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Distributive Parallel Processing Of Image Geographic Information System Data For Spatial Analysis And Modeling Of Earth Resources Information
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Book Synopsis Distributive Parallel Processing of Image/geographic Information System Data for Spatial Analysis and Modeling of Earth Resources Information by : Alan J. Yost
Download or read book Distributive Parallel Processing of Image/geographic Information System Data for Spatial Analysis and Modeling of Earth Resources Information written by Alan J. Yost and published by . This book was released on 1986 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Big Data written by Hassan A. Karimi and published by CRC Press. This book was released on 2024-08-01 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past decade, since the publication of the first edition, there have been new advances in solving complex geoinformatics problems. Advancements in computing power, computing platforms, mathematical models, statistical models, geospatial algorithms, and the availability of data in various domains, among other things, have aided in the automation of complex real-world tasks and decision-making that inherently rely on geospatial data. Of the many fields benefiting from these latest advancements, machine learning, particularly deep learning, virtual reality, and game engine, have increasingly gained the interest of many researchers and practitioners. This revised new edition provides up-to-date knowledge on the latest developments related to these three fields for solving geoinformatics problems. FEATURES Contains a comprehensive collection of advanced big data approaches, techniques, and technologies for geoinformatics problems Provides seven new chapters on deep learning models, algorithms, and structures, including a new chapter on how spatial metaverse is used to build immersive realistic virtual experiences Presents information on how deep learning is used for solving real-world geoinformatics problems This book is intended for researchers, academics, professionals, and students in such fields as computing and information, civil and environmental engineering, environmental sciences, geosciences, geology, geography, and urban studies.
Book Synopsis Heterogeneous Spatial Data by : Giuseppe Patanè
Download or read book Heterogeneous Spatial Data written by Giuseppe Patanè and published by Morgan & Claypool Publishers. This book was released on 2016-04-29 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: New data acquisition techniques are emerging and are providing fast and efficient means for multidimensional spatial data collection. Airborne LIDAR surveys, SAR satellites, stereo-photogrammetry and mobile mapping systems are increasingly used for the digital reconstruction of the environment. All these systems provide extremely high volumes of raw data, often enriched with other sensor data (e.g., beam intensity). Improving methods to process and visually analyze this massive amount of geospatial and user-generated data is crucial to increase the efficiency of organizations and to better manage societal challenges. Within this context, this book proposes an up-to-date view of computational methods and tools for spatio-temporal data fusion, multivariate surface generation, and feature extraction, along with their main applications for surface approximation and rainfall analysis. The book is intended to attract interest from different fields, such as computer vision, computer graphics, geomatics, and remote sensing, working on the common goal of processing 3D data. To this end, it presents and compares methods that process and analyze the massive amount of geospatial data in order to support better management of societal challenges through more timely and better decision making, independent of a specific data modeling paradigm (e.g., 2D vector data, regular grids or 3D point clouds). We also show how current research is developing from the traditional layered approach, adopted by most GIS softwares, to intelligent methods for integrating existing data sets that might contain important information on a geographical area and environmental phenomenon. These services combine traditional map-oriented visualization with fully 3D visual decision support methods and exploit semantics-oriented information (e.g., a-priori knowledge, annotations, segmentations) when processing, merging, and integrating big pre-existing data sets.
Book Synopsis Pattern-Based Compression of Multi-Band Image Data for Landscape Analysis by : Wayne L. Myers
Download or read book Pattern-Based Compression of Multi-Band Image Data for Landscape Analysis written by Wayne L. Myers and published by Springer Science & Business Media. This book was released on 2006-12-18 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes an integrated approach to using remotely sensed data in conjunction with geographic information systems for landscape analysis. Remotely sensed data are compressed into an analytical image-map that is compatible with the most popular geographic information systems as well as freeware viewers. The approach is most effective for landscapes that exhibit a pronounced mosaic pattern of land cover.
Book Synopsis CyberGIS for Geospatial Discovery and Innovation by : Shaowen Wang
Download or read book CyberGIS for Geospatial Discovery and Innovation written by Shaowen Wang and published by Springer. This book was released on 2018-06-26 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book elucidates how cyberGIS (that is, new-generation geographic information science and systems (GIS) based on advanced computing and cyberinfrastructure) transforms computation- and data-intensive geospatial discovery and innovation. It comprehensively addresses opportunities and challenges, roadmaps for research and development, and major progress, trends, and impacts of cyberGIS in the era of big data. The book serves as an authoritative source of information to fill the void of introducing this exciting and growing field. By providing a set of representative applications and science drivers of cyberGIS, this book demonstrates how cyberGIS has been advanced to enable cutting-edge scientific research and innovative geospatial application development. Such cyberGIS advances are contextualized as diverse but interrelated science and technology frontiers. The book also emphasizes several important social dimensions of cyberGIS such as for empowering deliberative civic engagement and enabling collaborative problem solving through structured participation. In sum, this book will be a great resource to students, academics, and geospatial professionals for leaning cutting-edge cyberGIS, geospatial data science, high-performance computing, and related applications and sciences.
Book Synopsis Advances in Machine Learning and Image Analysis for GeoAI by : Saurabh Prasad
Download or read book Advances in Machine Learning and Image Analysis for GeoAI written by Saurabh Prasad and published by Elsevier. This book was released on 2024-06-01 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Machine Learning and Image Analysis for GeoAI provides state-of-the-art machine learning and signal processing techniques for a comprehensive collection of geospatial sensors and sensing platforms. The book covers supervised, semi-supervised and unsupervised geospatial image analysis, sensor fusion across modalities, image super-resolution, transfer learning across sensors and time-points, and spectral unmixing among other topics. The chapters in these thematic areas cover a variety of algorithmic frameworks such as variants of convolutional neural networks, graph convolutional networks, multi-stream networks, Bayesian networks, generative adversarial networks, transformers and more.Advances in Machine Learning and Image Analysis for GeoAI provides graduate students, researchers and practitioners in the area of signal processing and geospatial image analysis with the latest techniques to implement deep learning strategies in their research. Covers the latest machine learning and signal processing techniques that can effectively leverage geospatial imagery at scale Presents a variety of algorithmic frameworks, including variants of convolutional neural networks, multi-stream networks, Bayesian networks, and more Includes open-source code-base for algorithms described in each chapter
Book Synopsis Automating the Analysis of Spatial Grids by : Valliappa Lakshmanan
Download or read book Automating the Analysis of Spatial Grids written by Valliappa Lakshmanan and published by Springer Science & Business Media. This book was released on 2012-06-14 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ability to create automated algorithms to process gridded spatial data is increasingly important as remotely sensed datasets increase in volume and frequency. Whether in business, social science, ecology, meteorology or urban planning, the ability to create automated applications to analyze and detect patterns in geospatial data is increasingly important. This book provides students with a foundation in topics of digital image processing and data mining as applied to geospatial datasets. The aim is for readers to be able to devise and implement automated techniques to extract information from spatial grids such as radar, satellite or high-resolution survey imagery.
Book Synopsis Advances in Scalable and Intelligent Geospatial Analytics by : Surya S Durbha
Download or read book Advances in Scalable and Intelligent Geospatial Analytics written by Surya S Durbha and published by CRC Press. This book was released on 2023-05-12 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geospatial data acquisition and analysis techniques have experienced tremendous growth in the last few years, providing an opportunity to solve previously unsolved environmental- and natural resource-related problems. However, a variety of challenges are encountered in processing the highly voluminous geospatial data in a scalable and efficient manner. Technological advancements in high-performance computing, computer vision, and big data analytics are enabling the processing of big geospatial data in an efficient and timely manner. Many geospatial communities have already adopted these techniques in multidisciplinary geospatial applications around the world. This book is a single source that offers a comprehensive overview of the state of the art and future developments in this domain. FEATURES Demonstrates the recent advances in geospatial analytics tools, technologies, and algorithms Provides insight and direction to the geospatial community regarding the future trends in scalable and intelligent geospatial analytics Exhibits recent geospatial applications and demonstrates innovative ways to use big geospatial data to address various domain-specific, real-world problems Recognizes the analytical and computational challenges posed and opportunities provided by the increased volume, velocity, and veracity of geospatial data This book is beneficial to graduate and postgraduate students, academicians, research scholars, working professionals, industry experts, and government research agencies working in the geospatial domain, where GIS and remote sensing are used for a variety of purposes. Readers will gain insights into the emerging trends on scalable geospatial data analytics.
Download or read book NASA Technical Memorandum written by and published by . This book was released on 1963 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Building Feature Extraction with Machine Learning by : Bharath.H. Aithal
Download or read book Building Feature Extraction with Machine Learning written by Bharath.H. Aithal and published by CRC Press. This book was released on 2022-12-29 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big geospatial datasets created by large infrastructure projects require massive computing resources to process. Feature extraction is a process used to reduce the initial set of raw data for manageable image processing, and machine learning (ML) is the science that supports it. This book focuses on feature extraction methods for optical geospatial data using ML. It is a practical guide for professionals and graduate students who are starting a career in information extraction. It explains spatial feature extraction in an easy-to-understand way and includes real case studies on how to collect height values for spatial features, how to develop 3D models in a map context, and others. Features Provides the basics of feature extraction methods and applications along with the fundamentals of machine learning Discusses in detail the application of machine learning techniques in geospatial building feature extraction Explains the methods for estimating object height from optical satellite remote sensing images using Python Includes case studies that demonstrate the use of machine learning models for building footprint extraction and photogrammetric methods for height assessment Highlights the potential of machine learning and geospatial technology for future project developments This book will be of interest to professionals, researchers, and graduate students in geoscience and earth observation, machine learning and data science, civil engineers, and urban planners.
Book Synopsis Information Fusion and Intelligent Geographic Information Systems by : Vasily Popovich
Download or read book Information Fusion and Intelligent Geographic Information Systems written by Vasily Popovich and published by Springer Nature. This book was released on 2019-11-19 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers the proceedings of the 9th International Symposium “Information Fusion and Intelligent Geographic Information Systems 2019” (IF&IGIS'2019), which was held in St. Petersburg, Russia from May 22 to 24, 2019. The goal of the symposium was to provide a forum for exchange among leading international scholars in the fields of spatial data, information integration and Intelligent Geographic Information Systems (IGIS). The symposium was an opportunity to discuss sound and effective lines of modeling in the fusion of spatial data and information within the broader scope of intelligent GIS. The topics of the 2019 Symposium essentially fall into three broad categories of developments aimed at leveraging the power of spatial information, namely: artificial intelligence; algorithmic and computations processes; and data-informed simulation models. All papers collected here present compelling, cutting-edge research on cloud computing, deep learning, visual analytics, and large-scale optimization. They discuss information fusion and intelligent GIS research in the context of surface and sub-surface maritime activities, port asset management, land-based trip and travel planning, smart city and e-government, emergency management, and environmental monitoring. Given its scope, the book will be of interest to students, researchers and professionals working in GIS, remote sensing, and cloud computing.
Book Synopsis A Taxonomy of Parallel Vector Spatial Analysis Algorithms by : Jason Laura
Download or read book A Taxonomy of Parallel Vector Spatial Analysis Algorithms written by Jason Laura and published by . This book was released on 2015 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nearly 25 years ago, parallel computing techniques were first applied to vector spatial analysis methods. This initial research was driven by the desire to reduce computing times in order to support scaling to larger problem sets. Since this initial work, rapid technological advancement has driven the availability of High Performance Computing (HPC) resources, in the form of multi-core desktop computers, distributed geographic information processing systems, e.g. computational grids, and single site HPC clusters. In step with increases in computational resources, significant advancement in the capabilities to capture and store large quantities of spatially enabled data have been realized. A key component to utilizing vast data quantities in HPC environments, scalable algorithms, have failed to keep pace. The National Science Foundation has identified the lack of scalable algorithms in codified frameworks as an essential research product. Fulfillment of this goal is challenging given the lack of a codified theoretical framework mapping atomic numeric operations from the spatial analysis stack to parallel programming paradigms, the diversity in vernacular utilized by research groups, the propensity for implementations to tightly couple to under- lying hardware, and the general difficulty in realizing scalable parallel algorithms. This dissertation develops a taxonomy of parallel vector spatial analysis algorithms with classification being defined by root mathematical operation and communication pattern, a computational dwarf. Six computational dwarfs are identified, three being drawn directly from an existing parallel computing taxonomy and three being created to capture characteristics unique to spatial analysis algorithms. The taxonomy provides a high-level classification decoupled from low-level implementation details such as hardware, communication protocols, implementation language, decomposition method, or file input and output. By taking a high-level approach implementation specifics are broadly proposed, breadth of coverage is achieved, and extensibility is ensured. The taxonomy is both informed and informed by five case studies im- plemented across multiple, divergent hardware environments. A major contribution of this dissertation is a theoretical framework to support the future development of concrete parallel vector spatial analysis frameworks through the identification of computational dwarfs and, by extension, successful implementation strategies.
Author :Society of Photo-optical Instrumentation Engineers Publisher :SPIE-International Society for Optical Engineering ISBN 13 : Total Pages :114 pages Book Rating :4.3/5 (91 download)
Book Synopsis Geo-spatial Image and Data Exploitation II by : Society of Photo-optical Instrumentation Engineers
Download or read book Geo-spatial Image and Data Exploitation II written by Society of Photo-optical Instrumentation Engineers and published by SPIE-International Society for Optical Engineering. This book was released on 2001 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis High Performance Geographic Information System by : Wei Xiong
Download or read book High Performance Geographic Information System written by Wei Xiong and published by Springer. This book was released on 2024-11-07 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of earth observation and computing technology has promoted the wide application of spatio-temporal big data and artificial intelligence. The enrichment of data and the improvement of computational performance make it possible to perform spatio-temporal analysis and computation on a larger scale. Therefore, it is necessary to study the optimization methods and application methods of high-performance geocomputing, starting from GIS architecture, in order to form a high-performance GIS that can serve the society and economy and support various applications. This book focuses on the architecture, technology, platform, and application of high-performance GIS, analyzes the key technologies of spatio-temporal big data organization and access, parallelized spatial analysis and processing, large-scale map rendering, and parallel visualization under the high-performance computing architecture, explains how to build high-performance geographic information applications, and looks forward to the trend of the new generation of GIS.
Book Synopsis Parallel and In-memory Big Spatial Data Processing Systems and Benchmarking by : Md. Mahbub Alam
Download or read book Parallel and In-memory Big Spatial Data Processing Systems and Benchmarking written by Md. Mahbub Alam and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the accelerated growth in spatial data volume, being generated from a wide variety of sources, the need for efficient storage, retrieval, processing and analyzing of spatial data is ever more important. Hence, the spatial data processing system has become an important field of research. Though the traditional relational database systems provide spatial functionality (such as, PostgreSQL with PostGIS), due to the lack of parallelism and I/O bottleneck, these systems are not efficient to run compute-intensive spatial queries on large datasets. In recent times a number of big spatial data systems have been proposed by researchers around the world. These systems can be roughly categorized into disk-based systems over Apache Hadoop and in memory systems based on Apache Spark. The available features supported by these systems vary widely. However, there has not been any comprehensive evaluation study of these systems in terms of performance, scalability, and functionality. In order to address this need, this thesis proposes a benchmark to evaluate big spatial data systems. It intends to investigate the present status of the big spatial data systems by conducting a comprehensive feature analysis and performance evaluation of a few representative systems. The Hadoop and Spark based big spatial data systems are distributed, scalable, and able to exploit the parallelism of today’s multi-core/many-core architecture. However, most of them are immature, unstable, difficult to extend and missing efficient query language like SQL. In this work, a disk based system Parallax is introduced as a parallel big spatial database system. It integrates the powerful spatial features of PostgreSQL/PostGIS and distributed persistence storage of Alluxio. The host-specific data partitioning and parallel query on local data in each node ensure the maximum utilization of main memory, disk storage, and CPU. This thesis also introduces an in-memory system SpatialIgnite, as extended spatial support for Apache Ignite. SpatialIgnite incorporates a spatial library which contains all the OGC compliant join predicates and spatial analysis functions. Along with query parallelism and collocated query processing of Ignite, the integrated spatial data partitioning techniques improve the performance of SpatialIgnite. The evaluation shows that Spatial Ignite performs better than Hadoop and Spark based systems.
Book Synopsis Manual of Digital Earth by : Huadong Guo
Download or read book Manual of Digital Earth written by Huadong Guo and published by Springer Nature. This book was released on 2019-11-18 with total page 846 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book offers a summary of the development of Digital Earth over the past twenty years. By reviewing the initial vision of Digital Earth, the evolution of that vision, the relevant key technologies, and the role of Digital Earth in helping people respond to global challenges, this publication reveals how and why Digital Earth is becoming vital for acquiring, processing, analysing and mining the rapidly growing volume of global data sets about the Earth. The main aspects of Digital Earth covered here include: Digital Earth platforms, remote sensing and navigation satellites, processing and visualizing geospatial information, geospatial information infrastructures, big data and cloud computing, transformation and zooming, artificial intelligence, Internet of Things, and social media. Moreover, the book covers in detail the multi-layered/multi-faceted roles of Digital Earth in response to sustainable development goals, climate changes, and mitigating disasters, the applications of Digital Earth (such as digital city and digital heritage), the citizen science in support of Digital Earth, the economic value of Digital Earth, and so on. This book also reviews the regional and national development of Digital Earth around the world, and discusses the role and effect of education and ethics. Lastly, it concludes with a summary of the challenges and forecasts the future trends of Digital Earth. By sharing case studies and a broad range of general and scientific insights into the science and technology of Digital Earth, this book offers an essential introduction for an ever-growing international audience.
Book Synopsis Geospatial Science for Smart Land Management by : Walter Timo de Vries
Download or read book Geospatial Science for Smart Land Management written by Walter Timo de Vries and published by CRC Press. This book was released on 2023-12-22 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: Responsible land distribution in Asia, with ever-increasing limitations in space, requires the use of smart technologies, sophisticated models, intelligent algorithms, and big data repositories. This book presents new land management perspectives and fit-for-purpose, flexible, dynamic, and effective solutions for land management and land administration problems. Written by global experts from different Asian countries, including China, India, Indonesia, Iran, Japan, South Korea, Thailand, Vietnam, etc., all these cases demonstrate how and why the uptake of geospatial technologies is booming and how to handle land scarcity and competing spatial interests in both urban and rural areas in Asia. FEATURES Summarizes trends of geospatial technologies in Asia Describes and applies leading-edge geospatial models Explains fit-for-purpose digital land administration Provides case studies and examples that include the use of smart land management tools Helps readers advance their understanding of geospatial and land management science Truly an interdisciplinary book, this text is a practical guide for an array of readers, such as practitioners in public and private companies involved in both geospatial and land management applications, as well as graduate students, researchers, academics, and professionals working in land administration, land management, spatial planning, real estate studies, geosciences, geoinformatics, and geodesy.
