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Dive into the dynamic world of Geographic Information Systems (GIS) and data science with our comprehensive book in which innovation and insights converge. This book presents a pioneering exploration at the intersection of GIS and data science, providing a comprehensive view of their symbiotic relationship and transformative potential. It encapsulates advanced methodologies, real-world applications, and interdisciplinary approaches that redefine how we perceive and utilize spatial data. Offering a gateway to cutting-edge research and practical insights, this book serves as a crucial resource for scholars, practitioners, and enthusiasts alike. It addresses pressing challenges across diverse domains, from environmental studies to public health and predictive analytics, demonstrating the paramount significance of integrating GIS with data science methodologies. It is an essential compass guiding readers toward a deeper understanding and application of these dynamic fields in today's data-driven world.
Geographic Information Systems: Concepts, Methodologies, Tools, and Applications is a collection of knowledge on the latest advancements and research of geographic information systems. This book aims to be useful for academics and practitioners involved in geographical data.
Earth observation systems, by use of space science and technology advances, present a large-scale opportunity for applying remote sensing methods with geographical information system (GIS) developments. Integrating these two methods makes it possible to achieve high-accuracy satellite data processing. This book considers aspects of GIS technology applications with space science technology and innovation approaches. It examines the potential of Earth observation satellite systems as well as existing challenges and problems in the field. Chapters cover topics such as RGB-D sensors for autonomous pothole detection, machine learning in GIS, interferometric synthetic aperture radar (InSAR) modeling, and others.
Data science has recently gained much attention for a number of reasons, and among them is Big Data. Scientists (from almost all disciplines including physics, chemistry, biology, sociology, among others) and engineers (from all fields including civil, environmental, chemical, mechanical, among others) are faced with challenges posed by data volume, variety, and velocity, or Big Data. This book is designed to highlight the unique characteristics of geospatial data, demonstrate the need to different approaches and techniques for obtaining new knowledge from raw geospatial data, and present select state-of-the-art geospatial data science techniques and how they are applied to various geoscience problems.
This book provides the tools, the methods, and the theory to meet the challenges of contemporary data science applied to geographic problems and data. In the new world of pervasive, large, frequent, and rapid data, there are new opportunities to understand and analyze the role of geography in everyday life. Geographic Data Science with Python introduces a new way of thinking about analysis, by using geographical and computational reasoning, it shows the reader how to unlock new insights hidden within data. Key Features: ● Showcases the excellent data science environment in Python. ● Provides examples for readers to replicate, adapt, extend, and improve. ● Covers the crucial knowledge needed by geographic data scientists. It presents concepts in a far more geographic way than competing textbooks, covering spatial data, mapping, and spatial statistics whilst covering concepts, such as clusters and outliers, as geographic concepts. Intended for data scientists, GIScientists, and geographers, the material provided in this book is of interest due to the manner in which it presents geospatial data, methods, tools, and practices in this new field.
Geographic Information Systems for the Social Sciences: Investigating Space and Place is the first book to take a cutting-edge approach to integrating spatial concepts into the social sciences. In this text, authors Steven J. Steinberg and Sheila L. Steinberg simplify GIS (Geographic Information Systems) for practitioners and students in the social sciences through the use of examples and actual program exercises so that they can become comfortable incorporating this research tool into their repertoire and scope of interest. The authors provide learning objectives for each chapter, chapter summaries, links to relevant Web sites, as well as suggestions for student research projects.
Presents strategies for application development, interface design, and enabling Web-based access. Includes numerous case studies and examples from the private and public sectors. Provides information on integrating legacy MIS systems and planning for future developments in database design.
Features a five part structure covering: Foundations; Principles; Techniques; Analysis; and Management and Policy. This book includes chapters on Distributed GIS, Map Production, Geovisualization, Modeling, and Managing GIS. It offers coverage of such topics as: GIS and the New World Order; security, health and well being; and the greening of GIS.
Capable of acquiring large volumes of data through sensors deployed in air, land, and sea, and making this information readily available in a continuous time frame, the science of geographical information system (GIS) is rapidly evolving. This popular information system is emerging as a platform for scientific visualization, simulation, and computation of spatio-temporal data. New computing techniques are being researched and implemented to match the increasing capability of modern-day computing platforms and easy availability of spatio-temporal data. This has led to the need for the design, analysis, development, and optimization of new algorithms for extracting spatio-temporal patterns from a large volume of spatial data. Computing in Geographic Information Systems considers the computational aspects, and helps students understand the mathematical principles of GIS. It provides a deeper understanding of the algorithms and mathematical methods inherent in the process of designing and developing GIS functions. It examines the associated scientific computations along with the applications of computational geometry, differential geometry, and affine geometry in processing spatial data. It also covers the mathematical aspects of geodesy, cartography, map projection, spatial interpolation, spatial statistics, and coordinate transformation. The book discusses the principles of bathymetry and generation of electronic navigation charts. The book consists of 12 chapters. Chapters one through four delve into the modeling and preprocessing of spatial data and prepares the spatial data as input to the GIS system. Chapters five through eight describe the various techniques of computing the spatial data using different geometric and statically techniques. Chapters nine through eleven define the technique for image registration computation and measurements of spatial objects and phenomenon. Examines cartographic modeling and map projection Covers the mathematical aspects of different map projections Explores some of the spatial analysis techniques and applications of GIS Introduces the bathymetric principles and systems generated using bathymetric charts Explains concepts of differential geometry, affine geometry, and computational geometry Discusses popular analysis and measurement methods used in GIS This text outlines the key concepts encompassing GIS and spatio-temporal information, and is intended for students, researchers, and professionals engaged in analysis, visualization, and estimation of spatio-temporal events.