Making the Trade-Off between Decision Quality and Information Cost

As such, there is a growing emphasis upon the adoption of forAbstract mal decision-science methods to help us understand the qualA growing problem confronting users of remotely sensed imagery ity of our decisions, as opposed to the conventional standardsis whether the use of additional or different imagery to improve based approaches of the past where acceptable quality levels decision quality is actually justified by its cost. This paper disare pre-defined according to commonly used data accuracy cusses how to compare these competing factors so that an acstandards. ceptable trade-off may be made between them. The proposed Once computed, the application of decision analytical method is based on probabilistic cost-benefit analysis. The measures of uncertainty importance is relatively straightforconcept of “value of information” is introduced in a practical ward, and the use of additional information should only be case study using remote sensing to verify farmers’ declarations employed if the expected benefits to arise from using that inforfor a crop subsidy program in the European Union. Application mation are higher than the associated costs. In turn, the best of the method requires that (1) the problem at hand can be method of information acquisition for the decision to be taken represented by a decision tree, (2) the desirability of each deis the one that results in the largest positive difference between cision outcome can be expressed numerically, (3) the imagery the expected desirability of the decision outcome and the costs reveals information about the occurrence of events not under involved. This approach is valid for utility-based decision makthe decision maker’s control, and (4) the probabilities of these ing in which decisions are based on the valuation of outcomes events and the extent to which they are detectable in remotely (Morgan and Henrion, 1990, p. 25). sensed imagery can be assessed. The notion of “value of information” is probably the best-