Description
Book SynopsisGeostatistical 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 o
Table of ContentsINTRODUCTION TO GEOSTATISTICAL ERROR MANAGEMENT.
Foundations of Geostatistical Error Management.
GEM Perspectives.
Introduction to Error.
STATISTICAL CONSIDERATIONS.
Foundations of Statistics.
Data Distributions.
Distributional Models.
SAMPLING THEORY AND PRACTICE.
Heterogeneity and Sampling.
Sampling Errors.
GEOSTATISTICAL APPRAISAL.
Bivariate Distributions.
Variograms: Quantification of Spatial Continuity.
The Volume-Variance Relationship.
Estimation Variance.
Optimizing Estimation: Kriging.
Practical Aspects of Kriging.
DATA QUALITY OBJECTIVES.
Data Quality Objectives.
Integrating DQOs and STP: Development of Sampling Strategies.
Integrating DQOs and GA: Mapping and Appraisal.
Appendices.
References.
Index.
