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This book brings together in one place two dynamic subjects, precision agriculture and geostatistics, that have spatial variation at their core. Geostatistics is applied in precision agriculture (PA) to sampling, prediction, mapping, decision-making, economics, designed experiments, variable-rate applications and so on. Contributions from experts in both fields illustrate how geostatistics can and has been used to advantage with PA data such as yield, soil, crop, pests, aerial photograph, remote and proximal imagery. Geostatistical techniques include variography, ordinary-, disjunctive-, factorial-, indicator-, regression-, simple-, space-time- and co-kriging, and geostatistical simulation. The link between geostatistics and PA will increase as more intensive information on the soil and crops becomes available from sensors and on-the-go technology. This is not a recipe book, but is intended to guide readers in the use of appropriate techniques for the types of data and needs of the farmer in managing the land.

Mathematics --- Geology. Earth sciences --- General ecology and biosociology --- Environmental protection. Environmental technology --- Agronomy --- Agriculture. Animal husbandry. Hunting. Fishery --- Production management --- milieukunde --- landbouw --- landbouwbeleid --- duurzame ontwikkeling --- wiskunde --- geografie --- geologie --- milieutechnologie --- aarde (astronomie)

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As climate change continues to dominate the international environmental agenda, phenology – the study of the timing of recurring biological events – has received increasing research attention, leading to an emerging consensus that phenology can be viewed as an ‘early warning system’ for climate change impact. A multidisciplinary science involving many branches of ecology, geography and remote sensing, phenology to date has lacked a coherent methodological text. This new synthesis, including contributions from many of the world’s leading phenologists, therefore fills a critical gap in the current biological literature. Providing critiques of current methods, as well as detailing novel and emerging methodologies, the book, with its extensive suite of references, provides readers with an understanding of both the theoretical basis and the potential applications required to adopt and adapt new analytical and design methods. An invaluable source book for researchers and students in ecology and climate change science, the book also provides a useful reference for practitioners in a range of sectors, including human health, fisheries, forestry, agriculture and natural resource management.

Statistical science --- Operational research. Game theory --- Probability theory --- Mathematics --- Meteorology. Climatology --- Biomathematics. Biometry. Biostatistics --- General ecology and biosociology --- Environmental protection. Environmental technology --- medische statistiek --- environment --- waarschijnlijkheidstheorie --- milieukunde --- stochastische analyse --- biostatistiek --- statistiek --- milieuzorg --- wiskunde --- milieutechnologie --- kansrekening --- milieubeheer --- klimaatverandering

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Spatial statistics are useful in subjects as diverse as climatology, ecology, economics, environmental and earth sciences, epidemiology, image analysis and more. This book covers the best-known spatial models for three types of spatial data: geostatistical data (stationarity, intrinsic models, variograms, spatial regression and space-time models), areal data (Gibbs-Markov fields and spatial auto-regression) and point pattern data (Poisson, Cox, Gibbs and Markov point processes). The level is relatively advanced, and the presentation concise but complete. The most important statistical methods and their asymptotic properties are described, including estimation in geostatistics, autocorrelation and second-order statistics, maximum likelihood methods, approximate inference using the pseudo-likelihood or Monte-Carlo simulations, statistics for point processes and Bayesian hierarchical models. A chapter is devoted to Markov Chain Monte Carlo simulation (Gibbs sampler, Metropolis-Hastings algorithms and exact simulation). A large number of real examples are studied with R, and each chapter ends with a set of theoretical and applied exercises. While a foundation in probability and mathematical statistics is assumed, three appendices introduce some necessary background. The book is accessible to senior undergraduate students with a solid math background and Ph.D. students in statistics. Furthermore, experienced statisticians and researchers in the above-mentioned fields will find the book valuable as a mathematically sound reference. This book is the English translation of Modélisation et Statistique Spatiales published by Springer in the series Mathématiques & Applications, a series established by Société de Mathématiques Appliquées et Industrielles (SMAI). Carlo Gaetan is Associate Professor of Statistics in the Department of Statistics at the Ca' Foscari University of Venice. Xavier Guyon is Professor Emeritus at the University of Paris 1 Panthéon-Sorbonne. He is author of a Springer monograph on random fields.

Statistical science --- Quantitative methods (economics) --- Operational research. Game theory --- Probability theory --- Mathematics --- Geology. Earth sciences --- General ecology and biosociology --- Environmental protection. Environmental technology --- waarschijnlijkheidstheorie --- milieukunde --- stochastische analyse --- statistiek --- econometrie --- wiskunde --- geografie --- geologie --- milieutechnologie --- kansrekening --- aarde (astronomie) --- statistisch onderzoek

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Uncertainty and Environmental Decision Making: A Handbook of Research and Best Practice presents the state of the art in applying operations research and management science (OR/MS) techniques to a broad range of environmental decision making (EDM) challenges. Drawing on leading researchers in the field, it provides a guided tour of selected methods and tools to help deal with issues as climate change, depleting biodiversity and biocapacity, and more general atmospheric, water and soil pollution problems. Individual peer-reviewed chapters look at applying stochastic reasoning on difficult issues arising in EDM under uncertainty; applying stochastic or robust programming methods to techno-economic modeling of energy/environment interactions; important consequences of uncertainty inherent in weather patterns, the El Nino phenomenon and anticipated climate change; exploiting tools of decision analysis, utility theory and optimal control theory to account for differences in time scales between human development processes and the natural processes of the biosphere; and methods that combine statistical and decision analyses that can support a variety of environmental management problems. This important new work will be of special interest to a wide range of researchers, students, and practitioners in environmental economics, OR/MS, environmental and earth sciences, climatologists, and risk assessment.

Economics --- Nature protection --- Operational research. Game theory --- Mathematical statistics --- Mathematics --- Measuring methods in physics --- General ecology and biosociology --- Environmental protection. Environmental technology --- Planning (firm) --- Environmental planning --- Economic geography --- monitoring --- milieukunde --- ruimtelijke ordening --- besluitvorming --- economie --- mathematische modellen --- sociale economie --- milieubeleid --- milieuzorg --- speltheorie --- econometrie --- wiskunde --- operationeel onderzoek --- milieutechnologie --- milieubeheer --- milieuanalyse