Geostatistical Error Management

Geostatistical Error Management
Author :
Publisher : John Wiley & Sons
Total Pages : 596
Release :
ISBN-10 : 0471285560
ISBN-13 : 9780471285564
Rating : 4/5 (564 Downloads)

Book Synopsis Geostatistical Error Management by : Jeffrey C. Myers

Download or read book Geostatistical Error Management written by Jeffrey C. Myers and published by John Wiley & Sons. This book was released on 1997-05-13 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geostatistical Error Management Geostatistical modeling conceptsand techniques have become daily practice in mining operations.That's because these precise analytical tools help professionalsquantify uncertainty and make objective decisions in the face ofthorny "real world" challenges. Geostatistical Error Management isthe first book to apply these proven quantitative tools toenvironmental challenges. The centerpiece of this working guide isan innovative decision-making framework, known as geostatisticalerror management (GEM). GEM integrates the related areas of DataQuality Objectives, Sampling Theory & Practice, andGeostatistical Appraisal to create an entirely new set of toolsthat help you more accurately assess resources for collectingenvironmental data, analyze sources of error in sampling, andquantify the extent and levels of contamination at environmentallyimpacted sites needing remediation. This practical,results-oriented resource * Focuses on the environmental applications of geostatisticaltechniques and how they fit into today's regulatory, legal, andengineering environments * Provides step-by-step explanations for applying error managementtools at every stage of an environmental site assessment * Points the way to applying GEM to environmental work beyond siteevaluation and characterization Geostatistical Error Management will enable environmentalspecialists to perform assessments of hazardous waste andenvironmentally impacted sites more accurately and to confidentlymanage uncertainty and error at every phase of a remediationproject.


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The data. Estimation.: Estimation regimes. Estimation variance. Kriging; Block variance. Clecking the variances. Estimation and selection. Further data sets. Nu