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Model simulations of residential segregation have shown that even modest levels of social homophily (or wishing to live near residents with similar social characteristics) gives rise to distinct spatial patterns of residential segregation. However, this proposition has been contested where social homophily is modest. This paper contrasts two explanations for urban sociospatial patterns (socioeconomic and demographic spatial patterns) in a region where social homophily is modest-South East Queensland (SEQ). The research question is whether sociospatial patterns are better explained by social homophily or by structural homophily. In other words, are they better explained by residents wishing to live in neighborhoods with similar people (social homophily), or by residents with similar social characteristics finding similar neighborhood physical attributes important, and thus moving to neighborhoods with similar people (structural homophily). SEQ residents were asked how important various reasons were in choosing their neighborhood. The survey data were linked to neighborhood social characteristics from census data with the aid of geographic information systems. Six neighborhood social characteristics in SEQ were investigated. Social homophily explained a small, though statistically significant, level of spatial variation in socioeconomic and ethnic (non-Western) environments. However, it did not explain any variation in the other four neighborhood social characteristics which related to household structure: that is, younger nonnuclear household environments; nuclear family environments; and older nonnuclear household environments, or disadvantaged environments. Moreover, structural homophily explained much more variation than did social homophily in all six neighborhood social characteristics. In regions such as SEQ, spatial patterns can largely be explained by structural homophily. Thus, modest levels of social homophily are not necessarily important in explaining sociospatial patterning. [ABSTRACT FROM AUTHOR]

Geographic information systems (GIS) offer attractive tools for modelling recreational behaviour. In this paper GIS is combined with a discrete choice modelling approach to investigate the importance of landscape attributes for determining forest recreational choices. A new large Danish national dataset (28 947 recreational trips) is used in conjunction with an area information system and information on other site attributes to estimate a recreational choice model. A wide set of landscape characteristics influencing recreational choice is identified. These are the size of the forest patch and adjacency or distance to other land-cover types. The area of the forest patch was found to have a positive marginally declining effect. Adjacency to other seminatural areas was found to have a positive effect. The results show that the parameter estimates depend critically on the choice-set specification and that the size of the choice set needs to be considerably larger than previous research suggests. [ABSTRACT FROM AUTHOR]