This paper assesses the contribution of the Ecological Footprint as a method for estimating the environmental impact of festivals. It responds to calls for more rigorous methods to assess the environmental impacts of festivals, and contributes towards providing festival organisers and policy-makers with a more balanced evaluation of their outcomes. This paper focuses on the 2012 Hay Festival of Literature and Arts (Wales, United Kingdom), and describes how the Ecological Footprint was used to calculate the environmental impact of its visitors. It also considers the potential value of the Ecological Footprint as a method for evaluating alternative strategies designed to improve the environmental sustainability of festivals. The paper demonstrates that Ecological Footprint analysis can provide valuable information for festival organisers and policy-makers on factors influencing the scale of a festivals' environmental impact, and the types of strategies needed to reduce the effect of visitor travel.

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Betweenness is a measure long used in spatial network analysis (SpNA) to predict flows of pedestrians and vehicles, and more recently in public health research. We improve on this approach with a methodology for combining multiple betweenness computations using cross-validated ridge regression to create wide-scale, high-resolution transport models. This enables computationally efficient calibration of distance decay, agglomeration effects, and multiple trip purposes. Together with minimization of the Geoffrey E. Havers (GEH) statistic commonly used to evaluate transport models, this bridges a gap between SpNA and mainstream transport modeling practice. The methodology is demonstrated using models of bicycle transport, where the higher resolution of the SpNA models compared to mainstream (four-step) models is of particular use. Additional models are developed incorporating heterogeneous user preferences (cyclist aversion to motor traffic). Based on network shape and flow data alone the best model gives reasonable correlation against cyclist flows on individual links, weighted to optimize GEH (r 2 D 0.78, GEH D 1.9). As SpNA models use a single step rather than four, and can be based on flow data alone rather than demographics and surveys, the cost of calibration is lower, ensuring suitability for small-scale infrastructure projects as well as large-scale studies.