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See detailOn the distance travelled for woodland leisure via different transport modes in Wallonia, south Belgium
Li, Sen; Colson, Vincent; Lejeune, Philippe ULg et al

in Urban Forestry and Urban Greening (2016), 15

Based on an extensive survey of woodland visitors in Wallonia, south Belgium, we examined a widerange of individual-, residential- and destination-level variables for their associations with the ... [more ▼]

Based on an extensive survey of woodland visitors in Wallonia, south Belgium, we examined a widerange of individual-, residential- and destination-level variables for their associations with the distancetravelled for woodland leisure on foot, by bicycle and by car. For each transport mode, explanatorybivariate analyses were conducted firstly to identify potential correlates of the distances travelled. Then,cross-classified multilevel analysis was performed to build estimation models for the trip distance. Theresults showed that, amongst the multilevel variables selected, walking trip distance was only associatedwith individual trip behaviour, while cycling and car-borne trip distance could also be associated withindividual socio-economic profile as well as a large range of residential and destination attributes onland use, land cover and visitor support services. The final estimation model for (i) walking trip distanceincluded trip duration as the only explanatory variable, for (ii) cycling trip distance included variables ontrip duration, proportion of woodland area at residence and presence of service facilities at destination,and for (iii) car-borne trip distance included variables on trip duration, visitor’s employment status,whether the trip is on weekend or in summer, proportion of woodland area at residence and remotenessof destination from urban area. Despite being simple in form, all multilevel estimation models showa satisfactory explanatory power and a better performance than the ordinary single-level models. Ourresults add new empirical evidences on the key factors associated with the transport mode-specific traveldistance, in particular, for woodland leisure. The cross-classified multilevel analysis used in our studyprovides new methodological insights for the estimation of individual trip distance, which could benefitfuture modelling of woodland recreation demand. [less ▲]

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See detailMid-term economical consequences of roadside tree topping
Campanella, Bruno ULg; Toussaint, André ULg; Paul, Roger ULg

in Urban Forestry and Urban Greening (2009), 8

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See detailMap and determinants of woodlands visiting in Wallonia
Colson, Vincent ULg; Garcia, S.; Rondeux, Jacques ULg et al

in Urban Forestry and Urban Greening (2009)

The Walloon forest taken as a whole can be regarded as typical of a rural area, although its proximity to densely populated areas gives it a peri-urban character. It is visited by the local population as ... [more ▼]

The Walloon forest taken as a whole can be regarded as typical of a rural area, although its proximity to densely populated areas gives it a peri-urban character. It is visited by the local population as well as by tourists (including from neighboring countries). To provide spatial information on the level of Wallonia woodland visitation, a survey was conducted among managers of Forest Service districts (also called ‘‘cantonnements’’). The aim was to map the woodlands to show spatial patterns of visitation levels, and analyze them qualitatively to determine the influence factors. This map identifies regional hubs of recreation woodlands and, conversely, areas where the recreational function is much less important. The level of visitation was scaled in four levels ranging from low to very high. The mapping was supplemented with a statistical analysis of data collected from the forest managers and also from different GIS-layers (slope, hydrology, land use, etc.). An equation using the level of visitation as a dependent variable was fitted to a set of characteristics of the woodland with an ordered Logit model. The results show that type of ownership, type of forest, and recreational facilities significantly influence the level of woodland visitation. They also show that woodland visitors prefer any type of forest to mainly coniferous woodland. These results and the analysis of the map are particularly useful for developing forest policy and tourism as well as managing the forest. [less ▲]

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