Characterising spatial and temporal variation in environmental properties, generatingmapsfromsparse samples,and quantifyinguncertaintiesin the maps,are key concerns across the environmental sciences. The body of tools known as g- statistics offers a powerful means of addressing these and related questions. This volume presents recent research in methodological developments in geostatistics and in a variety of speci?c environmental application areas including soil science, climatology, pollution, health, wildlife mapping, ?sheries and remote sensing, amongst others. This book contains selected contributions from geoENV VII, the 7th Int- national Conference on Geostatistics for Environmental Applications, held in Southampton, UK, in September 2008. Like previous conferences in the series, the meeting attracted a diversity of researchers from across Europe and further a?eld. A total of 82 abstracts were submitted to the conference and from these the organisation committee selected 46 papers for oral presentation and 30 for poster presentation. The chapters contained in the book represent the state-of-the-art in geostatistics for the environmental sciences. The book includes 35 chapters arranged according to their main focus, whether methodological, or in a particular application. All of the chapters included were accepted after review by members of the scienti?c c- mittee and each chapter was also subject to checks by the editors.

Geostatistical Modelling of Wildlife Populations: A Non-stationary Hierarchical Model for Count Data.- Incorporating Survey Data to Improve SpaceTime 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 SpaceTime 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 ofSoil 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.