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A ground-up approach to explaining dynamic spatial modelling for an interdisciplinary audience. Across broad areas of the environmental and social sciences, simulation models are  an important way to study systems inaccessible to scientific experimental and observational methods, and also an essential complement to those more conventional approaches.  The contemporary research literature is teeming with abstract simulation models whose presentation is mathematically demanding and requires a high level of knowledge of quantitative and computational methods and approaches.  Furthermore, simulation models designed to represent specific systems and phenomena are often complicated, and, as a result, difficult to reconstruct from their descriptions in the literature.  This book aims to provide a practical and accessible account of dynamic spatial modelling, while also equipping readers with a sound conceptual foundation in the subject, and a useful introduction to the wide-ranging literature. Spatial Simulation: Exploring Pattern and Process is organised around the idea that a small number of spatial processes underlie the wide variety of dynamic spatial models. Its central focus on three 'building-blocks' of dynamic spatial models – forces of attraction and segregation, individual mobile entities, and processes of spread – guides the reader to an understanding of the basis of many of the complicated models found in the research literature. The three building block models are presented in their simplest form and are progressively elaborated and related to real world process that can be represented using them.  Introductory chapters cover essential background topics, particularly the relationships between pattern, process and spatiotemporal scale.  Additional chapters consider how time and space can be represented in more complicated models, and methods for the analysis and evaluation of models. Finally, the three building block models are woven together in a more elaborate example to show how a complicated model can be assembled from relatively simple components. To aid understanding, more than 50 specific models described in the book are available online at patternandprocess.org for exploration in the freely available Netlogo platform.  This book encourages readers to develop intuition for the abstract types of model that are likely to be appropriate for application in any specific context.  Spatial Simulation: Exploring Pattern and Process will be of interest to undergraduate and graduate students taking courses in environmental, social, ecological and geographical disciplines.  Researchers and professionals who require a non-specialist introduction will also find this book an invaluable guide to dynamic spatial simulation.

Traditional methods for handling spatial data are encumbered by the assumption of separate origins for horizontal and vertical measurements, but modern measurement systems operate in a 3-D spatial environment. The 3-D Global Spatial Data Model: Principles and Applications, Second Edition maintains a new model for handling digital spatial data, the global spatial data model or GSDM. The GSDM preserves the integrity of three-dimensional spatial data while also providing additional benefits such as simpler equations, worldwide standardization, and the ability to track spatial data accuracy with greater specificity and convenience. This second edition expands to new topics that satisfy a growing need in the GIS, professional surveyor, machine control, and Big Data communities while continuing to embrace the earth center fixed coordinate system as the fundamental point of origin of one, two, and three-dimensional data sets. Ideal for both beginner and advanced levels, this book also provides guidance and insight on how to link to the data collected and stored in legacy systems. -- Provided by publisher.

With the advancement of GIS technology since its inception in 1960’s, many educational institutions, government departments, public/ private sectors and individuals have started its use for the production and management of spatial data. Spatial Data Infrastructure (SDI) concept was introduced in the early1990’s and provides a set of technologies, standards, protocols, policies and guidelines on the whole cycle of geospatial data production and distributions, i.e., from data capture to storage and to sharing. SDI initiative at national level, termed as National Spatial Data Infrastructure (NSDI), has been taken by different countries including India. Geospatial community is facing various challenges like handling of large volumes of geospatial data, requirement of high computing resources to process geospatial data, scalability and interoperability. Therefore, need of advanced technologies in the form of SDI and cloud computing is realized to resolve the above challenges. Cloud computing has several characteristics like scalability, elasticity and self-provisioning that offers high-performance computing resources to perform geoprocessing efficiently. The main aim of the present paper is to study SDI and its components along with analysis and comparison of NSDI of various countries as well as to conceptualize and discuss service oriented architecture of cloud enabled SDI. Several challenges of the spatial data handling and processing that occurred due to the high intensity of data and lack of processing capability can be solved by adopting proposed cloud enabled SDI architecture. This research will help geospatial community and SDI developers in various perspectives including data sharing and management, interoperability, security and reliability, fault tolerance, mass market solution, upfront cost and global collaboration.

This book draws on author's wealth of knowledge working on numerous projects across many countries. It provides a clear overview of the development of the SDI concept and SDI worldwide implementation and brings a logical chronological approach to the linkage of GIS technology with SDI enabling data. The theory and practice approach help understand that SDI development and implementation is very much a social process of learning by doing. The author masterfully selects main historical developments and updates them with an analytical perspective promoting informed and responsible use of geographic information and geospatial technologies for the benefit of society from local to global scales. -- Provided by publisher.

Gaining useful information about our built, social and natural environments is vital and possible. The value of data for cities is more informed, more effective management and development choices resulting in more benefits to a greater range of stakeholders. This article explores the state-of-play of data infrastructures in New Zealand to identify the challenges to gaining better value from geospatial information. Following engagement with built environment data custodians and information users, it analyses how digital information infrastructure can support the sharing and use of richer and more comprehensive information by weaving a supportive fabric across data. The analysis reveals that data infrastructures primarily need to facilitate agreement on data management, sharing and use; the sharing of costs and benefits across stakeholders; and emphasise place as a powerful driver to richer information. An overarching sociotechnical approach to digital information infrastructure weaves data platforms, policy and technology together.

Traditional methods for handling spatial data are encumbered by the assumption of separate origins for horizontal and vertical measurements, but modern measurement systems operate in a 3-D spatial environment. The 3-D Global Spatial Data Model: Principles and Applications, Second Edition maintains a new model for handling digital spatial data, the global spatial data model or GSDM. The GSDM preserves the integrity of three-dimensional spatial data while also providing additional benefits such as simpler equations, worldwide standardization, and the ability to track spatial data accuracy with greater specificity and convenience. This second edition expands to new topics that satisfy a growing need in the GIS, professional surveyor, machine control, and Big Data communities while continuing to embrace the earth center fixed coordinate system as the fundamental point of origin of one, two, and three-dimensional data sets. Ideal for both beginner and advanced levels, this book also provides guidance and insight on how to link to the data collected and stored in legacy systems.

Although universities conduct research in the SDI field, they have repeatedly erred when storing, preserving, and sharing their geospatial data. The general objective of this research is to develop a proposal for a Spatial Data Infrastructure (SDI) for the graduate programs of the Department of Earth Sciences at Federal University of Paraná (UFPR). In order to initiate the process of implementing UFPR's academic SDI, a sample of the theses and dissertations of the aforementioned programs was collected. Subsequently, a survey of the metadata of the spatial study areas and publications was conducted, and finally, these metadata were made available as a catalog through GeoNetwork. The metadata, ISO TC-221, OGC and WC3 standards recommended by INDE-BR were adopted, and free and open source software was used. In this paper, the results of the metadata survey and their availability are presented in the form of a catalog, as well as a synthesis of the reflections made during the execution of the research, in order to help define the characteristics of academic SDIs in the country. The cataloging of historical metadata was found to be viable and to facilitate the dissemination of geospatial data to the scientific community.

There is a demand for evaluation of spatial data infrastructures (SDIs), to justify and monitor the relations between investments in SDI initiatives and the results obtained. It is also essential to pay particular attention to identifying user communities, and eliciting their assessment of effects deriving from an SDI. The paper introduces a concept of a multi-criteria method which allows to assess effectiveness of the SDI from the user perspective. The application of the proposed method in the Polish Spatial Data Infrastructure (PSDI) and its main access point to spatial data and services called ‘Geoportal 2’ as well as two groups of the national geoportal”s users (spatial planners and land surveyors) presents its potential. The total scores for the Geoportal 2 indicated the investment has potential and is quite effective, although some components of the PSDI (e.g. main access point, datasets, network services, software, hardware, procedures) may need improvements and additional analyses in the future. The contribution of this paper is the multi-criteria method which enables the analysis of outcomes, benefits (impacts) and business value of using SDI business project’s artifacts (outputs) considering the following dimensions: information and support provided, use process, user organizational performance, strategic alignment and business impact on user enterprise.

In 'Spatial Data Infrastructures at Work', Ezra Dessers introduces spatial enablement as a key concept to describe the realisation of SDI objectives in the context of individual public sector processes. Drawing on four years of research, Dessers argues that it has become essential, even unavoidable, to manage and (re)design inter-organisational process chains in order to further advance the role of SDIs as an enabling platform for a spatially enabled society. Detailed case studies illustrate that the process he describes is the setting in which one can see the SDI at work.