Representing Time and Space in GIS
Tim Whiteaker, CRWR
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 was 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 Everglades, or rainfall measured by NEXRAD.
Space-Time Toolbox - An ArcToolbox for processing geospatial data through time created by Jon Goodall. Download Setup File
Data Ingestion Toolset:
1. Ingest a series of ASCII rasters in to a Raster
Catalog indexed by time and time series type.
2. Download water and energy fluxes for a lat/long box
from North American Regional Reanlysis (NARR)
3. Download time series data from National Water Information
System (NWIS) for one or more stations and one or more parameters
External Processing Toolset:
1. Call an R command
Hydrologic Processing Toolset:
1. Perform a water balance on a feature that is coupled
to a series of flux and/or flow time series (requires a Coupling Table)
Temporal Geoprocessing Toolset:
1. Create a series of rasters indexed by time from a
point feature class and related time series through interpolation (Kriging, IDW,
or Spline)
2. Extract a time series from a series of time indexed
rasters for a point, line, or area feature class. (returns the average value of
the raster pixels)
Time Scaling Toolset:
1. Upscale an attribute series (e.g. from daily to
monthly)
TS Window Toolbar - An ArcMap tool for plotting time series for one or more selected features created by Jon Goodall. Download Setup File (Setup Instructions)
Arc Hydro TimeSeries provides a means for storing spatially and temporally irregular measurements within two tables. The first table, named TimeSeries, is a repository for all the measurement values and the time they where collected. The second table, named TSType, is a metadata catalog for describing the properties of a particular type of time series. While this is a very general and flexible system for handling different types of time series, it is not easy to understand, analyze, or visualize the time series in its native data format.
For this reason, we have begun to develop tools for visualizing time series stored in Arc Hydro using ArcMap. The tool is called TS Window and is a toolbar to ArcMap for graphing time series for a selected set of features over a user defined interval of time.
The purpose of this tool is simply to allow one to quickly view temporal information within an Arc Hydro geodatabase. The tools are not designed for performing complex time series analysis or modeling, although the TSWindow application does allow adding and subtracting of time series to perform simple water balance accounting. Instead, the tools provide a means for selecting a subset of data within an Arc Hydro geodatabase and "rearranging" the data to provide useful information to a user.
TS Window Toolbar also includes functions to retrieve flow and water-quality data from the internet, as shown in the following figure.
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, Nashville, TN.
Tim Whiteaker
University of Texas at Austin
e-mail: twhit@mail.utexas.edu
Phone: (512) 471-0570
These materials may be used for study, research, and education, but please credit the authors and the Center for Research in Water Resources, The University of Texas at Austin. All commercial rights reserved. Copyright 2004 Center for Research in Water Resources.