Table of Contents
Storing data describing the hydrologic environment requires temporal as well as geospatial referencing of data. In dynamic systems like a flood event or pollutant transport, it is impossible to understand the system without temporal context. Commercial GIS systems have traditionally focused on geospatial and not temporal referencing of data, limiting the usefulness of GIS for visualizing dynamic hydrologic events. Recent research at the Center for Research in Water Resources (CRWR) has focused on designing a set of spatio-temporal data types capable of providing the foundation for a temporal GIS. Just as the point, line, polygon, raster, and TIN provide the foundation for geospatial data representation, our goal is to develop these spatial data types to describe spatio-temporal phenomena. The result is three spatio-temporal data types called "Attribute Series", "Feature Series", and "Raster Series" presented in Figure 1 with a generic non-spatial data type called "Time Series."
Figure 1 - Time Series and three spatio-temporal data representations.
Time Series
Time Series are a collection of time, value pairs. Time Series are not directly georeferenced, but can be indirectly georeferenced through a many-to-many relationship (many time series records can be related to many spatial features). In Figure 1, Time Series is disconnected from the other four features to indicate that it is not a spatio-temporal data structure, but instead a link to the "outside world" of hydrologic time series modeling and analysis.
Attribute Series
An Attribute Series is a collection of time-value pairs that are related to one spatial feature. The name Attribute Series comes from the idea that it is describing a feature with a dynamic attribute value - a particular attribute of that feature that varies with time (e.g., flow, dissolved oxygen concentration, precipitation, etc.). An Attribute Series is identical to the current Arc Hydro TimeSeries component where there are two tables: one to store the time-value records, and one to store metadata describing the type of time series being measured (see Chapter 7 of the Arc Hydro book for more detail).
Feature Series
Feature Series are a collection of shape, time pairs. A Feature Series is a collection of features indexed by time. Each feature in a feature series exists for only a period of time, making Feature Series an ideal structure for representing a series of flood inundation polygons. Feature Series could also be used to represent the movement of particles through the environment. In this case, the Feature Series would be a set of points, each valid for some instant in time.
Raster Series
Finally,
Raster Series are a collection of rasters indexed by time. Each raster is
a "snapshot" of the environment at some instant in time.
Grouping a series of rasters can describe how the environment changes over
time. Raster Series is useful for describing the dynamics of spatially
continuous phenomena, like ponded depth in the
For more information about the conceptual framework for representing time and space in GIS, please see:
Goodall, J.L., D.R. Maidment, and J. Sorenson. 2004. Representation
of Spatial and Temporal Data in ArcGIS, AWRA GIS and Water Resources III
Conference,
e-mail: twhit@mail.utexas.edu
Phone: (512) 471-0570
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please credit the authors and the Center for Research in Water Resources, The