Developments In Multidimensional Spatial Data Models
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Developments in Multidimensional Spatial Data Models
Author: Alias Abdul Rahman
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-04-13
This book presents the latest research developments in geoinformation science, which includes all the sub-disciplines of the subject, such as: geomatic engineering, GIS, remote sensing, digital photogrammetry, digital cartography, etc.
Recent Advances in 3D Geoinformation Science
The book includes the contributions to the international conference “18th 3D GeoInfo”. The papers published in the book were selected through a double-blind review process. 3D GeoInfo has been the forum joining researchers, professionals, software developers, and data providers designing and developing innovative concepts, tools, and application related to 3D geo data processing, modeling, management, analytics, and simulation. A big focus is on topics related to data modeling for 3D city and landscape models as well as their many and diverse applications. This conference series is very successfully running since 2006 and has been hosted by countries in Europe, Asia, Africa, North America, and Australia. In the period 2006 to 2017, the proceedings has been published by Springer in this series with Thomas H. Kolbe being the editor of the 2010 edition of the conference proceedings. 18th 3DGeoInfo was organized by Technical University of Munich in cooperation with the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF), the local associations Runder Tisch GIS e.V. (Round Table GIS) and Leonhard Obermeyer Center—TUM Center of Digital Methods for the Built Environment, and the City of Munich. The international program committee consisted of committee members of previous 3D GeoInfo conferences and further leading scientists in the field of 3D Geoinformation Science.
Emerging Trends, Techniques, and Applications in Geospatial Data Science
With the emergence of smart technology and automated systems in today’s world, big data is being incorporated into many applications. Trends in data can be detected and objects can be tracked based on the real-time data that is utilized in everyday life. These connected sensor devices and objects will provide a large amount of data that is to be analyzed quickly, as it can accelerate the transformation of smart technology. The accuracy of prediction of artificial intelligence (AI) systems is drastically increasing by using machine learning and other probability and statistical approaches. Big data and geospatial data help to solve complex issues and play a vital role in future applications. Emerging Trends, Techniques, and Applications in Geospatial Data Science provides an overview of the basic concepts of data science, related tools and technologies, and algorithms for managing the relevant challenges in real-time application domains. The book covers a detailed description for readers with practical ideas using AI, the internet of things (IoT), and machine learning to deal with the analysis, modeling, and predictions from big data. Covering topics such as field spectra, high-resolution sensing imagery, and spatiotemporal data engineering, this premier reference source is an excellent resource for data scientists, computer and IT professionals, managers, mathematicians and statisticians, health professionals, technology developers, students and educators of higher education, librarians, researchers, and academicians.