High-Tech Systems to Support Spatial Thinking
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.