Spatial refers to space. Temporal refers to time. Spatiotemporal, or spatial temporal, is used in data analysis when data is collected across both space and time. It describes a phenomenon in a certain location and time — for example, shipping movements across a geographic area over time (see above example image).
However, there is no a commonly agreed definition of what is a spatio-temporal data warehouse and what functionality such a data warehouse should support.
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However, there is no a commonly agreed definition of what is a spatio-temporal data warehouse and what functionality such a data warehouse should support.
Spatio-temporal data warehouses can collect and store readings from geographically distributed sensors. As an example consider a pollution monitoring system, ...
Spatiotemporal exploratory data analysis is a methodological approach to detect and describe patterns, trends, and relations in data in both space and time.
Sep 20, 2024 · Spatial data mining is a process of extracting patterns according to location and temporal data mining deals with time series. These two are ...
A spatiotemporal database is a database that manages both space and time information. Common examples include: Tracking of moving objects, which typically ...
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One particular aspect in this respect concerns mobility data management, i.e., storing mobility data in a data warehouse for their subsuquent analysis. This ...
data in a more general data warehousing framework, which we call spatio-temporal data warehousing [1]. II. SPATIO-TEMPORAL DATA WAREHOUSES. Data warehouses ...
In this paper we propose a Spatio-Temporal data warehousing (STDW) for efficiently querying location ... Spatio-temporal data warehousing (or trajectory data ...