Spatial Cloud Computing

An exploration of the benefits of cloud computing in geoscience research and applications as well as future research directions, Spatial Cloud Computing: A Practical Approach discusses the essential elements of cloud computing and their ...


Author: Chaowei Yang

Publisher: CRC Press

ISBN: 9781466593176

Category: Computers

Page: 357

View: 289

An exploration of the benefits of cloud computing in geoscience research and applications as well as future research directions, Spatial Cloud Computing: A Practical Approach discusses the essential elements of cloud computing and their advantages for geoscience. Using practical examples, it details the geoscience requirements of cloud computing, covers general procedures and considerations when migrating geoscience applications onto cloud services, and demonstrates how to deploy different applications. The book discusses how to choose cloud services based on the general cloud computing measurement criteria and cloud computing cost models. The authors examine the readiness of cloud computing to support geoscience applications using open source cloud software solutions and commercial cloud services. They then review future research and developments in data, computation, concurrency, and spatiotemporal intensities of geosciences and how cloud service can be leveraged to meet the challenges. They also introduce research directions from the aspects of technology, vision, and social dimensions. Spatial Cloud Computing: A Practical Approach a common workflow for deploying geoscience applications and provides references to the concepts, technical details, and operational guidelines of cloud computing. These features and more give developers, geoscientists, and IT professionals the information required to make decisions about how to select and deploy cloud services.

Cloud Computing in Ocean and Atmospheric Sciences

By providing general information on the use of the cloud for oceanographic and atmospheric computing, as well as examples of specific applications, this book encourages and educates potential users of the cloud.


Author: Tiffany C Vance

Publisher: Elsevier

ISBN: 9780128031933

Category: Science

Page: 454

View: 899

Cloud Computing in Ocean and Atmospheric Sciences provides the latest information on this relatively new platform for scientific computing, which has great possibilities and challenges, including pricing and deployments costs and applications that are often presented as primarily business oriented. In addition, scientific users may be very familiar with these types of models and applications, but relatively unfamiliar with the intricacies of the hardware platforms they use. The book provides a range of practical examples of cloud applications that are written to be accessible to practitioners, researchers, and students in affiliated fields. By providing general information on the use of the cloud for oceanographic and atmospheric computing, as well as examples of specific applications, this book encourages and educates potential users of the cloud. The chapters provide an introduction to the practical aspects of deploying in the cloud, also providing examples of workflows and techniques that can be reused in new projects. Provides real examples that help new users quickly understand the cloud and provide guidance for new projects Presents proof of the usability of the techniques and a clear path to adoption of the techniques by other researchers Includes real research and development examples that are ideal for cloud computing adopters in ocean and atmospheric domains

Cloud Computing

Retrieving and Indexing Spatial Data in the Cloud Computing Environment
Yonggang Wang1,∗, Sheng Wang2, and Daliang Zhou2 1 Institute of Remote
Sensing Applications, Chinese Academy of Sciences, 100101 Beijing, China
Phone: ...


Author: Martin Gilje Jaatun

Publisher: Springer Science & Business Media

ISBN: 9783642106644

Category: Computers

Page: 707

View: 855

This volume contains the proceedings of CloudCom 2009, the First Inter- tional Conference on Cloud Computing. The conference was held in Beijing, China, during December 1–4, 2009, and was the ?rst in a series initiated by the Cloud Computing Association ( The Cloud Computing Association was founded in 2009 by Chunming Rong, Martin Gilje Jaatun, and Frode Eika Sandnes. This ?rst conference was organized by the Beijing Ji- tong University, Chinese Institute of Electronics, and Wuhan University, and co-organized by Huazhong University of Science and Technology, South China Normal University, and Sun Yat-sen University. Ever since the inception of the Internet, a “Cloud” has been used as a metaphor for a network-accessible infrastructure (e.g., data storage, computing hardware, or entire networks) which is hidden from users. To some, the concept of cloud computing may seem like a throwback to the days of big mainframe computers, but we believe that cloud computing makes data truly mobile, - lowing a user to access services anywhere, anytime, with any Internet browser. In cloud computing, IT-related capabilities are provided as services, accessible without requiring control of, or even knowledge of, the underlying technology. Cloud computing provides dynamic scalability of services and computing power, and although many mature technologies are used as components in cloud c- puting, there are still many unresolved and open problems.

Spatial Computing

Computing power , computer storage , remote - sensing tools -- all are continuing
to improve . Our computers are becoming smaller and more powerful , and much
of the storage and processing of computer imagery is done in cloud computing ...


Author: Shashi Shekhar

Publisher: MIT Press

ISBN: 9780262538046

Category: Computers

Page: 256

View: 429

An accessible guide to the ideas and technologies underlying such applications as GPS, Google Maps, Pokémon Go, ride-sharing, driverless cars, and drone surveillance. Billions of people around the globe use various applications of spatial computing daily—by using a ride-sharing app, GPS, the e911 system, social media check-ins, even Pokémon Go. Scientists and researchers use spatial computing to track diseases, map the bottom of the oceans, chart the behavior of endangered species, and create election maps in real time. Drones and driverless cars use a variety of spatial computing technologies. Spatial computing works by understanding the physical world, knowing and communicating our relation to places in that world, and navigating through those places. It has changed our lives and infrastructures profoundly, marking a significant shift in how we make our way in the world. This volume in the MIT Essential Knowledge series explains the technologies and ideas behind spatial computing. The book offers accessible descriptions of GPS and location-based services, including the use of Wi-Fi, Bluetooth, and RFID for position determination out of satellite range; remote sensing, which uses satellite and aerial platforms to monitor such varied phenomena as global food production, the effects of climate change, and subsurface natural resources on other planets; geographic information systems (GIS), which store, analyze, and visualize spatial data; spatial databases, which store multiple forms of spatial data; and spatial statistics and spatial data science, used to analyze location-related data.

Urban Computing

The third part of this book, composed of chapters 4, 5, and 6, introduces data
management for spatial and spatiotemporal data. It starts with basic indexing and
retrieval algorithms and then discusses the technology that uses cloud-
computing ...


Author: Yu Zheng

Publisher: MIT Press

ISBN: 9780262039086

Category: Computers

Page: 632

View: 142

An authoritative treatment of urban computing, offering an overview of the field, fundamental techniques, advanced models, and novel applications. Urban computing brings powerful computational techniques to bear on such urban challenges as pollution, energy consumption, and traffic congestion. Using today's large-scale computing infrastructure and data gathered from sensing technologies, urban computing combines computer science with urban planning, transportation, environmental science, sociology, and other areas of urban studies, tackling specific problems with concrete methodologies in a data-centric computing framework. This authoritative treatment of urban computing offers an overview of the field, fundamental techniques, advanced models, and novel applications. Each chapter acts as a tutorial that introduces readers to an important aspect of urban computing, with references to relevant research. The book outlines key concepts, sources of data, and typical applications; describes four paradigms of urban sensing in sensor-centric and human-centric categories; introduces data management for spatial and spatio-temporal data, from basic indexing and retrieval algorithms to cloud computing platforms; and covers beginning and advanced topics in mining knowledge from urban big data, beginning with fundamental data mining algorithms and progressing to advanced machine learning techniques. Urban Computing provides students, researchers, and application developers with an essential handbook to an evolving interdisciplinary field.

Decentralized Spatial Computing

information is more likely to be more relevant in answering spatial queries. For
example, when ... Similarly, related work on grid computing, cloud computing,
and distributed GIS typically assume no spatial constraints on the movement ...


Author: Matt Duckham

Publisher: Springer Science & Business Media

ISBN: 9783642308536

Category: Science

Page: 322

View: 642

Computing increasingly happens somewhere, with that geographic location important to the computational process itself. Many new and evolving spatial technologies, such as geosensor networks and smartphones, embody this trend. Conventional approaches to spatial computing are centralized, and do not account for the inherently decentralized nature of "computing somewhere": the limited, local knowledge of individual system components, and the interaction between those components at different locations. On the other hand, despite being an established topic in distributed systems, decentralized computing is not concerned with geographical constraints to the generation and movement of information. In this context, of (centralized) spatial computing and decentralized (non-spatial) computing, the key question becomes: "What makes decentralized spatial computing special?" In Part I of the book the author covers the foundational concepts, structures, and design techniques for decentralized computing with spatial and spatiotemporal information. In Part II he applies those concepts and techniques to the development of algorithms for decentralized spatial computing, stepping through a suite of increasingly sophisticated algorithms: from algorithms with minimal spatial information about their neighborhoods; to algorithms with access to more detailed spatial information, such as direction, distance, or coordinate location; to truly spatiotemporal algorithms that monitor environments that are dynamic, even using networks that are mobile or volatile. Finally, in Part III the author shows how decentralized spatial and spatiotemporal algorithms designed using the techniques explored in Part II can be simulated and tested. In particular, he investigates empirically the important properties of a decentralized spatial algorithm: its computational efficiency and its robustness to unavoidable uncertainty. Part III concludes with a survey of the opportunities for connecting decentralized spatial computing to ongoing research and emerging hot topics in related fields, such as biologically inspired computing, geovisualization, and stream computing. The book is written for students and researchers of computer science and geographic information science. Throughout the book the author's style is characterized by a focus on the broader message, explaining the process of decentralized spatial algorithm design rather than the technical details. Each chapter ends with review questions designed to test the reader's understanding of the material and to point to further work or research. The book includes short appendices on discrete mathematics and SQL. Simulation models written in NetLogo and associated source code for all the algorithms presented in the book can be found on the author's accompanying website.

Ubiquitous Information Technologies and Applications

CICC to Support Location Based Service in Cloud Computing Doohee Song and
Kwangjin Park* Department of ... Thus we are using a cloud computing
environment to store big data to overcome limited data spatial storage in more
efficient ...


Author: Young-Sik Jeong

Publisher: Springer Science & Business Media

ISBN: 9783642416712

Category: Technology & Engineering

Page: 854

View: 325

The theme of CUTE is focused on the various aspects of ubiquitous computing for advances in ubiquitous computing and provides an opportunity for academic and industry professionals to discuss the latest issues and progress in the area of ubiquitous computing. Therefore this book will be include the various theories and practical applications in ubiquitous computing

Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases

CHAPTER 9 Cloud Computing–Enabled Cluster Detection Using a Flexibly
Shaped Scan Statistic for Real-Time Syndromic Surveillance Paul Belanger and
Kieran Moore KFL&A Public Health, Kingston, ON, Canada Queen's University, ...


Author: Dongmei Chen

Publisher: John Wiley & Sons

ISBN: 9781118629932

Category: Medical

Page: 496

View: 427

Cloud Computing and Services Science

To achieve near real-time latency, it is therefore crucial to take into account the
network characteristics when deploying the distributed spatial index on the
cloud's nodes. For this, we introduce the concept of network-aware spatial


Author: Ivan Ivanov

Publisher: Springer Science & Business Media

ISBN: 9781461423263

Category: Business & Economics

Page: 392

View: 112

The Cloud Computing and Services Science book comprises a collection of the best papers presented at the International Conference on Cloud Computing and Services Science (CLOSER), which was held in The Netherlands in May 2011. In netting papers from the conference researchers and experts from all over the world explore a wide-ranging variety of the emerging Cloud Computing platforms, models, applications and enabling technologies. Further, in several papers the authors exemplify essential links to Services Science as service development abstraction, service innovation, and service engineering, acknowledging the service-orientation in most current IT-driven structures in the Cloud. The Cloud Computing and Services Science book is organized around important dimensions of technology trends in the domain of cloud computing in relation to a broad scientific understanding of modern services emerging from services science. The papers of this book are inspired by scholarly and practical work on the latest advances related to cloud infrastructure, operations, security, services, and management through the global network. This book includes several features that will be helpful, interesting, and inspirational to students, researchers as well as practitioners. Professionals and decision makers working in this field will also benefit from this book


However, the entry of non-traditional approaches into the geospatial market, such
as the Cloud Computing expertise of WeoGeo and spatial database appliance
options from Netezza, is introducing a new level of innovation. As these types of ...




ISBN: STANFORD:36105132736518

Category: Geographic information systems


View: 661

Contemporary Advancements in Information Technology Development in Dynamic Environments

Spatial. Decision. Making. in. Cloud. Computing. Michele Argiolas Università
degli Studi di Cagliari, Italy Maurizio Atzori Università degli Studi di Cagliari, Italy
Nicoletta Dessì Università degli Studi di Cagliari, Italy Barbara Pes Università
degli ...


Author: Khosrow-Pour, Mehdi

Publisher: IGI Global

ISBN: 9781466662537

Category: Computers

Page: 410

View: 669

The advancement of information technology is becoming more prevalent in all aspects of the world today, including online environments. Understanding technology’s effect on niche markets and all fields of research is crucial for practitioners in this area. Contemporary Advancements in Information Technology Development in Dynamic Environments presents an in-depth discussion into the information technology revolution present in fields such as government, gaming, social networking, and cloud computing. This book’s investigation into the research and application of information technology in several specific areas make this a useful resource for practitioners, professionals, undergraduate/graduate students, and academics.

Spatial Data Mining

· This book is an updated version of a well-received book previously published in Chinese by Science Press of China (the first edition in 2006 and the second in 2013).


Author: Deren Li

Publisher: Springer

ISBN: 9783662485385

Category: Computers

Page: 308

View: 182

· This book is an updated version of a well-received book previously published in Chinese by Science Press of China (the first edition in 2006 and the second in 2013). It offers a systematic and practical overview of spatial data mining, which combines computer science and geo-spatial information science, allowing each field to profit from the knowledge and techniques of the other. To address the spatiotemporal specialties of spatial data, the authors introduce the key concepts and algorithms of the data field, cloud model, mining view, and Deren Li methods. The data field method captures the interactions between spatial objects by diffusing the data contribution from a universe of samples to a universe of population, thereby bridging the gap between the data model and the recognition model. The cloud model is a qualitative method that utilizes quantitative numerical characters to bridge the gap between pure data and linguistic concepts. The mining view method discriminates the different requirements by using scale, hierarchy, and granularity in order to uncover the anisotropy of spatial data mining. The Deren Li method performs data preprocessing to prepare it for further knowledge discovery by selecting a weight for iteration in order to clean the observed spatial data as much as possible. In addition to the essential algorithms and techniques, the book provides application examples of spatial data mining in geographic information science and remote sensing. The practical projects include spatiotemporal video data mining for protecting public security, serial image mining on nighttime lights for assessing the severity of the Syrian Crisis, and the applications in the government project ‘the Belt and Road Initiatives’.

Middle Atmosphere Temporal and Spatial Structures

The analysis also allows us to define a rough cloud top height ( CTH ) by
computing the first tangent height where the cloud index falls below the specified
threshold of CI < 2 ( Figure 2 and Figure 3 ) during a downward scan . The CTHs
were ...


Author: COSPAR. Scientific Commission C. C2.3-A1.4 Symposium


ISBN: STANFORD:36105110973323

Category: Atmospheric physics

Page: 165

View: 734

Spatial and Temporal Scales of Precipitating Tropical Cloud Systems

Quantifying the spectrum of cloud systems that results from the hierarchy of
convective structures described above is an ... present day limitations in
computing power prevent long - range , global climate predictions from being
performed at ...


Author: Eric Martin Wilcox


ISBN: UCSD:31822009313974


Page: 262

View: 457

Spatial Data Science for Addressing Environmental Challenges in the 21st Century

The year 2005 sparked a geographic revolution through the release of Google Maps, arguably the first geographic tool to capture public interest and act as a catalyst for neogeography (i.e. the community of non-geographers who built tools ...


Author: Jenny Lizbeth Palomino


ISBN: OCLC:1066229777


Page: 148

View: 170

The year 2005 sparked a geographic revolution through the release of Google Maps, arguably the first geographic tool to capture public interest and act as a catalyst for neogeography (i.e. the community of non-geographers who built tools and technologies without formal training in geography). A few years later, in 2008, the scientific community witnessed another major turning point through open access to the Landsat satellite archive, which had been collecting earth observation data since 1972. These moments were critical starting points of an explosion in geographic tools and data that today remains on a rapid upward trajectory. In more recent years, new additions in data and tools have come from the Free and Open Source Software (FOSS), open and volunteered data movements, new data collection methods (such as unmanned aerial vehicles, micro-satellites, real-time sensors), and advances in computational technologies such as cloud and high performance computing (HPC). However, within the broader Data Science community, specific attention was often not given to the unique characteristics (e.g. spatial dependence) and evolutions in geospatial data (e.g. increasing temporal/spatial resolutions and extents). Beginning in 2015, researchers such as Luc Anselin as well as others who had been developing geospatial cyber-infrastructure (CyberGIS) since 2008 began to call for a Spatial Data Science, a field that could leverage the advances from Data Science, such as data mining, machine learning, and other statistical and visualization ‘big’ data techniques, for geospatial data. New challenges have emerged from this rapid expansion in data and tool options: how to scale analyses for ‘big’ data; deal with uncertainty and quality for data synthesis; evaluate options and choose the right data or tool; integrate options when only one will not suffice; and use emerging tools to effectively collaborate on increasingly more multi-disciplinary and multi-dimensional research that aims to address our current societal and environmental challenges, such as climate change, loss of biodiversity and natural areas, and wildfire management. This dissertation addresses in part these challenges by applying emerging methods and tools in Spatial Data Science (such as cloud-computing, cluster analysis and machine learning) to develop new frameworks for evaluating geospatial tools based on collaborative potential and for evaluating and integrating competing remotely-sensed map products of vegetation change and disturbance. In Chapter One, I discuss in further detail the historical trajectory toward a Spatial Data Science and provide a new working definition of the field that recognizes its interdisciplinary and collaborative potential and that serves as the guiding conceptual foundation of this dissertation. In Chapter Two, I identify the key components of a collaborative Spatial Data Science workflow to develop a framework for evaluating the various functional aspects of multi-user geospatial tools. Using this framework, I then score thirty-one existing tools and apply a cluster analysis to create a typology of these tools. I present this typology as the first map of the emergent ecosystem and functional niches of collaborative geospatial tools. I identify three primary clusters of tools composed of eight secondary clusters across which divergence is driven by required infrastructure and user involvement. I use my results to highlight how environmental collaborations have benefited from these tools and propose key areas of future tool development for continued support of collaborative geospatial efforts. In Chapters Three and Four, I apply Spatial Data Science within a case study of California fire to compare the differences as well as explore the synergies between the three remotely-sensed map products of vegetation disturbance for 2001-2010: Hansen Global Forest Change (GFC); North American Forest Dynamics (NAFD); and Landscape Fire and Resource Management Planning Tools (LANDFIRE). Specifically, Chapter Three identifies the implications of the differing creation methods of these products on their representations of disturbance and fire. I identify that LANDFIRE (the traditional created product that integrates field data and public data on disturbance events with remote sensing) reported the highest amount of vegetation disturbance across all years and habitat types, as compared to GFC and NAFD, which are both produced from automated remote sensing analyses. I also find that these differences in reported disturbance are driven by differential inclusion of reference data on fire (rather than differences in environmental conditions) and identify the widest range in reported disturbance (i.e. more uncertainty) in years with more fire incidence and in scrub/shrub habitat. In Chapter Four, I use spatial agreement among the competing products as a measure of uncertainty. I identify low uncertainty in disturbance (i.e. where all products agree) across only 15% of the total area of California that was reported as disturbed by at least one product between 2001 and 2010. Specifically, I find that scrub/shrub habitat had a lower uncertainty of disturbance than forest, particularly for fire, and that uncertainty was universally high across all bioregions. I also identify that LANDFIRE was solely responsible for approximately 50% of the total area reported as disturbed and find large differences between the burned areas reported by the reference data and the areas with low uncertainty of disturbance, indicating potential overestimation of disturbance by both LANDFIRE and the reference data on fire. Last, in Chapter Five, I conclude by highlighting how unresolved key challenges for Spatial Data Science can serve as new opportunities to guide the scaling of methods for “big” data, increased spatial-temporal integration, as well as promote new curriculum to better prepare future Spatial Data Scientists. In all, this dissertation explores the opportunities and challenges posed by Spatial Data Science and serves as a guiding reference for professionals and practitioners to successfully navigate the changing world of geospatial data and tools.

Computing in Geographic Information Systems

The computing paradigms such as distributed computing, grid computing, cloud
computing, network computing, and quantum computing make their impact in GIS
by evolving new algorithms, processing large volumes of spatial data. 1.1.5 GIS ...


Author: Narayan Panigrahi

Publisher: CRC Press

ISBN: 9781482223149

Category: Mathematics

Page: 303

View: 643

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.

AI and Cloud Computing

AI and Cloud Computing, Volume 120 in the Advances in Computers series, highlights new advances in the field, with this updated volume presenting interesting chapters on topics including A Deep-forest based Approach for Detecting Fraudulent ...



Publisher: Academic Press

ISBN: 9780128211472

Category: Computers

Page: 310

View: 962

AI and Cloud Computing, Volume 120 in the Advances in Computers series, highlights new advances in the field, with this updated volume presenting interesting chapters on topics including A Deep-forest based Approach for Detecting Fraudulent Online Transaction, Design of Cyber-Physical-Social Systems with Forensic-awareness Based on Deep Learning, Review on Privacy-preserving Data Comparison Protocols in Cloud Computing, Fingerprint Liveness Detection Using an Improved CNN with the Spatial Pyramid Pooling Structure, Protecting Personal Sensitive Data Security in the Cloud with Blockchain, and more. Provides the authority and expertise of leading contributors from an international board of authors Presents the latest release in the Advances in Computers series Includes the latest information on AI and Cloud Computing

Visualization in Scientific Computing

Such rotations are small enough to maintain the general orientation of the cloud
so that examination is not adversely affected , yet large enough to maintain the
illusion of a third spatial dimension while the cloud is being examined . Software


Author: Gregory M. Nielson


ISBN: UOM:39015021512580

Category: Computer graphics

Page: 283

View: 592

The purpose of this text is to provide a reference source to scientists, engineers, and students who are new to scientific visualization or who are interested in expanding their knowledge in this subject. If used properly, it can also serve as an introduction and tutorial.

ACM Transactions on Modeling and Computer Simulation

A Publication of the Association for Computing Machinery ... Ware and Beatty (
1988 ] have designed a method that uses color to represent multidimensional
data elements ; subsets of the data with similar values appear as a spatialcloud
” of ...




ISBN: UOM:39015036301060

Category: Computer simulation


View: 660

Geographical Information Systems

The mid 1960s witnessed the initial development of GIS in combining spatially
referenced data, spatial data models and ... Specifically, mobile and internet
devices, Cloud computing, NoSQL databases, Semantic Web, Web services offer
new ...


Author: Elaheh Pourabbas

Publisher: CRC Press

ISBN: 9781466596955

Category: Computers

Page: 358

View: 197

Web services, cloud computing, location based services, NoSQLdatabases, and Semantic Web offer new ways of accessing, analyzing, and elaborating geo-spatial information in both real-world and virtual spaces. This book explores the how-to of the most promising recurrent technologies and trends in GIS, such as Semantic GIS, Web GIS, Mobile GIS, NoSQL Geographic Databases, Cloud GIS, Spatial Data Warehousing-OLAP, and Open GIS. The text discusses and emphasizes the methodological aspects of such technologies and their applications in GIS.