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This paper describes the methods used to produce accounts for the recreational value of Natura 2000 areas in Flanders, Belgium. First, a biophysical account of recreation supply and demand is compiled and mapped. Demand is based on data for green visits per year per inhabitant and covers both recreation and nature-based tourism. It distinguishes local walking trips, local cycling, recreation trips with pre-transport and visits by tourists. The number of green visits is based on a combination of yearly statistics (for tourism, day trips) and irregular surveys (for local visits). The supply account is based on modelling predicted visits. The annual visits per inhabitant are attributed to ecosystems using a green visit prediction model that uses the extent and condition accounts related to availability of green-blue areas, accessibility, the attractive potential of landscapes for informal recreation (extent and condition accounts), residence and distance decay functions for different recreation types.Potential destinations include a wide range of green infrastructure, such as parks, forests, natural and agricultural areas and blue spaces (waterside and coastal natural areas). The attractiveness of landscapes is mainly based on an empirical study (choice experiment) in Flanders on people’s preferences for landscape features complemented by evidence from literature.The monetary accounts are preliminary, as there are unsufficient data available for Flanders to estimate the total value for the wide range of recreation types (from local walking and biking to tourism). Especially, data are missing to model travel and time costs for local visits (walking and biking), that account for a large share of total visits in Flanders. It should be noted that, for most visits, apart from nature-based tourism, valuation cannot be based on income fees or parking costs because, in Flanders, visits and parking are free.As unsufficient data are avaible to estimate travel and time costs in detail, we used Flemish data on average expenditure per visit per recreational type as a proxy. We discuss the limits of this preliminary approach and suggest further steps.In the results session, we discuss the implementation of the model to estimate the predicted visits to parts of the Natura2000 areas in Flanders in 2016 and 2018. As different land-uses are strongly interwoven in Flanders, these areas include a wide range of different land-uses and also areas close to residence used for local walking and biking.The differences between 2016 and 2018 illustrate how the model of predicted visits allows us to cope with land-use changes and improved quality and attractiveness of the landscapes in Natura2000 areas.

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