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Full Description
It is increasingly clear that good quantitative work in the environmental sciences must be genuinely interdisciplinary. This volume, the proceedings of the first combined TIES/SPRUCE conference held at the University of Sheffield in September 2000, well demonstrates the truth of this assertion, highlighting the successful use of both statistics and mathematics in important practical problems.
It brings together distinguished scientists and engineers to present the most up-to-date and practical methods for quantitative measurement and prediction and is organised around four themes:
- spatial and temporal models and methods;
- environmental sampling and standards;
- atmosphere and ocean;
- risk and uncertainty.
Quantitative Methods for Current Environmental Issues is an invaluable resource for statisticians, applied mathematicians and researchers working on environmental problems, and for those in government agencies and research institutes involved in the analysis of environmental issues.
Contents
I. Spatial and Temporal Models and Methods.- 1 Modeling Spatio-Temporally Misaligned Areal and Point Process Environmental Data.- 2 Space and Space-Time Modeling using Process Convolutions.- 3 Multivariate Kriging for Interpolating with Data from Different Sources.- II. Environmental Sampling and Standards.- 4 Distance Sampling: Recent Advances and Future Directions.- 5 Setting Environmental Standards: A Statistical Approach.- III. Atmosphere and Ocean.- 6 The Interpretation and Validation of Measurements of the Ocean Wave Directional Spectrum.- 7 Thermal Energy Emission and Propagation from Accidents.- 8 Development and Application of an Extended Methodology to Validate Short-Range Atmospheric Dispersion Models.- 9 Uncertainty and Sensitivity of Dispersion Model Results to Meteorological Inputs: Two Case Studies.- IV. Risk and Uncertainty.- 10 Statistics and the Environmental Sciences: Approaches to Model Combination.- 11 Bayesian Analysis of Computer Code Outputs.- 12 The Realities of Decision Making on Risks.
