Journal article
Methods for Space-Time Analysis and Modeling: An Overview
International journal of applied geospatial research, v 4(4), pp 1-18
01 Oct 2013
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
With increasing availability of spatio-temporal data and the democratization of Geographical Information Systems (GIS), there has been a demand for novel statistical and visualization techniques which can explicitly integrate space and time. The paper discusses the nature of spatio-temporal data, the integration of time within GIS and the flourishing availability of spatial and temporal-explicit data over the Internet. The paper attempts to answer the fundamental question on how these large datasets can be analyzed in space and time to reveal critical patterns. The authors further elaborate on how spatial autocorrelation techniques are extended to deal with time, for point, linear, and areal features, and the impact of parameter selection, such as critical distance and time threshold to build adjacency matrices. The authors also discuss issues of space-time modeling for optimization problems.
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Details
- Title
- Methods for Space-Time Analysis and Modeling: An Overview
- Creators
- Eric Delmelle - University of North Carolina at CharlotteChangjoo Kim - University of CincinnatiNingchuan Xiao - The Ohio State UniversityWei Chen - The Ohio State University
- Publication Details
- International journal of applied geospatial research, v 4(4), pp 1-18
- Publisher
- Igi Global
- Number of pages
- 18
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Urban Health Collaborative
- Web of Science ID
- WOS:000219204700002
- Scopus ID
- 2-s2.0-84897899818
- Other Identifier
- 991021874423504721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Geography