ABSTRACT
In Chapter 9, formula (9.3) expressed fitness-for-use of analytical outputs as a function of model, data and professional where each of these is a set of entities. Throughout this book we have been progressively looking at the mapping:
(10.1)
and more specifically:
where D = set of domain inputs, 91 = set of real decisions, u = uncertainty. We have looked in Chapter 8 at the issues surrounding data uncertainties
and the evolving strategies for knowing and reducing the level of uncer tainty in spatial data and the analytical products of GIS. In Chapter 9, we considered a range of issues in model uncertainty and, again, the evolving strategies for knowing and reducing the level of uncertainty in the products of GIS and environmental simulation modelling. But as we saw from equa tion (9 .3 ), even with the best in the world there will still be some residual uncertainty s. But having got to this stage, a decision needs to be made by somebody - is there a problem or isn’t there, should something be done about it and if so what, is it technically the most appropriate solution, will the majority agree with it, how much is it going to cost, can we afford it, should we afford it and does it represent value for money? This typifies the decision space that needs to be explored and navigated. Many GIS analysts and professional modellers may well say it is not their decision, they just ascertain and present the facts as they see them. But as we discussed in Chapter 5, there has to be communication with the policy makers and the public in an iterative process that should ideally bring about an informed consensus. Bellamy et al. (1999), for example, have emphasised the politi cal and social context of environmental decision-making requiring an inclu sive process of collaboration and participation of scientists, professionals and stakeholders. If the level of propagated uncertainty to is high, one
policy option is to continue improving the level of knowledge about risks so that a policy decision on whether to intervene or not can eventually be taken (Figure 10.1). This means that GIS analysts and professional mod ellers should be honest in giving information about the limitations and uncertainties of their analytical products (Rejeski, 1993).
