Spatiotemporal Patterns In Earth Sciences
Download Spatiotemporal Patterns In Earth Sciences PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Spatiotemporal Patterns In Earth Sciences book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Spatiotemporal Patterns in Earth Sciences
Author: Pasquale De Marco
language: en
Publisher: Pasquale De Marco
Release Date: 2025-07-12
Spatiotemporal patterns are ubiquitous in nature and society. From the daily cycle of day and night to the seasonal changes of the Earth's climate, from the distribution of species in a forest to the spread of disease through a population, spatiotemporal patterns shape our world and our lives. This book provides a comprehensive introduction to the study of spatiotemporal patterns, covering the fundamental concepts, methods, and applications of this exciting field. With a focus on real-world examples and applications, this book is written in a clear and accessible style, making it ideal for students, researchers, and practitioners in a variety of disciplines. **Key Features:** * Comprehensive coverage of the fundamental concepts, methods, and applications of spatiotemporal analysis * Clear and accessible writing style, with a focus on real-world examples and applications * No prior knowledge of statistics or mathematics is assumed * Suitable for a broad audience, including students, researchers, and practitioners in a variety of disciplines **Topics Covered:** * The nature of spatiotemporal patterns * Modeling spatiotemporal patterns * Spatiotemporal patterns in earth sciences * Spatiotemporal patterns in environmental sciences * Spatiotemporal patterns in social sciences * Spatiotemporal patterns in health sciences * Spatiotemporal patterns in engineering * Spatiotemporal patterns in computer science * Spatiotemporal patterns in mathematics * Spatiotemporal patterns in physics This book is an essential resource for anyone interested in the study of spatiotemporal patterns. It provides a solid foundation for further research and applications in a wide range of disciplines. If you like this book, write a review!
Deep Learning for the Earth Sciences
Author: Gustau Camps-Valls
language: en
Publisher: John Wiley & Sons
Release Date: 2021-08-18
DEEP LEARNING FOR THE EARTH SCIENCES Explore this insightful treatment of deep learning in the field of earth sciences, from four leading voices Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only recently entered academic curricula and thus has not yet proliferated. Deep Learning for the Earth Sciences delivers a unique perspective and treatment of the concepts, skills, and practices necessary to quickly become familiar with the application of deep learning techniques to the Earth sciences. The book prepares readers to be ready to use the technologies and principles described in their own research. The distinguished editors have also included resources that explain and provide new ideas and recommendations for new research especially useful to those involved in advanced research education or those seeking PhD thesis orientations. Readers will also benefit from the inclusion of: An introduction to deep learning for classification purposes, including advances in image segmentation and encoding priors, anomaly detection and target detection, and domain adaptation An exploration of learning representations and unsupervised deep learning, including deep learning image fusion, image retrieval, and matching and co-registration Practical discussions of regression, fitting, parameter retrieval, forecasting and interpolation An examination of physics-aware deep learning models, including emulation of complex codes and model parametrizations Perfect for PhD students and researchers in the fields of geosciences, image processing, remote sensing, electrical engineering and computer science, and machine learning, Deep Learning for the Earth Sciences will also earn a place in the libraries of machine learning and pattern recognition researchers, engineers, and scientists.
Random Field Models in Earth Sciences
This book is about modeling as a prinicipal component of scientific investigations. In general terms, modeling is the funamental process of combining intellectual creativity with physical knowledge and mathematical techniques in order to learn the properties of the mechanisms underlying a physical phenomenon and make predictions. The book focuses on a specific class of models, namely, random field models and certain of their physical applications in the context of a stochastic data analysis and processing research program. The term application is considered here in the sense wherein the mathematical random field model is shaping, but is also being shaped by, its objects.This book explores the application of random field models and stochastic data processing to problems in hydrogeology, geostatistics, climate modeling, and oil reservoir engineering, among others Researchers in the geosciences who work with models of natural processes will find discussion of; - Spatiotemporal random fields - Space transformation - Multidimensional estimation - Simulation - Sampling design - Stochastic partial differential equations