Spatiotemporal Modeling And Analysis In Marine Science

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).

This advanced textbook on modeling, data analysis and numerical techniques for marine science has been developed from a course taught by the authors for many years at the Woods Hole Oceanographic Institute. The first part covers statistics: singular value decomposition, error propagation, least squares regression, principal component analysis, time series analysis and objective interpolation. The second part deals with modeling techniques: finite differences, stability analysis and optimization. The third part describes case studies of actual ocean models of ever increasing dimensionality and complexity, starting with zero-dimensional models and finishing with three-dimensional general circulation models. Throughout the book the general principles and goals of scientific visualization are emphasized through technique and application. Ideal as a textbook for advanced students of oceanography on courses in data analysis and numerical modeling, the book is also an invaluable resource for a broad range of scientists undertaking modeling in chemical, biological, geological and physical oceanography.

Field Methods in Marine Science: From Measurements to Models is an authoritative guide of the methods most appropriate for field research within the marine sciences, from experimental design to data analysis. Written for upper-level undergraduate and graduate students as well as early-career researchers, this textbook also serves as an accessible introduction to the concepts and practice of modeling marine system dynamics. This textbook trains the next generation of field scientists to move beyond the classic methods of data collection and statistical analysis to contemporary methods of numerical modeling; to pursue the assimilation and synthesis of information, not the mere recording of data. Boxes and side bars highlight important questions, interesting facts, relevant examples, and research techniques that supplement the text. Students and researchers alike will find the thorough appendices useful as a way of expanding comprehension of fundamental concepts.

Spatio-temporal Analysis of Extreme Hydrological Events offers an extensive view of the experiences and applications of the latest developments and methodologies for analyzing and understanding extreme environmental and hydrological events. The book addresses the topic using spatio-temporal methods, such as space-time geostatistics, machine learning, statistical theory, hydrological modelling, neural network and evolutionary algorithms. This important resource for both hydrologists and statisticians interested in the framework of spatial and temporal analysis of hydrological events will provide users with an enhanced understanding of the relationship between magnitude, dynamics and the probability of extreme hydrological events. Presents spatio-temporal processes, including multivariate dynamic modelling Provides varying methodological approaches, giving the readers multiple hydrological modelling information to use in their work Includes a variety of case studies making the context of the book relatable to everyday working situations

This advanced textbook on modeling, data analysis and numerical techniques for marine science has been developed from a course taught by the authors for many years at the Woods Hole Oceanographic Institute. The first part covers statistics: singular value decomposition, error propagation, least squares regression, principal component analysis, time series analysis and objective interpolation. The second part deals with modeling techniques: finite differences, stability analysis and optimization. The third part describes case studies of actual ocean models of ever increasing dimensionality and complexity, starting with zero-dimensional models and finishing with three-dimensional general circulation models. Throughout the book hands-on computational examples are introduced using the MATLAB programming language and the principles of scientific visualization are emphasised. Ideal as a textbook for advanced students of oceanography on courses in data analysis and numerical modeling, the book is also an invaluable resource for a broad range of scientists undertaking modeling in chemical, biological, geological and physical oceanography.

This is a textbook on modelling, data analysis and numerical techniques for advanced students and researchers in chemical, biological, geological and physical oceanography.

Ecological dynamics are tremendously complicated and are studied at a variety of spatial and temporal scales. Ecologists often simplify analysis by describing changes in density of individuals across a landscape, and statistical methods are advancing rapidly for studying spatio-temporal dynamics. However, spatio-temporal statistics is often presented using a set of principles that may seem very distant from ecological theory or practice. This book seeks to introduce a minimal set of principles and numerical techniques for spatio-temporal statistics that can be used to implement a wide range of real-world ecological analyses regarding animal movement, population dynamics, community composition, causal attribution, and spatial dynamics. We provide a step-by-step illustration of techniques that combine core spatial-analysis packages in R with low-level computation using Template Model Builder. Techniques are showcased using real-world data from varied ecological systems, providing a toolset for hierarchical modelling of spatio-temporal processes. Spatio-Temporal Models for Ecologists is meant for graduate level students, alongside applied and academic ecologists. Key Features: Foundational ecological principles and analyses Thoughtful and thorough ecological examples Analyses conducted using a minimal toolbox and fast computation Code using R and TMB included in the book and available online

The five-volume set LNCS 9155-9159 constitutes the refereed proceedings of the 15th International Conference on Computational Science and Its Applications, ICCSA 2015, held in Banff, AB, Canada, in June 2015. The 232 revised full papers presented in 22 workshops and a general track were carefully reviewed and selected from 780 initial submissions for inclusion in this volume. They cover various areas in computational science ranging from computational science technologies to specific areas of computational science such as computational geometry and security.