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The Rise of Big Spatial Data (Hardcover, 1st ed. 2017): Igor Ivan, Alex Singleton, Jiri Horak, Tomas Inspektor The Rise of Big Spatial Data (Hardcover, 1st ed. 2017)
Igor Ivan, Alex Singleton, Jiri Horak, Tomas Inspektor
R7,217 Discovery Miles 72 170 Ships in 12 - 17 working days

This edited volume gathers the proceedings of the Symposium GIS Ostrava 2016, the Rise of Big Spatial Data, held at the Technical University of Ostrava, Czech Republic, March 16-18, 2016. Combining theoretical papers and applications by authors from around the globe, it summarises the latest research findings in the area of big spatial data and key problems related to its utilisation. Welcome to dawn of the big data era: though it's in sight, it isn't quite here yet. Big spatial data is characterised by three main features: volume beyond the limit of usual geo-processing, velocity higher than that available using conventional processes, and variety, combining more diverse geodata sources than usual. The popular term denotes a situation in which one or more of these key properties reaches a point at which traditional methods for geodata collection, storage, processing, control, analysis, modelling, validation and visualisation fail to provide effective solutions. >Entering the era of big spatial data calls for finding solutions that address all "small data" issues that soon create "big data" troubles. Resilience for big spatial data means solving the heterogeneity of spatial data sources (in topics, purpose, completeness, guarantee, licensing, coverage etc.), large volumes (from gigabytes to terabytes and more), undue complexity of geo-applications and systems (i.e. combination of standalone applications with web services, mobile platforms and sensor networks), neglected automation of geodata preparation (i.e. harmonisation, fusion), insufficient control of geodata collection and distribution processes (i.e. scarcity and poor quality of metadata and metadata systems), limited analytical tool capacity (i.e. domination of traditional causal-driven analysis), low visual system performance, inefficient knowledge-discovery techniques (for transformation of vast amounts of information into tiny and essential outputs) and much more. These trends are accelerating as sensors become more ubiquitous around the world.

The Rise of Big Spatial Data (Paperback, Softcover reprint of the original 1st ed. 2017): Igor Ivan, Alex Singleton, Jiri... The Rise of Big Spatial Data (Paperback, Softcover reprint of the original 1st ed. 2017)
Igor Ivan, Alex Singleton, Jiri Horak, Tomas Inspektor
R6,189 Discovery Miles 61 890 Ships in 10 - 15 working days

This edited volume gathers the proceedings of the Symposium GIS Ostrava 2016, the Rise of Big Spatial Data, held at the Technical University of Ostrava, Czech Republic, March 16-18, 2016. Combining theoretical papers and applications by authors from around the globe, it summarises the latest research findings in the area of big spatial data and key problems related to its utilisation. Welcome to dawn of the big data era: though it's in sight, it isn't quite here yet. Big spatial data is characterised by three main features: volume beyond the limit of usual geo-processing, velocity higher than that available using conventional processes, and variety, combining more diverse geodata sources than usual. The popular term denotes a situation in which one or more of these key properties reaches a point at which traditional methods for geodata collection, storage, processing, control, analysis, modelling, validation and visualisation fail to provide effective solutions. >Entering the era of big spatial data calls for finding solutions that address all "small data" issues that soon create "big data" troubles. Resilience for big spatial data means solving the heterogeneity of spatial data sources (in topics, purpose, completeness, guarantee, licensing, coverage etc.), large volumes (from gigabytes to terabytes and more), undue complexity of geo-applications and systems (i.e. combination of standalone applications with web services, mobile platforms and sensor networks), neglected automation of geodata preparation (i.e. harmonisation, fusion), insufficient control of geodata collection and distribution processes (i.e. scarcity and poor quality of metadata and metadata systems), limited analytical tool capacity (i.e. domination of traditional causal-driven analysis), low visual system performance, inefficient knowledge-discovery techniques (for transformation of vast amounts of information into tiny and essential outputs) and much more. These trends are accelerating as sensors become more ubiquitous around the world.

Consumer Data Research (Paperback): Paul A. Longley, Alex Singleton, James Cheshire Consumer Data Research (Paperback)
Paul A. Longley, Alex Singleton, James Cheshire
R596 Discovery Miles 5 960 Ships in 12 - 17 working days
Patch the Cat (Paperback): Ben Hay, Alex Singleton Patch the Cat (Paperback)
Ben Hay, Alex Singleton
R243 Discovery Miles 2 430 Ships in 10 - 15 working days
Underworld (Paperback): Katherine Sutherland, Alex Singleton Underworld (Paperback)
Katherine Sutherland, Alex Singleton
R283 Discovery Miles 2 830 Ships in 10 - 15 working days

Persephone is a shadowy liminal figure, shifting, both in image and in character across time. Was she a victim of the wiles of Hades, or a willing Queen of the underworld? In this lyrical re-working of the classical myth of Persephone and the epic journey to and return from the underworld, her voice is explored as it has never been heard before. Through a rich tapestry of words and images that resonate with both classical and contemporary interpretations of this grand narrative, Katherine Sutherland and Alex Singleton breath new life into the age-old story of descent, ascent and transformation.

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