We review the literature regarding the aggregation of benefit value estimates for nonmarket goods. Two case studies are presented through which we develop an approach to aggregation which applies the spatial analytic capabilities of a geographical information system to combine geo-referenced physical, census and survey data to estimate a spatially sensitive valuation function. These case studies show that the common reliance upon political rather than economic jurisdictions and the use of sample mean values within the aggregation process are liable to lead to significant errors in resultant values. We also highlight the fact that for resources with use values then we should expect overall values to reduce with increasing distance from such sites, but that changes in the choice of welfare measure will determine whether such 'distance decay' is to be expected within values stated by those who are presently non-users. The paper concludes by providing recommendations for future improvements to the methodology. (c) 2006 Elsevier B.V. All rights reserved.