-PDF Download- Handbook Of Big Geospatial Data EBOOK

Handbook of Big Geospatial Data

Author: Martin Werner

Publisher: Springer Nature

Published: 2021-05-07

Total Pages: 641

ISBN-13: 3030554627

This handbook covers a wide range of topics related to the collection, processing, analysis, and use of geospatial data in their various forms. This handbook provides an overview of how spatial computing technologies for big data can be organized and implemented to solve real-world problems. Diverse subdomains ranging from indoor mapping and navigation over trajectory computing to earth observation from space, are also present in this handbook. It combines fundamental contributions focusing on spatio-textual analysis, uncertain databases, and spatial statistics with application examples such as road network detection or colocation detection using GPUs. In summary, this handbook gives an essential introduction and overview of the rich field of spatial information science and big geospatial data. It introduces three different perspectives, which together define the field of big geospatial data: a societal, governmental, and governance perspective. It discusses questions of how the acquisition, distribution and exploitation of big geospatial data must be organized both on the scale of companies and countries. A second perspective is a theory-oriented set of contributions on arbitrary spatial data with contributions introducing into the exciting field of spatial statistics or into uncertain databases. A third perspective is taking a very practical perspective to big geospatial data, ranging from chapters that describe how big geospatial data infrastructures can be implemented and how specific applications can be implemented on top of big geospatial data. This would include for example, research in historic map data, road network extraction, damage estimation from remote sensing imagery, or the analysis of spatio-textual collections and social media. This multi-disciplinary approach makes the book unique. This handbook can be used as a reference for undergraduate students, graduate students and researchers focused on big geospatial data. Professionals can use this book, as well as practitioners facing big collections of geospatial data.

Big Data Computing for Geospatial Applications

Author: Zhenlong Li

Publisher:

Published: 2020

Total Pages: 222

ISBN-13: 9783039432455

DOWNLOAD EBOOK →

The convergence of big data and geospatial computing has brought forth challenges and opportunities to Geographic Information Science with regard to geospatial data management, processing, analysis, modeling, and visualization. This book highlights recent advancements in integrating new computing approaches, spatial methods, and data management strategies to tackle geospatial big data challenges and meanwhile demonstrates opportunities for using big data for geospatial applications. Crucial to the advancements highlighted in this book is the integration of computational thinking and spatial thinking and the transformation of abstract ideas and models to concrete data structures and algorithms.

Big Data

Author: Hassan A. Karimi

Publisher: CRC Press

Published: 2014-02-18

Total Pages: 312

ISBN-13: 1466586559

DOWNLOAD EBOOK →

Big data has always been a major challenge in geoinformatics as geospatial data come in various types and formats, new geospatial data are acquired very fast, and geospatial databases are inherently very large. And while there have been advances in hardware and software for handling big data, they often fall short of handling geospatial big data ef

Big Data Computing for Geospatial Applications

Author: Zhenlong Li

Publisher: MDPI

Published: 2020-11-23

Total Pages: 222

ISBN-13: 3039432443

DOWNLOAD EBOOK →

Geospatial Data Analytics and Urban Applications

Author: Sandeep Narayan Kundu

Publisher:

Published: 2022

Total Pages: 0

ISBN-13: 9789811676505

DOWNLOAD EBOOK →

This book highlights advanced applications of geospatial data analytics to address real-world issues in urban society. With a connected world, we are generating spatial at unprecedented rates which can be harnessed for insightful analytics which define the way we analyze past events and define the future directions. This book is an anthology of applications of spatial data and analytics performed on them for gaining insights which can be used for problem solving in an urban setting. Each chapter is contributed by spatially aware data scientists in the making who present spatial perspectives drawn on spatial big data. The book shall benefit mature researchers and student alike to discourse a variety of urban applications which display the use of machine learning algorithms on spatial big data for real-world problem solving.

Geospatial Data Science Techniques and Applications

Author: Hassan A. Karimi

Publisher: CRC Press

Published: 2017-10-24

Total Pages: 375

ISBN-13: 1351855980

DOWNLOAD EBOOK →

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.

Handbook of Geospatial Artificial Intelligence

Author: Song Gao

Publisher: CRC Press

Published: 2023-12-29

Total Pages: 469

ISBN-13: 1003814921

DOWNLOAD EBOOK →

This comprehensive handbook covers Geospatial Artificial Intelligence (GeoAI), which is the integration of geospatial studies and AI machine (deep) learning and knowledge graph technologies. It explains key fundamental concepts, methods, models, and technologies of GeoAI, and discusses the recent advances, research tools, and applications that range from environmental observation and social sensing to natural disaster responses. As the first single volume on this fast-emerging domain, Handbook of Geospatial Artificial Intelligence is an excellent resource for educators, students, researchers, and practitioners utilizing GeoAI in fields such as information science, environment and natural resources, geosciences, and geography. Features Provides systematic introductions and discussions of GeoAI theory, methods, technologies, applications, and future perspectives Covers a wide range of GeoAI applications and case studies in practice Offers supplementary materials such as data, programming code, tools, and case studies Discusses the recent developments of GeoAI methods and tools Includes contributions written by top experts in cutting-edge GeoAI topics This book is intended for upper-level undergraduate and graduate students from different disciplines and those taking GIS courses in geography or computer sciences as well as software engineers, geospatial industry engineers, GIS professionals in non-governmental organizations, and federal/state agencies who use GIS and want to learn more about GeoAI advances and applications.

Springer Handbook of Geographic Information

Author: Wolfgang Kresse

Publisher: Springer Nature

Published: 2022-06-24

Total Pages: 985

ISBN-13: 3030531252

DOWNLOAD EBOOK →

This handbook provides an exhaustive, one-stop reference and a state-of-the-art description of geographic information and its use. This new, substantially updated edition presents a complete and rigorous overview of the fundamentals, methods and applications of the multidisciplinary field of geographic information systems. Designed to be a useful and readable desk reference book, but also prepared in various electronic formats, this title allows fast yet comprehensive review and easy retrieval of essential reliable key information. The Springer Handbook of Geographic Information is divided into three parts. Part A, Basics and Computer Science, provides an overview on the fundamentals, including descriptions of databases and encoding of geographic information. It also covers the underlying mathematical and statistics methods and modeling. A new chapter exemplifies the emerging use and analysis of big data in a geographic context. Part B offers rigorous descriptions of gathering, processing and coding of geographic information in a standardized way to allow interoperable use in a variety of systems; from traditional methods such as geodesy and surveying to state-of-the-art remote sensing and photogrammetry; from cartography to geospatial web services. Discussions on geosemantic interoperability and security of open distributed geospatial information systems complete the comprehensive coverage. The final part describes a wide array of applications in science, industry and society at large, such as agriculture, defense, transportation, energy and utilities, health and human services. The part is enhanced by new chapters on smart cities and building information modeling, as well as a complete overview of the currently available open-source geographic information systems. Using standardized international terminology, in accordance with ISO/TC 211 and INSPIRE, this handbook facilitates collaboration between different disciplines and is a must have for practitioners and new comers in industry and academia.

Applied Spatial Data Analysis with R

Author: Roger S. Bivand

Publisher: Springer Science & Business Media

Published: 2013-06-21

Total Pages: 414

ISBN-13: 1461476186

DOWNLOAD EBOOK →

Applied Spatial Data Analysis with R, second edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of interest to users who need to access and visualise spatial data. Data import and export for many file formats for spatial data are covered in detail, as is the interface between R and the open source GRASS GIS and the handling of spatio-temporal data. The second part showcases more specialised kinds of spatial data analysis, including spatial point pattern analysis, interpolation and geostatistics, areal data analysis and disease mapping. The coverage of methods of spatial data analysis ranges from standard techniques to new developments, and the examples used are largely taken from the spatial statistics literature. All the examples can be run using R contributed packages available from the CRAN website, with code and additional data sets from the book's own website. Compared to the first edition, the second edition covers the more systematic approach towards handling spatial data in R, as well as a number of important and widely used CRAN packages that have appeared since the first edition. This book will be of interest to researchers who intend to use R to handle, visualise, and analyse spatial data. It will also be of interest to spatial data analysts who do not use R, but who are interested in practical aspects of implementing software for spatial data analysis. It is a suitable companion book for introductory spatial statistics courses and for applied methods courses in a wide range of subjects using spatial data, including human and physical geography, geographical information science and geoinformatics, the environmental sciences, ecology, public health and disease control, economics, public administration and political science. The book has a website where complete code examples, data sets, and other support material may be found: http://www.asdar-book.org. The authors have taken part in writing and maintaining software for spatial data handling and analysis with R in concert since 2003.

Geospatial Analysis

Author: Michael John De Smith

Publisher: Troubador Publishing Ltd

Published: 2007

Total Pages: 417

ISBN-13: 1905886608

DOWNLOAD EBOOK →

Addresses a range of analytical techniques that are provided within modern Geographic Information Systems and related geospatial software products. This guide covers: the principal concepts of geospatial analysis; core components of geospatial analysis; and, surface analysis, including surface form analysis, gridding and interpolation methods.