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Spatial Modeling In Natural Sciences And Engineering
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Book Synopsis Spatial Modeling in Natural Sciences and Engineering by : Jürgen Friedrich
Download or read book Spatial Modeling in Natural Sciences and Engineering written by Jürgen Friedrich and published by Springer Science & Business Media. This book was released on 2011-06-27 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: The author introduces the reader to the creation and implementation of space-related models by applying a learning-by-doing and problem-oriented approach. The required procedural skills are rarely taught at universities and many scientists and engineers struggle to transfer a model into a computer program. The purpose of this book is to fill this gap. It moves from simple to more complex applications, covering various important topics in the sequence: dynamic matrix processing, 2D and 3D graphics, databases, Java applets and parallel computing. A file (SMOP.zip) with all examples can be downloaded free of charge from the Internet at http://de.geocities.com/bsttc2/book.
Book Synopsis Spatial Modeling in GIS and R for Earth and Environmental Sciences by : Hamid Reza Pourghasemi
Download or read book Spatial Modeling in GIS and R for Earth and Environmental Sciences written by Hamid Reza Pourghasemi and published by Elsevier. This book was released on 2019-01-18 with total page 798 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial Modeling in GIS and R for Earth and Environmental Sciences offers an integrated approach to spatial modelling using both GIS and R. Given the importance of Geographical Information Systems and geostatistics across a variety of applications in Earth and Environmental Science, a clear link between GIS and open source software is essential for the study of spatial objects or phenomena that occur in the real world and facilitate problem-solving. Organized into clear sections on applications and using case studies, the book helps researchers to more quickly understand GIS data and formulate more complex conclusions. The book is the first reference to provide methods and applications for combining the use of R and GIS in modeling spatial processes. It is an essential tool for students and researchers in earth and environmental science, especially those looking to better utilize GIS and spatial modeling. Offers a clear, interdisciplinary guide to serve researchers in a variety of fields, including hazards, land surveying, remote sensing, cartography, geophysics, geology, natural resources, environment and geography Provides an overview, methods and case studies for each application Expresses concepts and methods at an appropriate level for both students and new users to learn by example
Book Synopsis Random Fields for Spatial Data Modeling by : Dionissios T. Hristopulos
Download or read book Random Fields for Spatial Data Modeling written by Dionissios T. Hristopulos and published by Springer Nature. This book was released on 2020-02-17 with total page 884 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an inter-disciplinary introduction to the theory of random fields and its applications. Spatial models and spatial data analysis are integral parts of many scientific and engineering disciplines. Random fields provide a general theoretical framework for the development of spatial models and their applications in data analysis. The contents of the book include topics from classical statistics and random field theory (regression models, Gaussian random fields, stationarity, correlation functions) spatial statistics (variogram estimation, model inference, kriging-based prediction) and statistical physics (fractals, Ising model, simulated annealing, maximum entropy, functional integral representations, perturbation and variational methods). The book also explores links between random fields, Gaussian processes and neural networks used in machine learning. Connections with applied mathematics are highlighted by means of models based on stochastic partial differential equations. An interlude on autoregressive time series provides useful lower-dimensional analogies and a connection with the classical linear harmonic oscillator. Other chapters focus on non-Gaussian random fields and stochastic simulation methods. The book also presents results based on the author’s research on Spartan random fields that were inspired by statistical field theories originating in physics. The equivalence of the one-dimensional Spartan random field model with the classical, linear, damped harmonic oscillator driven by white noise is highlighted. Ideas with potentially significant computational gains for the processing of big spatial data are presented and discussed. The final chapter concludes with a description of the Karhunen-Loève expansion of the Spartan model. The book will appeal to engineers, physicists, and geoscientists whose research involves spatial models or spatial data analysis. Anyone with background in probability and statistics can read at least parts of the book. Some chapters will be easier to understand by readers familiar with differential equations and Fourier transforms.
Book Synopsis Natural Hazards GIS-Based Spatial Modeling Using Data Mining Techniques by : Hamid Reza Pourghasemi
Download or read book Natural Hazards GIS-Based Spatial Modeling Using Data Mining Techniques written by Hamid Reza Pourghasemi and published by Springer. This book was released on 2018-12-13 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume assesses capabilities of data mining algorithms for spatial modeling of natural hazards in different countries based on a collection of essays written by experts in the field. The book is organized on different hazards including landslides, flood, forest fire, land subsidence, earthquake, and gully erosion. Chapters were peer-reviewed by recognized scholars in the field of natural hazards research. Each chapter provides an overview on the topic, methods applied, and discusses examples used. The concepts and methods are explained at a level that allows undergraduates to understand and other readers learn through examples. This edited volume is shaped and structured to provide the reader with a comprehensive overview of all covered topics. It serves as a reference for researchers from different fields including land surveying, remote sensing, cartography, GIS, geophysics, geology, natural resources, and geography. It also serves as a guide for researchers, students, organizations, and decision makers active in land use planning and hazard management.
Book Synopsis Value of Information in the Earth Sciences by : Jo Eidsvik
Download or read book Value of Information in the Earth Sciences written by Jo Eidsvik and published by Cambridge University Press. This book was released on 2015-11-19 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gathering the right kind and the right amount of information is crucial for any decision-making process. This book presents a unified framework for assessing the value of potential data gathering schemes by integrating spatial modelling and decision analysis, with a focus on the Earth sciences. The authors discuss the value of imperfect versus perfect information, and the value of total versus partial information, where only subsets of the data are acquired. Concepts are illustrated using a suite of quantitative tools from decision analysis, such as decision trees and influence diagrams, as well as models for continuous and discrete dependent spatial variables, including Bayesian networks, Markov random fields, Gaussian processes, and multiple-point geostatistics. Unique in scope, this book is of interest to students, researchers and industry professionals in the Earth and environmental sciences, who use applied statistics and decision analysis techniques, and particularly to those working in petroleum, mining, and environmental geoscience.
Book Synopsis Spatial Regression Models for the Social Sciences by : Guangqing Chi
Download or read book Spatial Regression Models for the Social Sciences written by Guangqing Chi and published by SAGE Publications. This book was released on 2019-03-06 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Space and geography are important aspects of social science research in fields such as criminology, sociology, political science, and public health. Many social scientists are interested in the spatial clustering of various behaviors and events. There has been a rapid development of interest in regression methods for analyzing spatial data over recent years, but little available on the topic that is aimed at graduate students and advanced undergraduate classes in the social sciences (most texts are for the natural sciences, or regional science, or economics, and require a good understanding of advanced statistics and probability theory). Spatial Regression Models for the Social Sciences fills the gap, and focuses on the methods that are commonly used by social scientists. Each spatial regression method is introduced in the same way. Guangqing Chi and Jun Zhu explain what each method is and when and how to apply it, by connecting it to social science research topics. They try to avoid mathematical formulas and symbols as much as possible. Secondly, throughout the book they use the same social science example to demonstrate applications of each method and what the results can tell us. Spatial Regression Models for the Social Sciences provides comprehensive coverage of spatial regression methods for social scientists and introduces the methods in an easy-to-follow manner.
Book Synopsis Discipline-Based Education Research by : National Research Council
Download or read book Discipline-Based Education Research written by National Research Council and published by National Academies Press. This book was released on 2012-08-27 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: The National Science Foundation funded a synthesis study on the status, contributions, and future direction of discipline-based education research (DBER) in physics, biological sciences, geosciences, and chemistry. DBER combines knowledge of teaching and learning with deep knowledge of discipline-specific science content. It describes the discipline-specific difficulties learners face and the specialized intellectual and instructional resources that can facilitate student understanding. Discipline-Based Education Research is based on a 30-month study built on two workshops held in 2008 to explore evidence on promising practices in undergraduate science, technology, engineering, and mathematics (STEM) education. This book asks questions that are essential to advancing DBER and broadening its impact on undergraduate science teaching and learning. The book provides empirical research on undergraduate teaching and learning in the sciences, explores the extent to which this research currently influences undergraduate instruction, and identifies the intellectual and material resources required to further develop DBER. Discipline-Based Education Research provides guidance for future DBER research. In addition, the findings and recommendations of this report may invite, if not assist, post-secondary institutions to increase interest and research activity in DBER and improve its quality and usefulness across all natural science disciples, as well as guide instruction and assessment across natural science courses to improve student learning. The book brings greater focus to issues of student attrition in the natural sciences that are related to the quality of instruction. Discipline-Based Education Research will be of interest to educators, policy makers, researchers, scholars, decision makers in universities, government agencies, curriculum developers, research sponsors, and education advocacy groups.
Book Synopsis Value of Information in the Earth Sciences by : Jo Eidsvik
Download or read book Value of Information in the Earth Sciences written by Jo Eidsvik and published by Cambridge University Press. This book was released on 2015-11-19 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a unified framework for assessing the value of potential data-gathering schemes, with a focus on the Earth sciences.
Book Synopsis Fundamentals of Spatial Analysis and Modelling by : Jay Gao
Download or read book Fundamentals of Spatial Analysis and Modelling written by Jay Gao and published by CRC Press. This book was released on 2021-12-15 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides comprehensive and in-depth explanations of all topics related to spatial analysis and spatiotemporal simulation, including how spatial data are acquired, represented digitally, and spatially aggregated. Also features the nature of space and how it is measured. Descriptive, explanatory, and inferential analyses are covered for point, line, and area data. It captures the latest developments in spatiotemporal simulation with cellular automata and agent-based modelling, and through practical examples discusses how spatial analysis and modelling can be implemented in different computing platforms. A much-needed textbook for a course at upper undergraduate and postgraduate levels.
Book Synopsis Spatial Modeling Principles in Earth Sciences by : Zekai Sen
Download or read book Spatial Modeling Principles in Earth Sciences written by Zekai Sen and published by Springer Science & Business Media. This book was released on 2009-06-10 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial Modeling Principles in Earth Sciences presents fundamentals of spatial data analysis used in hydrology, geology, meteorology, atmospheric science and related fields. It examines methods for the quantitative determination of the spatial distribution patterns. This book brings together the material from the current literature in earth sciences and practical examples. It provides a sound background of philosophical, logical, rational and physical principles of spatial data and analysis, and explains how it can be modeled and applied in earth sciences projects and designs. It collects information not previously available in one source, and provides methodology for the treatment of spatial data to find the most rational and practical solution. The book is a valuable resource for students, researchers and practitioners of a broad range of disciplines including geology, geography, hydrology, meteorology, environment, image processing, spatial modeling and related topics.
Book Synopsis Spatial Modeling in Forest Resources Management by : Pravat Kumar Shit
Download or read book Spatial Modeling in Forest Resources Management written by Pravat Kumar Shit and published by Springer Nature. This book was released on 2020-10-08 with total page 675 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book demonstrates the measurement, monitoring, mapping, and modeling of forest resources. It explores state-of-the-art techniques based on open-source software & R statistical programming and modeling specifically, with a focus on the recent trends in data mining/machine learning techniques and robust modeling in forest resources. Discusses major topics such as forest health assessment, estimating forest biomass & carbon stock, land use forest cover (LUFC), dynamic vegetation modeling (DVM) approaches, forest-based rural livelihood, habitat suitability analysis, biodiversity and ecology, and biodiversity, the book presents novel advances and applications of RS-GIS and R in a precise and clear manner. By offering insights into various concepts and their importance for real-world applications, it equips researchers, professionals, and policy-makers with the knowledge and skills to tackle a wide range of issues related to geographic data, including those with scientific, societal, and environmental implications.
Book Synopsis Trends in Spatial Analysis and Modelling by : Martin Behnisch
Download or read book Trends in Spatial Analysis and Modelling written by Martin Behnisch and published by Springer. This book was released on 2017-10-24 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of original research papers that focus on recent developments in Spatial Analysis and Modelling with direct relevance to settlements and infrastructure. Topics include new types of data (such as simulation data), applications of methods to support decision-making, and investigations of human-environment data in order to recognize significance for structures, functions and processes of attributes. Research incorporated ranges from theoretical through methodological to applied work. It is subdivided into four main parts: the first focusing on the research of settlements and infrastructure, the second studies aspects of Geographic Data Mining, the third presents contributions in the field of Spatial Modelling, System Dynamics and Geosimulation, and the fourth part is dedicated to Multi-Scale Representation and Analysis. The book is valuable to those with a scholarly interest in spatial sciences, urban and spatial planning, as well as anyone interested in spatial analysis and the planning of human settlements and infrastructure. Most of the selected papers were originally presented at the “International Land Use Symposium (ILUS 2015): Trends in Spatial Analysis and Modelling of Settlements and Infrastructure” November 11-13 2015, in Dresden, Germany.
Book Synopsis Modeling Uncertainty in the Earth Sciences by : Jef Caers
Download or read book Modeling Uncertainty in the Earth Sciences written by Jef Caers and published by John Wiley & Sons. This book was released on 2011-05-25 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling Uncertainty in the Earth Sciences highlights the various issues, techniques and practical modeling tools available for modeling the uncertainty of complex Earth systems and the impact that it has on practical situations. The aim of the book is to provide an introductory overview which covers a broad range of tried-and-tested tools. Descriptions of concepts, philosophies, challenges, methodologies and workflows give the reader an understanding of the best way to make decisions under uncertainty for Earth Science problems. The book covers key issues such as: Spatial and time aspect; large complexity and dimensionality; computation power; costs of 'engineering' the Earth; uncertainty in the modeling and decision process. Focusing on reliable and practical methods this book provides an invaluable primer for the complex area of decision making with uncertainty in the Earth Sciences.
Book Synopsis Learning to Think Spatially by : National Research Council
Download or read book Learning to Think Spatially written by National Research Council and published by National Academies Press. This book was released on 2005-02-03 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learning to Think Spatially examines how spatial thinking might be incorporated into existing standards-based instruction across the school curriculum. Spatial thinking must be recognized as a fundamental part of Kâ€"12 education and as an integrator and a facilitator for problem solving across the curriculum. With advances in computing technologies and the increasing availability of geospatial data, spatial thinking will play a significant role in the information-based economy of the twenty-first century. Using appropriately designed support systems tailored to the Kâ€"12 context, spatial thinking can be taught formally to all students. A geographic information system (GIS) offers one example of a high-technology support system that can enable students and teachers to practice and apply spatial thinking in many areas of the curriculum.
Book Synopsis Principles of Modeling Uncertainties in Spatial Data and Spatial Analyses by : Wenzhong Shi
Download or read book Principles of Modeling Uncertainties in Spatial Data and Spatial Analyses written by Wenzhong Shi and published by CRC Press. This book was released on 2009-09-30 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: When compared to classical sciences such as math, with roots in prehistory, and physics, with roots in antiquity, geographical information science (GISci) is the new kid on the block. Its theoretical foundations are therefore still developing and data quality and uncertainty modeling for spatial data and spatial analysis is an important branch of that theory. Principles of Modeling Uncertainties in Spatial Data and Spatial Analyses outlines the foundational principles and supplies a firm grasp of the disciplines’ theoretical underpinnings. Comprehensive, Systematic Review of Methods for Handling Uncertainties The book summarizes the principles of modeling uncertainty of spatial data and spatial analysis, and then introduces the developed methods for handling uncertainties in spatial data and modeling uncertainties in spatial models. Building on this foundation, the book goes on to explore modeling uncertainties in spatial analyses and describe methods for presentation of data as quality information. Progressing from basic to advanced topics, the organization of the contents reflects the four major theoretical breakthroughs in uncertainty modeling: advances in spatial object representation, uncertainty modeling for static spatial data to dynamic spatial analyses, uncertainty modeling for spatial data to spatial models, and error description of spatial data to spatial data quality control. Determine Fitness-of-Use for Your Applications Modeling uncertainties is essential for the development of geographic information science. Uncertainties always exist in GIS and are then propagated in the results of any spatial analysis. The book delineates how GIS can be a better tool for decision-making and demonstrates how the methods covered can be used to control the data quality of GIS products.
Book Synopsis Spatial Regression Models by : Michael D. Ward
Download or read book Spatial Regression Models written by Michael D. Ward and published by SAGE Publications. This book was released on 2018-04-10 with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial Regression Models illustrates the use of spatial analysis in the social sciences within a regression framework and is accessible to readers with no prior background in spatial analysis. The text covers different modeling-related topics for continuous dependent variables, including: mapping data on spatial units, exploratory spatial data analysis, working with regression models that have spatially dependent regressors, and estimating regression models with spatially correlated error structures. Using social sciences examples based on real data, Michael D. Ward and Kristian Skrede Gleditsch illustrate the concepts discussed, and show how to obtain and interpret relevant results. The examples are presented along with the relevant code to replicate all the analysis using the R package for statistical computing. Users can download both the data and computer code to work through all the examples found in the text. New to the Second Edition is a chapter on mapping as data exploration and its role in the research process, updates to all chapters based on substantive and methodological work, as well as software updates, and information on estimation of time-series, cross-sectional spatial models.
Book Synopsis GIS and Spatial Analysis for the Social Sciences by : Robert Nash Parker
Download or read book GIS and Spatial Analysis for the Social Sciences written by Robert Nash Parker and published by Routledge. This book was released on 2009-09-10 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book to provide sociologists, criminologists, political scientists, and other social scientists with the methodological logic and techniques for doing spatial analysis in their chosen fields of inquiry. The book contains a wealth of examples as to why these techniques are worth doing, over and above conventional statistical techniques using SPSS or other statistical packages. GIS is a methodological and conceptual approach that allows for the linking together of spatial data, or data that is based on a physical space, with non-spatial data, which can be thought of as any data that contains no direct reference to physical locations.
