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Geostatistical Error Management: Quantifying Uncer

Autor JC Myers
en Limba Engleză Hardback – 20 apr 1997
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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Specificații

ISBN-13: 9780471285564
ISBN-10: 0471285560
Pagini: 596
Dimensiuni: 157 x 236 x 42 mm
Greutate: 0.97 kg
Editura: Wiley
Locul publicării:Hoboken, United States

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Descriere

Geostatistical Error Management Geostatistical modeling concepts and techniques have become daily practice in mining operations. That's because these precise analytical tools help professionals quantify uncertainty and make objective decisions in the face of thorny "real world" challenges.