National Academies Press: OpenBook

Learning to Think Spatially (2006)

Chapter: Appendix F What Is GIScience?

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Suggested Citation:"Appendix F What Is GIScience?." National Research Council. 2006. Learning to Think Spatially. Washington, DC: The National Academies Press. doi: 10.17226/11019.

Appendix F
What is GIScience?

The University Consortium for Geographic Information Science (UCGIS), a collaboration among approximately 70 academic institutions, private companies, and government agencies, and one of the more prominent manifestations of the rise of GIScience in the United States, is “dedicated to advancing our understanding of geographic processes and spatial relationships through improved theory, methods, technology, and data” ( This idea of tools in the service of science is echoed by Clarke (1997), who defines GIScience as “the discipline that uses geographic information systems as tools to understand the world.”

Yet this is only one of two competing definitions of GIScience. Goodchild (1992) defined GIScience as “the science behind the systems,” concerned with the set of fundamental questions raised by GIS and allied technologies, and Mark (2003) has provided a lengthy commentary on definitions. Thus, GIScience is the storehouse of knowledge that is implemented in GIS and makes the tools of GIS possible. GIScience may search for general principles, such as the enumeration of possible topological relationships between pairs of features by Egenhofer and Franzosa (1991), one of the most cited papers in GIScience (Fisher, 2001). It may discover faster algorithms, more efficient indexing schemes, or new ways of visualizing geographic information.

UCGIS has identified 10 “research challenges” representing a consensus on the most important long-term components of the GIScience research agenda: (1) spatial data acquisition and integration; (2) interoperability of geographic information; (3) distributed and mobile computing; (4) future and development of the spatial information infrastructure; (5) extensions to geographic representations (beyond two-dimensional, single-resolution maps); (6) cognition of geographic information and ease-of-use issues (the need to overcome the gap between human cognition and GIS if it is to be regarded by the general public as easy to use or introduced to young children); (7) scale; (8) uncertainty in geographic data and GIS-based analyses; (9) spatial analysis in a GIS environment; and (10) GIS and society (ethics, privacy).

As the science behind the systems, GIScience builds on the accumulated results of many centuries of investigation into how to describe, measure, and represent Earth’s surface. The shift to digital technology has revolutionized the older GISciences of surveying, photogrammetry, and cartography, giving new motivation to older research questions, and raising new questions related

Suggested Citation:"Appendix F What Is GIScience?." National Research Council. 2006. Learning to Think Spatially. Washington, DC: The National Academies Press. doi: 10.17226/11019.

to the greater flexibility and power of digital technologies. Moreover, the older GISciences evolved in an era of distinct, analog technologies—as long as the paper and pen of cartography had little in common with the analytical stereoplotter of photogrammetry or the theodolite of surveying, there was every reason for them to evolve separately, with separate research agendas. Today, however, all three fields have embraced digital technology wholeheartedly. They serve overlapping applications and face similar issues of representation, database design, accuracy, and visualization.

The world of geographic information has also grown more complex, as new questions have arisen that require the skills and principles of other sciences. Remote sensing, the science of Earth observation, is now an important source of geographic information with its own issues and principles. The unique problems of spatial information have begun to intrigue computer scientists, and spatial databases, computational geometry, and spatial indexing are now recognized subfields of computer science with special significance for GIScience (Liu et al., 2003; Worboys, 1995). Spatial statistics and geostatistics, recognized subfields of statistics, provide important frameworks for the study of accuracy and uncertainty in GIScience (Zhang and Goodchild, 2002), and for the development of advanced methods of spatial analysis, modeling, and visualization (Haining, 2003; Longley and Batty, 2003; O’Sullivan and Unwin, 2003). GIScience is a legitimate subfield of information science, and it is particularly attractive to information scientists because of the well-defined nature of geographic information and the comparatively advanced state of knowledge about this information type. Finally, an important section of the GIScience research agenda asks questions of interest to cognitive scientists: How are geographic knowledge and skills acquired by the human brain, and how can GIS be made more readily understood and usable by humans?


Clarke, K. C. 1997. Getting Started with Geographic Information Systems. Upper Saddle River, N.J: Prentice Hall.

Egenhofer, M. J., and R. D. Franzosa. 1991. Point-set topological spatial relations. International Journal of Geographical Information Systems 5:161–174.

Fisher, P. F. 2001. Editorial: Citations to the International Journal of Geographical Information Science: The first ten years. International Journal of Geographical Information Science 15(1):1–6.

Goodchild, M. F. 1992. Geographical information science. International Journal of Geographical Information Systems 6(1):31–45.

Haining, R. P. 2003. Spatial Data Analysis: Theory and Practice. Cambridge, U.K.: Cambridge University Press. 432 pp.

Liu, X., S. Shekhar, and S. Chawla. 2003. Object-based directional query processing in spatial databases. IEEE Trans. Knowl. Data Eng. 15(2):295-304.

Longley, P. A., and M. Batty, editors. 2003. Advanced Spatial Analysis: The CASA Book of GIS. Redlands, Calif.: ESRI Press.

Mark, D. M. 2003. Geographic information science: Defining the field. In M. Duckham, M. F. Goodchild, and M. F. Worboys, editors, Foundations of Geographic Information Science, pp. 3–18. New York: Taylor and Francis.

O’Sullivan, D., and D. J. Unwin, 2003. Geographic Information Analysis. New York: John Wiley & Sons.

University Consortium for Geographic Information Sciences (UCGIS). Available at Accessed on January 23, 2004.

Worboys, M. F. 1995. Geographic Information Systems: A Computing Perspective. London: Taylor and Francis.

Zhang, J. X., and M. F. Goodchild, 2002. Uncertainty in Geographical Information. New York: Taylor and Francis.

Suggested Citation:"Appendix F What Is GIScience?." National Research Council. 2006. Learning to Think Spatially. Washington, DC: The National Academies Press. doi: 10.17226/11019.
Page 287
Suggested Citation:"Appendix F What Is GIScience?." National Research Council. 2006. Learning to Think Spatially. Washington, DC: The National Academies Press. doi: 10.17226/11019.
Page 288
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Learning to Think Spatially examines how spatial thinking might be incorporated into existing standards-based instruction across the school curriculum. Spatial thinking must be recognized as a fundamental part of K–12 education and as an integrator and a facilitator for problem solving across the curriculum. With advances in computing technologies and the increasing availability of geospatial data, spatial thinking will play a significant role in the information-based economy of the twenty-first century. Using appropriately designed support systems tailored to the K–12 context, spatial thinking can be taught formally to all students. A geographic information system (GIS) offers one example of a high-technology support system that can enable students and teachers to practice and apply spatial thinking in many areas of the curriculum.


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