Geostatistical Modelling of Wildlife Populations: A Non-stationary Hierarchical Model for Count Data -- Incorporating Survey Data to Improve Space–Time Geostatistical Analysis of King Prawn Catch Rate -- Multivariate Interpolation of Monthly Precipitation Amount in the United Kingdom -- Extreme Precipitation Modelling Using Geostatistics and Machine Learning Algorithms -- On Geostatistical Analysis of Rainfall Using Data from Boundary Sites -- Geostatistics Applied to the City of Porto Urban Climatology -- Integrating Meteorological Dynamic Data and Historical Data into a Stochastic Model for Predicting Forest Fires Risk Maps -- Using Geostatistical Methods in the Analysis of Public Health Data: The Final Frontier? -- Second-Order Analysis of the Spatio-temporal Distribution of Human Campylobacteriosis in Preston, Lancashire -- Application of Geostatistics in Cancer Studies -- Blocking Markov Chain Monte Carlo Schemes for Inverse Stochastic Hydrogeological Modeling -- Simulation of Fine-Scale Heterogeneity of Meandering River Aquifer Analogues: Comparing Different Approaches -- Application of Multiple-Point Geostatistics on Modelling Groundwater Flow and Transport in a Cross-Bedded Aquifer -- Assessment of the Impact of Pollution by Arsenic in the Vicinity of Panasqueira Mine (Portugal) -- Simulation of Continuous Variables at Meander Structures: Application to Contaminated Sediments of a Lagoon -- Joint Space–Time Geostatistical Model for Air Quality Surveillance/Monitoring System -- Geostatistical Methods for Polluted Sites Characterization -- Geostatistical Mapping of Outfall Plume Dispersion Data Gathered with an Autonomous Underwater Vehicle -- Change of the A Priori Stochastic Structure in the Conditional Simulation of Transmissivity Fields -- Geostatistical Interpolation of Soil Properties in Boom Clay in Flanders -- An Examination of Transformation Techniques to Investigate and Interpret Multivariate Geochemical Data Analysis: Tellus Case Study -- Shelling in the First World War Increased the Soil Heavy Metal Concentration -- A Geostatistical Analysis of Rubber Tree Growth Characteristics and Soil Physical Attributes -- Investigating the Potential of Area-to-Area and Area-to-Point Kriging for Defining Management Zones for Precision Farming of Cranberries -- Estimating the Local Small Support Semivariogram for Use in Super-Resolution Mapping -- Modeling Spatial Uncertainty for Locally Uncertain Data -- Spatial Interpolation Using Copula-Based Geostatistical Models -- Exchanging Uncertainty: Interoperable Geostatistics? -- Hierarchical Bayesian Model for Gaussian, Poisson and Ordinal Random Fields -- Detection of Optimal Models in Parameter Space with Support Vector Machines -- Robust Automatic Mapping Algorithms in a Network Monitoring Scenario -- Parallel Geostatistics for Sparse and Dense Datasets -- Multiple Point Geostatistical Simulation with Simulated Annealing: Implementation Using Speculative Parallel Computing -- Application of Copulas in Geostatistics -- Integrating Prior Knowledge and Locally Varying Parameters with Moving-GeoStatistics: Methodology and Application to Bathymetric Mapping.

This volume brings together selected contributions from geoENV 2008, the 7th International Conference on Geostatistics for Environmental Applications, held in Southampton, UK, in September 2008. This book presents the state-of-the-art in geostatistics for the environmental sciences. It includes a wide range of methodological advances and applications. It offers insight and guidance for researchers, professionals, graduate students and others seeking information on the latest perspectives in the field. The rich body of applications will enable those new to geostatistics to assess the utility of the methods for their own applications. The book includes 35 chapters on topics as diverse as methodological developments, applications in the soil sciences, climatology, pollution, health, wildlife mapping, fisheries and remote sensing, amongst other areas. With its focus on environmental applications of geostatistics, rather than the more traditional geostatistical remit of mining and petroleum exploration, this book is part of a series that presents an invaluable resource. This book will be a first port of call for those who wish to apply geostatistical methods in the environmental sciences. Audience: Researchers, scientists, professionals, institutes, libraries, graduate students of geosciences, geostatistics, spatial statistics, environmental science and engineering, ecology, oceanography, climatology, hydrology, soil and forestry science.