Quantitative Analysis and Modeling of Earth and Environmental Data: Applications for Spatial and Temporal Variation

Quantitative Analysis and Modeling of Geoscience Data with Spatial Variation and Temporal Dynamics: Detecting, Dating, and Modeling offers a systematic, quantitative analysis of multi-sourced data that provides information about the spatial distribution and temporal dynamics of natural attributes. It includes techniques for handling data that may vary by space and/or time, and aims to improve understanding of the physical laws of change underlying the available numerical datasets, while taking into consideration the in-situ uncertainties and relevant measurement errors (conceptual, technical, computational). The notions and methods presented in Quantitative Analysis and Modeling of Geoscience Data with Spatial Variation and Temporal Dynamics cover a wide range of data in various forms and sources, including hard measurements, soft observations, secondary information and auxiliary variables (ground-level measurements, satellite observations, scientific instruments and records, protocols and surveys, empirical models and charts). Including real-world practical applications as well as practice exercises, this book is a comprehensive step-by-step tutorial of data-driven techniques that will help students and researchers master data analysis in earth and environmental sciences. Addresses the analysis and processing data that varies spatially and/or temporally, which is the case with the majority of data in scientific and engineering disciplinesCovers a wide range of data describing a variety of attributes characterizing physical phenomena and systems including earth, ocean and atmospheric variables, environmental and ecological parameters, population health states, disease indicators, and social and economic characteristicsIncludes case studies and practice exercises at the end of each chapter for both real-world applications and deeper understanding of the concepts presented INDICE: 1. Introduction to Concepts 2. Data Classification, Characterization And Collection 3. Statistical Modeling 4. Geostatistical Modeling 5. Variography 6. Regional and Chrono-regional Estimators 7. Krigology 8. Bayesian Maximum Entropy 9. Software Tutorials Appendix 1. Probability And Random Variable Theory 2. Instructor and Student Resources

• ISBN: 978-0-12-816341-2
• Editorial: Elsevier
• Encuadernacion: Rústica
• Páginas: 420
• Fecha Publicación: 01/01/2020
• Nº Volúmenes: 1
• Idioma: Inglés