Editing Geographic information system (section)

===Adding the dimension of time===
<!--This section is linked from [[Historical geographic information system]] and [[Time geography]] ([[MOS:HEAD]])-->
{{See also|Historical geographic information system|Time geography}}
The condition of the Earth's surface, atmosphere, and subsurface can be examined by feeding satellite data into a GIS. GIS&nbsp;technology gives researchers the ability to examine the variations in Earth processes over days, months, and years through the use of cartographic visualizations.<ref>{{cite journal |last1=Monmonier |first1=Mark |title=Strategies For The Visualization Of Geographic Time-Series Data |journal=Cartographica: The International Journal for Geographic Information and Geovisualization |date=1990 |volume=27 |issue=1 |pages=30–45 |doi=10.3138/U558-H737-6577-8U31}}</ref> As an example, the changes in vegetation vigor through a growing season can be animated to determine when drought was most extensive in a particular region. The resulting graphic represents a rough measure of plant health. Working with two variables over time would then allow researchers to detect regional differences in the lag between a decline in rainfall and its effect on vegetation.

GIS&nbsp;technology and the availability of digital data on regional and global scales enable such analyses. The satellite sensor output used to generate a vegetation graphic is produced for example by the [[advanced very-high-resolution radiometer]] (AVHRR). This sensor system detects the amounts of energy reflected from the Earth's surface across various bands of the spectrum for surface areas of about {{Convert|1|km2|sqmi|abbr=on}}. The satellite sensor produces images of a particular location on the Earth twice a day. AVHRR and more recently the [[moderate-resolution imaging spectroradiometer]] (MODIS) are only two of many sensor systems used for Earth surface analysis.

In addition to the integration of time in environmental studies, GIS is also being explored for its ability to track and model the progress of humans throughout their daily routines. A concrete example of progress in this area is the recent release of time-specific population data by the [[U.S.&nbsp;Census]]. In this data set, the populations of cities are shown for daytime and evening hours highlighting the pattern of concentration and dispersion generated by North American commuting patterns. The manipulation and generation of data required to produce this data would not have been possible without&nbsp;GIS.

Using models to project the data held by a GIS&nbsp;forward in time have enabled planners to test policy decisions using [[spatial decision support system]]s.