Download e-book for kindle: Computation and Visualization for Understanding Dynamics in by May Yuan

By May Yuan

ISBN-10: 1420060325

ISBN-13: 9781420060324

The realm is ever altering, and a finished knowing of the area should not completed with out theoretical and methodological advances to decode complicated dynamics in human and environmental platforms.

Computation and Visualization for the certainty of Dynamics in Geographic domain names: A examine schedule synthesizes key principles and concerns mentioned in the course of the UCGIS hosted workshop on computation. It expands upon renowned discussions to supply a accomplished assessment of geographic dynamics and new techniques to enhance our figuring out of geographic dynamics via computation and visualization.

The textual content provides an outline of the kingdom of study and the way this learn pertains to intelligence research. It addresses huge concerns and demanding situations in parts, reminiscent of spatiotemporal research and modeling, spatiotemporal visible analytics; spatiotemporal info mining, spatiotemporal reasoning, and spatiotemporal ontologies. The booklet additionally fuses feedback from workshop individuals with literature experiences to suggest new examine agendas and proposals for destiny advancements and collaboration.

With complete assurance on present advancements and possibly demanding situations, Computation and Visualization for the knowledge of Dynamics in Geographic domain names: A examine schedule establishes a starting place to advertise additional reviews in geographic dynamics and offers a springboard for the following gigantic medical and technological leap forward.

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Additional resources for Computation and Visualization for Understanding Dynamics in Geographic Domains: A Research Agenda

Example text

Geographic dynamics is observed through change and movement. Change addresses differences in properties or structures. Movement can be regarded as change in locations, but movement also prescribes speed and direction. Determination of identity is crucial for analysis of change or movement. GIS technology commonly uses location (be it a point, a line, or a polygon) as the basis for identity. While location-based identities facilitate change analysis through spatial overlays, the approach inherently has identities fixed with location and loses capabilities to represent movement.

The idea is used to represent storm processes through a hierarchical framework that captures footprints and transitions during a storm’s development (Yuan 2001b; McIntosh and Yuan 2005a). The representation starts with zone data objects to represent spatial footprints of a storm at different times. The hierarchical framework links zone data objects over time to form a sequence data object that tracks the locations and geometries of the storm over space and time. To account for merging and splitting during the storm development, a process data object is used to embed joint sequences that result from splitting an original sequence or from merging two sequences.

From these efforts, change becomes a major focus of analysis, although for many applications, merely recording change at locations is insufficient and ineffective, because information about the patterns of change through time is essential. To this end, time can serve a more effective reference than space to manage data about change. The Event-Based SpatioTemporal Data Model (ESTDM) organizes locations of change in a time series to facilitate temporal data retrieval and analysis (Peuquet and Duan 1995).

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Computation and Visualization for Understanding Dynamics in Geographic Domains: A Research Agenda by May Yuan

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