Methodology: Space-Time Analysis (S-T Analysis)

Space-time analysis has become a buzzword in the last decade or so. What really is it? Largely speaking, space-time analysis aims to answer questions of both "when" and "where" things occur, and sometimes, why things occur at locations or times of interest. Interest in space-time analysis can date to early stage of human history as a certain thing of interest (e.g., an event or a phenomenon) often had to be associated with a space and a time. However, since the 1990s, the number of publications about space-time analysis has exploded (An et al. 2015), signaling the advent of an era of space-time analysis.

Based on a literature review, An et al. (2015) have raised a typology of space-time analysis, which classifies various methods, models, and tools into two types: one for individual movement data analysis and one for spatial panel data analysis. Under each type, models can be largely labeled as pattern revelation models, space-time statistical models, and process-based simulation models. More details see the table below (from An et al. 2015).



The CHES group has been advocating and advancing two very important space-time analysis models: latent trajectory models connecting to eigenvector spatial filtering (LTM-ESF; An et al. 2016, Crook et al. 2016) and landscape survival analysis (LSA; An et al. 2008, 2011). Also through developing 4-D ABM, the CHES group is making space-time analysis more robust in visualizing, explaining, and envisioning human-landscape processes. Below are papers for generic knowledge of space-time analysis.

Readings and References:

An, L., M. Tsou, B. Spitzberg, J.M. Gawron, and D.K. Gupta (2016). Latent trajectory models for space-time analysis: An application in deciphering spatial panel data. Geographical Analysis (see the link below for "The LTM-ESF Paper").

An, L., and S. Crook (2016). Spatiotemporal analysis. Entry for The International Encyclopedia of Geography: People, the Earth, Environment, and Technology. Section editor: Mei-Po Kwan; general editor: Michael Goodchild.

An, L., M. Tsou, S. Crook, B. Spitzberg, J.M. Gawron, and D.K. Gupta (2015). Space-time analysis: Concepts, quantitative methods, and future directions. Annals of Association of American Geographers 105(5):891-914.

An, L., D. G. Brown, J. Nassauer, and B. Low (2011). Variations in development of exurban residential landscapes: Timing, location, and driving forces. Journal of Land Use Science.6 (1): 13–32.

An, L., and D. G. Brown (2008). Survival analysis in land-change science: integrating with GIScience to address temporal complexities. Annals of Association of American Geographers 98(2): 323-344.

Crook, S.E.S., L. An, D.A. Stow, and J.R. Weeks (2016). Latent trajectory modeling of spatiotemporal relationships between land cover and land use, socioeconomics, and obesity in Ghana. Spatial Demography 4(3): 221-244 (DOI 10.1007/s40980-016-0024-6).

Yuan, M., A. Nara, and J. Bothwell (2014). Space–time representation and analytics. Annals of GIS 20 (1): 1–9.

Models and Examples:

See this page for specific models, methods, and the related documentations.