Die Geostatistik beschreibt Beziehungen natürlicher Größen wie den Metallgehalt von Erzen, die Dicke von Bäumen in einem Waldbestand oder Eigenschaften von Bodenproben bestimmter Regionen. Die enorme Komplexität dieser Variablen verbietet eine Behandlung mit Hilfe mathematischer Standardfunktionen - unumgänglich ist die Berücksichtigung der sogenannten räumlichen Unbestimmtheit und des Unterschiedes zwischen Beschreibung und Interpretation. Wie verschiedene statistische Methoden diesen Anforderungen gerecht werden, untersucht dieses Buch.
A novel, practical approach to modeling spatial uncertainty.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 spatialuncertainty.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 typesof problems they address. Emphasizes the statistical methodologies employed in spatial estimation. Presents simulation techniques and digital models of uncertainty. Features more than 150 figures and many concrete examples throughout the text. 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.
A novel, practical approach to modeling spatial uncertainty.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 spatialuncertainty.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 typesof problems they address. Emphasizes the statistical methodologies employed in spatial estimation. Presents simulation techniques and digital models of uncertainty. Features more than 150 figures and many concrete examples throughout the text. 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.
"This is a book that the geostatistical community has been waiting for long since" "I can recommend anyone interested in geostatistics to get the volume...I am convinced that it will be the volume to cite in the next decade or more." (Journal of Geodsy, November 2000) 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 techniquesand digital models of uncertainty.