This document defines key concepts for spatiotemporal data analysis including spatial concepts like points, geometric figures, spatial objects, and layers. It also defines temporal concepts like time points, time intervals, time periods, events, and states. Spatiotemporal concepts combine spatial and temporal concepts by recording spatial views like objects and layers at different time points and intervals. Common spatiotemporal data models are also listed along with references.
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Definition
Spatial Concepts
Points1 : The elements of space
Geometric figures1 : finite sets of points (i.e., subsets of space, which can be point,
lines or regions)
Spatial objects1 : An object with spatial attributes
Spatial attribute1 : is specifies the object's geometric coordinates.
Layer1 : is a representation of a spatial attribute or a layer is a set of
geometric figures. .
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Definition
Temporal Concepts
We assume a linear ordered time line, isomorphic to a finite subset of the natural
numbers. The elements of this set are termed chronons.
Time points : is considered as one chronon.
Time intervals [tk...tm] : with tktm, time point sand k<m, has duration and is
defined as set of chronons.
Time period : defined as a set of time points, time intervals or any combination
thereof.
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Definition
Temporal Concepts
An event occurs at an exact time point, i.e., an event has no duration. Example
events are a car crash, sunrise etc.
A state is defined for each chronon in a time interval, hence it has a duration.
For example, a exam takes place from loam until lpm.
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Time series models
Autoregressive (AR) models
Moving-average (MA) models
Autoregressive moving-average (ARMA) models
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Definition
Spatiotemporal Concepts
We combine the concepts of spatial and temporal by simply recording the spatial
view (i.e., objects and layers) in time (time point and time interval);
For a moving vehicle in a route network we can record its new position in time
points
t1tk. In the same way, as a land parcel changes its shape (eg. split , expanded
etc.),we capture snapshots of such spatial object in time.
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Spatial Object Layer
Time Point Snapshot Snapshot (temporal layer)
Time Interval Motion,Change Phenomenon; Change
Time Period Snapshot;Version;Motion;Change Snapshot;Version;Phenomenon;Change
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Snapshot model (Armstrong 1988)
Spatiotemporal composite model (Langran and Chrisman 1988)
Event-based spatiotemporal data model (Peuquet and Duan 1995)
Three-domain data model (Yuan 1999)
Geo-atom model (Goodchild et al. 2007, Chen et al. 2012)
Object-oriental models (Wang and Cheng 2001)
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References
Xiaoyu Wang, Xiaofang Zhou . Spatiotemporal Data Modelling and Management: a Survey
Pebesma, Edzer, and others. 2012. Spacetime: Spatio-Temporal Data in r. Journal of
Statistical Software 51 (7): 130.
nnerfors, sa, Mariana Kotzeva, Teod坦ra Brandm端ller, and others. 2019. Eurostat Regional
Yearbook 2019 Edition.
Rowe, Francisco, Nikos Patias, and Dani Arribas-Bel. 2020. Policy Brief: Neighbourhood
Change and Trajectories of Inequality in Britain, 1971-2011.
Rowe, Francisco, and Nikos Patias. 2020. Mapping the Spatial Patterns of Internal Migration
in Europe. Regional Studies, Regional Science 7 (1): 39093.
Kwan, Mei-Po, and Jiyeong Lee. 2004. Geovisualization of Human Activity Patterns Using 3d
GIS: A Time-Geographic Approach. Spatially Integrated Social Science 27: 72144.
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References
Bi Yu Chen, Hui Yuan, Qingquan Li, Shih-Lung Shaw, William H.K. Lam & Xiaoling Chen
(2016) Spatiotemporal data model for network time geographic analysis in the era of big data,
International Journal of Geographical Information Science, 30:6, 1041-1071,