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Author: Junyu He
Publisher: Frontiers Media SA
ISBN: 2832537448
Category : Science
Languages : en
Pages : 175
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Book Description
With the development of earth observation technologies (such as satellite remote sensing, unmanned aerial vehicle, autonomous underwater vehicle, etc.), an era of big data with important and non-negligible spatial/temporal attributes comes. Novel and rigorous spatiotemporal methodologies and models are needed to process and analyze marine big data. Since many marine environmental processes, such as pollutants diffusion, algae distributions etc., vary or evolve across spatiotemporal domains, detecting the distributions and patterns of marine fauna and, particularly in the coastal regions, will improve our understanding of marine systems and can be beneficial in marine environmental management. The goals of this Research Topic, therefore, are two-fold: (a) to develop methodologies and models in theory and applications, including spatiotemporal geostatistics, geographic information system, deep learning, etc.; (b) to quantitatively gain the knowledge of the marine environment. This Research Topic will provide a platform for researchers to share and exchange their new knowledge gained in a spatiotemporal domain of marine or coastal regions. This Research Topic will cover, but is not limited to, the following areas: • Spatiotemporal variations of physical/chemical/biological indicators (such as chlorophyll, temperature, salinity, colorful dissolved organic matter, suspended solids, nutrients, microplastic, etc.) in marine. • Spatiotemporal variations of potential fishing grounds in marine. • Spatiotemporal variations of the ecosystems in coastal regions, such as salt marshes, mangroves, seagrass, macroalgae, etc. • Spatiotemporal distributions of the pollutants (such as heavy metals, polycyclic aromatic hydrocarbon, etc.) in marine and sediments. • Spatiotemporal evolution pattern modeling and prediction of the marine disasters and abnormal phenomena (such as algal bloom, typhoons, SST anomalies, etc).
Author: Junyu He
Publisher: Frontiers Media SA
ISBN: 2832537448
Category : Science
Languages : en
Pages : 175
Get Book Here
Book Description
With the development of earth observation technologies (such as satellite remote sensing, unmanned aerial vehicle, autonomous underwater vehicle, etc.), an era of big data with important and non-negligible spatial/temporal attributes comes. Novel and rigorous spatiotemporal methodologies and models are needed to process and analyze marine big data. Since many marine environmental processes, such as pollutants diffusion, algae distributions etc., vary or evolve across spatiotemporal domains, detecting the distributions and patterns of marine fauna and, particularly in the coastal regions, will improve our understanding of marine systems and can be beneficial in marine environmental management. The goals of this Research Topic, therefore, are two-fold: (a) to develop methodologies and models in theory and applications, including spatiotemporal geostatistics, geographic information system, deep learning, etc.; (b) to quantitatively gain the knowledge of the marine environment. This Research Topic will provide a platform for researchers to share and exchange their new knowledge gained in a spatiotemporal domain of marine or coastal regions. This Research Topic will cover, but is not limited to, the following areas: • Spatiotemporal variations of physical/chemical/biological indicators (such as chlorophyll, temperature, salinity, colorful dissolved organic matter, suspended solids, nutrients, microplastic, etc.) in marine. • Spatiotemporal variations of potential fishing grounds in marine. • Spatiotemporal variations of the ecosystems in coastal regions, such as salt marshes, mangroves, seagrass, macroalgae, etc. • Spatiotemporal distributions of the pollutants (such as heavy metals, polycyclic aromatic hydrocarbon, etc.) in marine and sediments. • Spatiotemporal evolution pattern modeling and prediction of the marine disasters and abnormal phenomena (such as algal bloom, typhoons, SST anomalies, etc).
Author: Mark R.T. Dale
Publisher: Cambridge University Press
ISBN: 110708931X
Category : Mathematics
Languages : en
Pages : 355
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Book Description
This book clearly describes the many applications of graph theory to ecological questions, providing instruction and encouragement to researchers.
Author: Noel Cressie
Publisher: John Wiley & Sons
ISBN: 1119243041
Category : Mathematics
Languages : en
Pages : 612
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Book Description
Winner of the 2013 DeGroot Prize. A state-of-the-art presentation of spatio-temporal processes, bridging classic ideas with modern hierarchical statistical modeling concepts and the latest computational methods Noel Cressie and Christopher K. Wikle, are also winners of the 2011 PROSE Award in the Mathematics category, for the book “Statistics for Spatio-Temporal Data” (2011), published by John Wiley and Sons. (The PROSE awards, for Professional and Scholarly Excellence, are given by the Association of American Publishers, the national trade association of the US book publishing industry.) Statistics for Spatio-Temporal Data has now been reprinted with small corrections to the text and the bibliography. The overall content and pagination of the new printing remains the same; the difference comes in the form of corrections to typographical errors, editing of incomplete and missing references, and some updated spatio-temporal interpretations. From understanding environmental processes and climate trends to developing new technologies for mapping public-health data and the spread of invasive-species, there is a high demand for statistical analyses of data that take spatial, temporal, and spatio-temporal information into account. Statistics for Spatio-Temporal Data presents a systematic approach to key quantitative techniques that incorporate the latest advances in statistical computing as well as hierarchical, particularly Bayesian, statistical modeling, with an emphasis on dynamical spatio-temporal models. Cressie and Wikle supply a unique presentation that incorporates ideas from the areas of time series and spatial statistics as well as stochastic processes. Beginning with separate treatments of temporal data and spatial data, the book combines these concepts to discuss spatio-temporal statistical methods for understanding complex processes. Topics of coverage include: Exploratory methods for spatio-temporal data, including visualization, spectral analysis, empirical orthogonal function analysis, and LISAs Spatio-temporal covariance functions, spatio-temporal kriging, and time series of spatial processes Development of hierarchical dynamical spatio-temporal models (DSTMs), with discussion of linear and nonlinear DSTMs and computational algorithms for their implementation Quantifying and exploring spatio-temporal variability in scientific applications, including case studies based on real-world environmental data Throughout the book, interesting applications demonstrate the relevance of the presented concepts. Vivid, full-color graphics emphasize the visual nature of the topic, and a related FTP site contains supplementary material. Statistics for Spatio-Temporal Data is an excellent book for a graduate-level course on spatio-temporal statistics. It is also a valuable reference for researchers and practitioners in the fields of applied mathematics, engineering, and the environmental and health sciences.
Author: Stephanie Brodie
Publisher: Frontiers Media SA
ISBN: 2889763013
Category : Science
Languages : en
Pages : 506
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Book Description
The Topic Editors Stephanie Brodie, Christopher Cvitanovic, Maria Grazia Pennino, Jon Lopez and André Frainer declare that they are members of the IMBeR (Integrated Marine Biosphere Research) network and IMECaN (Interdisciplinary Marine Early Career Network) and are collaborating with the IMBeR research community.
Author: Boris Goldengorin
Publisher: Springer Nature
ISBN: 3031316541
Category : Computers
Languages : en
Pages : 447
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Book Description
This book presents the state-of-the-art in the emerging field of data science and includes models for layered security with applications in the protection of sites—such as large gathering places—through high-stake decision-making tasks. Such tasks include cancer diagnostics, self-driving cars, and others where wrong decisions can possibly have catastrophic consequences. Additionally, this book provides readers with automated methods to analyze patterns and models for various types of data, with applications ranging from scientific discovery to business intelligence and analytics. The book primarily includes exploratory data analysis, pattern mining, clustering, and classification supported by real life case studies. The statistical section of this book explores the impact of data mining and modeling on the predictability assessment of time series. Further new notions of mean values based on ideas of multi-criteria optimization are compared with their conventional definitions, leading to new algorithmic approaches to the calculation of the suggested new means. The style of the written chapters and the provision of a broad yet in-depth overview of data mining, integrating novel concepts from machine learning and statistics, make the book accessible to upper level undergraduate and graduate students in data mining courses. Students and professionals specializing in computer and management science, data mining for high-dimensional data, complex graphs and networks will benefit from the cutting-edge ideas and practically motivated case studies in this book.
Author: Alan E. Gelfand
Publisher: CRC Press
ISBN: 1351648543
Category : Mathematics
Languages : en
Pages : 798
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Book Description
This handbook focuses on the enormous literature applying statistical methodology and modelling to environmental and ecological processes. The 21st century statistics community has become increasingly interdisciplinary, bringing a large collection of modern tools to all areas of application in environmental processes. In addition, the environmental community has substantially increased its scope of data collection including observational data, satellite-derived data, and computer model output. The resultant impact in this latter community has been substantial; no longer are simple regression and analysis of variance methods adequate. The contribution of this handbook is to assemble a state-of-the-art view of this interface. Features: An internationally regarded editorial team. A distinguished collection of contributors. A thoroughly contemporary treatment of a substantial interdisciplinary interface. Written to engage both statisticians as well as quantitative environmental researchers. 34 chapters covering methodology, ecological processes, environmental exposure, and statistical methods in climate science.
Author: Jun Xu
Publisher: Frontiers Media SA
ISBN: 283251362X
Category : Science
Languages : en
Pages : 227
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Book Description
Author: Benjamin M. Bolker
Publisher: Princeton University Press
ISBN: 0691125228
Category : Computers
Languages : en
Pages : 408
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Book Description
Introduction and background; Exploratory data analysis and graphics; Deterministic functions for ecological modeling; Probability and stochastic distributions for ecological modeling; Stochatsic simulation and power analysis; Likelihood and all that; Optimization and all that; Likelihood examples; Standar statistics revisited; Modeling variance; Dynamic models.
Author: Athanassios C. Tsikliras
Publisher: Frontiers Media SA
ISBN: 2832537758
Category : Science
Languages : en
Pages : 179
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Book Description
Author: Shiqiu Peng
Publisher: Frontiers Media SA
ISBN: 2832540600
Category : Science
Languages : en
Pages : 295
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Book Description
