Geostatistics: Modeling Spatial Uncertainty, Second Edition - Chilès. Praise for the First Edition". Mathematical Geosciences The state of the art in geostatistics. Geostatistical models and techniques such as kriging and stochastic multi- realizations exploit spatial correlations to evaluate natural resources, help optimize their development, and address environmental issues related to air and water quality, soil pollution, and forestry. Geostatistics: Modeling Spatial Uncertainty, Second Edition presents a comprehensive, up- to- date reference on the topic, now featuring the latest developments in the field. The authors explain both the theory and applications of geostatistics through a unified treatment that emphasizes methodology.
Key topics that are the foundation of geostatistics are explored in- depth, including stationary and nonstationary models; linear and nonlinear methods; change of support; multivariate approaches; and conditional simulations. The Second Edition highlights the growing number of applications of geostatistical methods and discusses three key areas of growth in the field: New results and methods, including kriging very large datasets; kriging with outliers; nonse??
Newly formed connections between geostatistics and other approaches such as radial basis functions, Gaussian Markov random fields, and data assimilation New perspectives on topics such as collocated cokriging, kriging with an external drift, discrete Gaussian change- of- support models, and simulation algorithms Geostatistics, Second Edition is an excellent book for courses on the topic at the graduate level. It also serves as an invaluable reference for earth scientists, mining and petroleum engineers, geophysicists, and environmental statisticians who collect and analyze data in their everyday work.
Geostatistics: Modeling Spatial Uncertainty - Chilès. Product Information. About The Product. A novel, practical approach to modeling spatial uncertainty.
The fact that these models incorporate uncertainty in their. Modeling and Analysis for Spatial. Geostatistics, Modeling Spatial uncertainty. . practical approach to modeling spatial uncertainty. Geostatistics: Modeling Spatial Uncertainty is the only. You have free access to. Geostatistics is a branch of statistics focusing on. theory to model the uncertainty associated with spatial estimation. one can distinguish two modeling.
- . and geostatistical data which can. modeling of local and spatial uncertainty. Delfiner, P. (1999). Geostatistics. Modelling Spatial Uncertainty.
- . Modeling Spatial Uncertainty. The state of the art in geostatistics. You have free access to this content.
- Enter your mobile number or email address below and we'll send you a link to download the free. and forestry. Geostatistics: Modeling Spatial Uncertainty.
- Geostatistics: Modeling Spatial Uncertainty Zheng, Li There are many geostatistics books currently in circulation. Each has its own goals and intended audience.
- . Mathematical Chils,J.-P. 1999.Geostatistics: modeling spatial uncertainty. Wiley series statistics.John Wiley Sons,New York. 2000.Modern spatiotemporal.
- 内容提示: 土地水利行业规范--Geostatistics Modeling Spatial Uncertainty-- 研究报告 文档格式:PDF | 浏览次数:21 | 上传日期:2012-01-21 13:21:57 | 文档星级.
- Modeling Uncertainty in the Earth Sciences Jef Caers Stanford University Modeling spatial uncertainty. Unit free. Complete SGS.
This book deals with statistical models used to describe natural variables distributed in space or in time and space. It takes a practical, unified approach to geostatistics- integrating statistical data with physical equations and geological concepts while stressing the importance of an objective description based on empirical evidence. This unique approach facilitates realistic modeling that accounts for the complexity of natural phenomena and helps solve economic and development problems- in mining, oil exploration, environmental engineering, and other real- world situations involving spatial uncertainty.
Up- to- date, comprehensive, and well- written, Geostatistics: Modeling Spatial Uncertainty explains both theory and applications, covers many useful topics, and offers a wealth of new insights for nonstatisticians and seasoned professionals alike. This volume: * Reviews the most up- to- date geostatistical methods and the types of problems they address.* Emphasizes the statistical methodologies employed in spatial estimation.* Presents simulation techniques and digital models of uncertainty.* Features more than 1. Includes extensive footnoting as well as a thorough bibliography. Geostatistics: Modeling Spatial Uncertainty is the only geostatistical book to address a broad audience in both industry and academia. An invaluable resource for geostatisticians, physicists, mining engineers, and earth science professionals such as petroleum geologists, geophysicists, and hydrogeologists, it is also an excellent supplementary text for graduate- level courses in related subjects.