An integrated framework for assessing uncertainties in environmental data, illustrated for different types of data and different complexities of problem

Research output: Chapter in Book/Report/Conference proceedingAbstract

Abstract

Understanding the limitations of environmental data is essential both for managing environmental systems effectively and for encouraging the responsible use of scientific research when knowledge is limited and priorities varied. Explicit assessments of data quality, and the uncertainties associated with data quality, are important in this context. Using a combination of quantitative and qualitative techniques for assessing probabilities, and acknowledging the importance of possibilistic techniques where probabilities are inappropriate, an integrated methodology is presented for handling uncertainties about environmental data. The methodology is based on a three-fold distinction between the magnitudes of uncertainty in data (and the ancillary information, such as data ‘support’, required to interpret this correctly), the sources of uncertainty in data, and the ‘goodness’ of an uncertainty model (critical self-reflection). In particular, emphasis is placed upon the conditions and parameters required for estimating quantitative probability models, for which a number of data categories are introduced, and on the application of simplifying assumptions to quantitative models of uncertainty. The methodology is illustrated with examples for different types of environmental data, including a discrete time-series, a categorical spatial variable and a continuous space-time variable, and for different complexities of problem. Here, three scenarios are introduced, including an ‘information-rich’ case, where probabilistic estimates of uncertainty are easily made, an ‘intermediate case’, and an ‘information-poor’ case, where the perceived quality of data, as well as the ‘goodness’ of an uncertainty model, becomes more case (person) dependent.
Original languageEnglish
Title of host publicationAccuracy 2004
EditorsH.T. Mowrer, R. McRoberts, P.C. van Deusen
Place of PublicationPortland, Maine U.S.A.
PublisherR.E. McRoberts
Pages26
Publication statusPublished - 2004
EventThe sixth int. symp. on spatial accuracy as. in nat. res. and env. sc. and the fifteenth annual conf. of TIES, Portland, 28 June - 1 July 2004 -
Duration: 28 Jun 20041 Jul 2004

Conference

ConferenceThe sixth int. symp. on spatial accuracy as. in nat. res. and env. sc. and the fifteenth annual conf. of TIES, Portland, 28 June - 1 July 2004
Period28/06/041/07/04

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    Brown, J., & Heuvelink, G. B. M. (2004). An integrated framework for assessing uncertainties in environmental data, illustrated for different types of data and different complexities of problem. In H. T. Mowrer, R. McRoberts, & P. C. van Deusen (Eds.), Accuracy 2004 (pp. 26). Portland, Maine U.S.A.: R.E. McRoberts.