You can control visualization of temporal data in ArcGIS 9.4 using the new "time slider."

In his First Law of Geography, noted geographer and cartographer Waldo Tobler states, "Everything is related to everything else, but near things are more related than distant things."

GIS professionals are well versed in visualization of spatial relationships and dependencies, of the proximity of near things and distant things, as in things you can measure with a ruler or with mile markers. But often when studying geography and looking for relationships and dependencies, equally important is proximity in time, as in something that can be measured with a watch or calendar.

Pioneering environmental planner Ian McHarg is widely known in the GIS community as the "discoverer" of overlay theory, the base theory behind GIS. Another of McHarg's discoveries—perhaps lesser known, but equally important—is chronology, or the placing of geographic layers in chronological sequence to show relationships, dependencies, and causation through time. "We found the earliest events, mainly of geological history, had pervasive and influential effects, not only on physiography, soils, and vegetation, but also on the availability of resources," McHarg states, describing an environmental planning study in the 1960s, in A Quest for Life. He calls his discovery of chronology—the order or sequence of features through time—". . . a most revelatory instrument for understanding the environment, diagnosing, and prescribing," a construct that leads to a deeper understanding of structure and meaning in the landscape.

Charles Joseph Minard's 1869 flow map of Napoleon's 1812 Russian campaign is a classic example of spatiotemporal visualization (Image Source: Wikimedia Commons).

Chronology is enabled by temporal data. Temporal data is data that specifically refers to times or dates. Temporal data may refer to discrete events, such as lightning strikes; moving objects, such as trains; or repeated observations, such as counts from traffic sensors.

Depicting spatial change over time is a four-dimensional problem, and visualizing temporal phenomena on a two-dimensional map has always been a challenge. The simplest approach is the map series, where individual maps of geographic conditions at certain points in time are presented individually, in chronological order.

Other inventive methods of visualizing change over time and space include creative symbolization, such as in Charles Joseph Minard's famous map of Napoleon's march across Russia.

Temporal GIS is an emerging capability for integrating temporal data with location and attribute data, enabling temporal visualization and ultimately temporal analysis. Visualizing change on a computer screen in a GIS environment may give the viewer more options, but it is still a challenge. A simple yet highly effective method of visualizing time in GIS is through animation—displaying a series of maps in rapid succession on the screen.

A creative method of representing temporal datasets in GIS developed by the Earth and Environmental Science Division at Los Alamos National Laboratory (Esri Map Book, Volume 19).

"The eye and brain are enormously efficient at detecting patterns and finding anomalies in maps and other visual displays," says Michael Goodchild of the University of California, Santa Barbara. "GIS works best when the computer and the brain combine forces and when GIS is used to augment human intuition by manipulating and displaying data in ways that reveal things that would otherwise be invisible." Building a robust temporal capability into GIS provides the human eye and brain with powerful visual tools to help determine the reasons why things happened in space-time. It is also key to modeling and predicting things that might happen in the future.

The new time-aware functionality in ArcGIS 9.4 lets you

• Create and manage time-based data.
• Display and animate temporal datasets.
• Publish and query temporal map services.

The user interface in ArcGIS 9.4 lets you set time properties for one or more layers.

ArcGIS 9.4 makes temporal mapping simple and easy; enables temporal data management, exploration, and visualization; and creates a strong foundation upon which sophisticated temporal geoprocessing tools and workflows can be built in the future. As McHarg states in To Heal the Earth, "Processes, laws, and time reveal the present." And once we have the tools and techniques in place to fully grasp how the past has created the present, we can use these same tools and techniques to shape our future.