variability and the relative geometry of measured and estimated locations. Ordinary kriging is a linear minimum-variance interpolator that assumes a constant, but unknown global mean. Other forms of linear kriging includes simple and universal kriging, as well as co-kriging. If measured data display non-Gaussian tendencies, more accurate interpolation may be obtained through non-linear kriging techniques, such as lognormal and indicator kriging.

Author:
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Category : Forests and forestry
Languages : en
Pages : 480

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Author:
Publisher:
ISBN:
Category : Forests and forestry
Languages : en
Pages : 480

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Author:
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ISBN:
Category : Forest management
Languages : en
Pages : 522

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Author: Noel Cressie
Publisher: John Wiley & Sons
ISBN: 1119115183
Category : Mathematics
Languages : en
Pages : 931

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Book Description
The Wiley Classics Library consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. Spatial statistics — analyzing spatial data through statistical models — has proven exceptionally versatile, encompassing problems ranging from the microscopic to the astronomic. However, for the scientist and engineer faced only with scattered and uneven treatments of the subject in the scientific literature, learning how to make practical use of spatial statistics in day-to-day analytical work is very difficult. Designed exclusively for scientists eager to tap into the enormous potential of this analytical tool and upgrade their range of technical skills, Statistics for Spatial Data is a comprehensive, single-source guide to both the theory and applied aspects of spatial statistical methods. The hard-cover edition was hailed by Mathematical Reviews as an "excellent book which will become a basic reference." This paper-back edition of the 1993 edition, is designed to meet the many technological challenges facing the scientist and engineer. Concentrating on the three areas of geostatistical data, lattice data, and point patterns, the book sheds light on the link between data and model, revealing how design, inference, and diagnostics are an outgrowth of that link. It then explores new methods to reveal just how spatial statistical models can be used to solve important problems in a host of areas in science and engineering. Discussion includes: Exploratory spatial data analysis Spectral theory for stationary processes Spatial scale Simulation methods for spatial processes Spatial bootstrapping Statistical image analysis and remote sensing Computational aspects of model fitting Application of models to disease mapping Designed to accommodate the practical needs of the professional, it features a unified and common notation for its subject as well as many detailed examples woven into the text, numerous illustrations (including graphs that illuminate the theory discussed) and over 1,000 references. Fully balancing theory with applications, Statistics for Spatial Data, Revised Edition is an exceptionally clear guide on making optimal use of one of the ascendant analytical tools of the decade, one that has begun to capture the imagination of professionals in biology, earth science, civil, electrical, and agricultural engineering, geography, epidemiology, and ecology.

Author: Margaret A. Oliver
Publisher: Springer
ISBN: 3319158651
Category : Technology & Engineering
Languages : en
Pages : 106

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Book Description
This brief will provide a bridge in succinct form between the geostatistics textbooks and the computer manuals for `push-button' practice. It is becoming increasingly important for practitioners, especially neophytes, to understand what underlies modern geostatistics and the currently available software so that they can choose sensibly and draw correct conclusions from their analysis and mapping. The brief will contain some theory, but only that needed for practitioners to understand the essential steps in analyses. It will guide readers sequentially through the stages of properly designed sampling, exploratory data analysis, variography (computing the variogram and modelling it), followed by ordinary kriging and finally mapping kriged estimates and their errors. There will be short section on trend and universal kriging. Other types of kriging will be mentioned so that readers can delve further in the substantive literature to tackle more complex tasks.

Author: Nicolas Remy
Publisher: Cambridge University Press
ISBN: 1139473468
Category : Science
Languages : en
Pages : 302

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The Stanford Geostatistical Modeling Software (SGeMS) is an open-source computer package for solving problems involving spatially related variables. It provides geostatistics practitioners with a user-friendly interface, an interactive 3-D visualization, and a wide selection of algorithms. This practical book provides a step-by-step guide to using SGeMS algorithms. It explains the underlying theory, demonstrates their implementation, discusses their potential limitations, and helps the user make an informed decision about the choice of one algorithm over another. Users can complete complex tasks using the embedded scripting language, and new algorithms can be developed and integrated through the SGeMS plug-in mechanism. SGeMS was the first software to provide algorithms for multiple-point statistics, and the book presents a discussion of the corresponding theory and applications. Incorporating the full SGeMS software (now available from www.cambridge.org/9781107403246), this book is a useful user-guide for Earth Science graduates and researchers, as well as practitioners of environmental mining and petroleum engineering.

Author: Richard Webster
Publisher: John Wiley & Sons
ISBN: 9780470517260
Category : Mathematics
Languages : en
Pages : 330

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Book Description
Geostatistics is essential for environmental scientists. Weather and climate vary from place to place, soil varies at every scale at which it is examined, and even man-made attributes – such as the distribution of pollution – vary. The techniques used in geostatistics are ideally suited to the needs of environmental scientists, who use them to make the best of sparse data for prediction, and top plan future surveys when resources are limited. Geostatistical technology has advanced much in the last few years and many of these developments are being incorporated into the practitioner’s repertoire. This second edition describes these techniques for environmental scientists. Topics such as stochastic simulation, sampling, data screening, spatial covariances, the variogram and its modeling, and spatial prediction by kriging are described in rich detail. At each stage the underlying theory is fully explained, and the rationale behind the choices given, allowing the reader to appreciate the assumptions and constraints involved.