Journal of Environmental Management (1997) 51, 373–389 Improving Benefit Transfer Demand Functions: A GIS Approach Andrew A. Lovett, Julii S. Brainard* and Ian J. Bateman School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ, United Kingdom Received 10 October 1996; accepted 27 July 1997 Methodologies for transfer of non-market, natural resource recreation benefits are an active research topic. This arises because of the appeal of modelling the impacts of possible changes in site quality or benefits at unsurveyed sites. However, successful benefit transfer must necessarily rely on development of reliable visitor demand functions that incorporate travel time, demographic and substitute factors. Previous efforts to include all of these elements in a single arrivals model are rare. By integrating data from numerous sources within a geographical information system (GIS) we have developed a model to predict the number of visitors to a recreational woodland in eastern England. Variables were classified into discrete groups that were combined into comparatively homogeneous zones from which to calculate visit rates. Poisson regression techniques were then applied in a stepwise procedure to assess the influence of each determinant. Our analysis highlighted both substantial promise and some caveats in using GIS for future benefit transfer work.  1997 Academic Press Limited Keywords: benefit transfer, geographical information systems, travel cost method, woodland recreation, Poisson regression. 1. Introduction The economic literature is replete with studies concerning the valuation of non-market, natural resource-based, recreational resources. The research can broadly be divided into expressed preference techniques such as contingent valuation (see Bateman and Turner, 1993; Carson and Mitchell, 1993; Willis and Garrod, 1993), or revealed methods, including travel cost analysis and hedonic pricing (e.g. Mendelsohn et al., 1992; Bateman, 1993; Garrod and Willis, 1993; Bockstael, 1995). Expressed preference methods ask consumers to assess their own welfare surplus, while revealed techniques use actual costs to estimate recreational benefits. When applied to outdoor recreation, both approaches tend to rely on the collection of data for and relevant to specific, solitary sites, and in general, the results have restricted applicability for other locations. * Corresponding author. 0301–4797/97/120373+17 $25.00/0/ev970150  1997 Academic Press Limited