Geoscience Reference
In-Depth Information
Geographic Information Systems
The GIS have become indispensable tools for geoscientific exploration, commerce,
and for decision making in environmental and social sciences (Morss, 2002). In gen-
eral, GIS involves a broad array of computer tools for mapping, and managing geo-
graphically referenced data, and for spatial analysis. Regardless of the application, all
the geographically related data can be input and prepared in a GIS such that users can
display the specific information of interest, or combine data contained within the sys-
tem to produce additional value-added information that might help answer a specific
problem. The extraordinary gains in computer performance over the past 2 decades
have seen a parallel growth in GIS applications. These applications have not only been
growing in number but also in their diversity. An important reason for the proliferation
of GIS use is that it provides a convenient framework for multidisciplinary analysis
and synthesis, which is becoming increasingly important as researchers explore the
frontiers of science. As the demand for innovative GIS applications, services, and
know-how grows, GIS is expected to play a pivotal role in shaping the cyberinfrastruc-
ture and data services in the geosciences.
The GIS's powerful capability is to integrate spatially referenced data from dis-
parate sources into a single environment. An important application of GIS is linking
remotely sensed data from a variety of instruments with various socioeconomic data
and biophysical datasets in a common framework. For example, GIS can be used to
integrate radar, lightning, and satellite data with land use and population data to study
how deforestation and urban development affects the occurrence and frequency of for-
est fi res. The ability to integrate observations and model data from several geoscience
disciplines with socioeconomic and biophysical data in a common framework permits
not only multidisciplinary analysis and synthesis, but also provides a pathway to ap-
proach geoscience problems and processes from an ESS perspective.
While the atmospheric science community has a rich tradition in developing spe-
cialized scientifi c analysis and visualization tools, which can be loosely characterized
as SIS, to process, analyze, and display atmospheric data, the fi eld has only recently
begun to embrace the use of GIS in education and research. One reason for the slow
adoption of GIS by the atmospheric science community is that current GIS frame-
works, due to their limitations in data models and lack of conceptual and physical
interoperability of proprietary GIS applications, are not suited to the management and
analysis of dynamic, multidimensional atmospheric datasets. Research is needed to
identify new frameworks and methodologies to integrate database constructs of GIS
with SIS datasets. For instance, combining real-time and forecast weather informa-
tion with GIS databases of population and infrastructure has signifi cant potential for
greatly improving weather related decision support systems. The utility and integra-
tion of “off-the-shelf” GIS tools and scientifi c applications in the context of climate
change and disaster research, mitigation and response should also be of high priority in
the development of future cyberinfrastructure in the atmospheric sciences.
The trend of GIS applications shifting from operational support tools to strategic
decision support systems, as described above, is followed by the demand for the in-
corporation of more powerful analysis techniques. It is into this context that the need
