Geospatial Data Systems
GIS and remote-sensing analysis systems (e.g., ArcView, MapInfo, Idrisi, Erdas, Imagine) provide advanced data management and analysis capabilities along with the means to generate maps, graphs, surfaces, and tables. They support a wide variety of spatial data types, have elaborate tools for geo-registering and integrating data, and typically provide high-quality cartographic tools. Their major drawbacks are poor support for the vertical dimension, poor support for the time dimension, complexity of the application program interfaces (APIs), and limited support for spatializing nonspatial information.
Geoscience analytical systems (e.g., Surpac, Vulcan, Micromine, Fractal Technologies), which are commonly used to manage geological exploration and mining activities, provide support for spatial thinking. Some of these products represent data in three dimensions, as opposed to two. Some of them explicitly model the change in a region through time (e.g., due to erosion, mining activities, etc.). Typically, these systems have strong analysis and geostatistical capabilities, but they are more limited cartographically than GIS.
Computer-assisted design systems (e.g., AutoCAD, MicroStation), which have an engineering and architectural heritage, provide strong graphics capabilities. They offer good support for vector-based data, complete support for the third dimension, and a high level of interoperation (data exchange) between systems. They offer no support for raster data or for geographic projections. They have limited spatial analysis and statistical capabilities.
Mathematical and Statistical Analysis Systems
Mathematical and statistical analysis systems (e.g., Mathematica, Maple) were developed to provide integrated environments for the analysis and transformation of scientific data. Consequently, they offer a strong selection of mathematical and statistical tools. Recently, they have been augmented with graphing tools that allow for the spatialization and visualization of data. Typically, they are limited in their ability to handle explicitly geographic data and to support high-quality cartographic output.
high-tech tools for supporting spatial thinking. The committee identifies the types of tools, their functions, and their strengths and weaknesses as supports for spatial thinking and shows how these systems are converging toward common goals, driven primarily by user expectations. Section 7.3 provides an introduction to the nature and functions of GIS. Section 7.4 assesses the current status of GIS, especially with respect to K–12 education.
A number of software tools have been developed to represent and manipulate objects in geographical space or in some other information space via spatialization. In the geospatial context, there are eight sets of tools: GIS and remote-sensing analysis systems; geoscience analytical systems; CAD systems; mathematical and statistical analysis systems; production graphics environments; animation environments; information visualization systems; and concept mapping tools (see Appendix E for web addresses that provide details of these tools). (There are also high-tech systems for spatial thinking in fields as diverse as protein analysis, medical imaging, and mapping star systems.) Each one of the eight high-tech tools offers different capabilities. For example, GIS and related satellite-based systems, such as GPS, have revolutionized geospatial data collection, analysis, and display.
Box 7.1 provides a description and assessment of these high-tech tools, which are divided into