{"product_id":"geostatistics-for-environmental-scientists-isbn-9780470028582","title":"Geostatistics for Environmental Scientists","description":"Geostatistics is essential for environmental scientists. Weather and climate vary from place to place, soil varies at every scale at which it is examined, and even man-made attributes – such as the distribution of pollution – vary. The techniques used in geostatistics are ideally suited to the needs of environmental scientists, who use them to make the best of sparse data for prediction, and top plan future surveys when resources are limited.  \u003cp\u003eGeostatistical technology has advanced much in the last few years and many of these developments are being incorporated into the practitioner’s repertoire. This second edition describes these techniques for environmental scientists. Topics such as stochastic simulation, sampling, data screening, spatial covariances, the variogram and its modeling, and spatial prediction by kriging are described in rich detail. At each stage the underlying theory is fully explained, and the rationale behind the choices given, allowing the reader to appreciate the assumptions and constraints involved.\u003c\/p\u003e  Preface  \u003cp\u003e1 Introduction\u003c\/p\u003e \u003cp\u003e2 Basic Statistics\u003c\/p\u003e \u003cp\u003e3 Prediction and Interpolation\u003c\/p\u003e \u003cp\u003e4 Characterizing Spatial Processes: The Covariance and Variogram\u003c\/p\u003e \u003cp\u003e5 Modelling the Variogram\u003c\/p\u003e \u003cp\u003e6 Reliability of the Experimental Variogram and Nested Sampling\u003c\/p\u003e \u003cp\u003e7 Spectral Analysis\u003c\/p\u003e \u003cp\u003e8 Local Estimation or Prediction: Kriging\u003c\/p\u003e \u003cp\u003e9 Kriging in the Presence of Trend and Factorial Kriging\u003c\/p\u003e \u003cp\u003e10 Cross-Correlation, Coregionalization and Cokriging\u003c\/p\u003e \u003cp\u003e11 Disjunctive Kriging\u003c\/p\u003e \u003cp\u003e12 Stochastic Simulation (new file)\u003c\/p\u003e \u003cp\u003eAppendix A\u003c\/p\u003e \u003cp\u003eAppendix B\u003c\/p\u003e \u003cp\u003eReferences\u003c\/p\u003e \u003cp\u003eIndex\u003c\/p\u003e \"This is certainly an invaluable text for advanced undergraduate and graduate students of spatial variation and environmental research.\" (\u003ci\u003eInternational Journal of Environmental and Analytical Chemistry\u003c\/i\u003e, August 2008)  \u003cp\u003e\u003cstrong\u003eRichard Webster\u003c\/strong\u003e, Rothamsted Research, Harpenden \u003c\/p\u003e\u003cp\u003eDr Webster is the Senior Research Fellow at Rothamsted Research. \u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eMargaret A. Oliver\u003c\/strong\u003e, Visiting Professor, Department of Soil Science, University of Reading\u003cbr\u003eProfessor Oliver has taught geostatistics, applied statistics, multivariate analysis and pedology to undergraduates and postgraduates. She also established a short geostatistics course while at the University of Birmingham, which has now been taught in several countries (e.g. Sweden, USA and Mexico). She is the author of over 70 papers and two co-authored books.   There are many factors that environmental scientists should consider in their research. Weather and climate vary widely between locations, soil varies at every spatial scale at which it is examined, and even man-made attributes, such as the distribution of pollution, fluctuate significantly. To analyse the varied kinds of data and to predict at unvisited places from them, research scientists need to be familiar with the techniques of Geostatistics.  \u003c\/p\u003e\u003cp\u003eThis revised and fully updated second edition of \u003ci\u003eGeostatistics for Environmental Scientists\u003c\/i\u003e provides comprehensive coverage of the techniques involved in this vital branch of statistics. The book\u003c\/p\u003e \u003cul type=\"disc\"\u003e \u003cli\u003eintroduces readers to the most up-to-date statistical techniques, including, sampling, data screening, spatial covariances, the variogram and its modelling;\u003c\/li\u003e \u003cli\u003eincludes a new chapter on stochastic simulation, and covers the latest methods, such as residual maximum likelihood and factorial kriging analysis;\u003c\/li\u003e \u003cli\u003eadopts a practical approach throughout, illustrating the applications with worked examples and case studies;\u003c\/li\u003e \u003cli\u003eprovides step-by-step guidance for analysing environmental survey data;\u003c\/li\u003e \u003cli\u003eexplains the underlying theory and rationale behind the choices faced by the researchers at each stage, allowing the reader to appreciate the assumptions and constraints involved.\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eThe accessible style of \u003ci\u003eGeostatistics for Environmental Scientists, Second Edition\u003c\/i\u003e makes this text invaluable to advanced undergraduate and graduate students of spatial variation and environmental research.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989284864229,"sku":"NP9780470028582","price":169.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9780470028582.jpg?v=1761783515","url":"https:\/\/k12savings.com\/products\/geostatistics-for-environmental-scientists-isbn-9780470028582","provider":"K12savings","version":"1.0","type":"link"}