A term which has subtle differences in meaning according to its academic context; F. Knight (1921) distinguishes between risk (randomness with knowable probabilities) and uncertainty (randomness with unknowable probabilities). The measurement of uncertainty is imperative for the production of knowledge; as Goodchild in S. Shekhar and H. Xiong (2008) notes: ‘all geographic information leaves some degree of uncertainty about conditions in the real world’. The two broad questions of uncertainty in geography are the estimation of experimental error, and the question of ‘how we come to know’.
The first theme is less problematic: D. W. Hubbard (2007) provides useful guidelines for assessing the value of information, and Schroeder (2007) Geogr. Analysis 39, 3, for example, outlines a model used to assess uncertainty in analyses of US census tracts, using aggregated data from incompatible zonal systems.
The second theme relates to the production and status of ‘knowledge’. ‘In assessing uncertainty, there is a need to question both “what is known” in geography, where knowledge and reflections about the “status” of knowledge differ between individuals and groups of scientists, and “how we came to know”, where knowledge and uncertainty are closely related to research tradition and practice’ (Brown (2004) TIBG 29, 3). Reed and Peters (2004, ACME 31, 1) draw on contemporary systems ecology to design research practices which ‘embrace the uncertainty and partiality of knowledge creation’—one of their wise practices is ‘preparing for surprise’. See also Ekinsmyth et al. (1995, Area 27, 4) on the uncertainty of economic geography, G. Foody and P. Atkinson’s e-book on GIS and uncertainty, Murphy et al. (2006) Area 38, 1 on uncertainty and climate change, and Hunsaker et al. eds (2001) on spatial uncertainty in ecology.