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Record |
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Author  |
Lehto, C.; Hedblom, M.; Ockinger, E.; Reinus, T., |
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Title |
In search of a human habitat: using machine learning to explore the role of landscape characteristics in human outdoor recreation |
Type |
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Year |
2021 |
Publication |
The 10th MMV Conference: Managing outdoor recreation experiences in the Anthropocene – Resources, markets, innovations |
Abbreviated Journal |
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Volume |
MINA fagrapport |
Issue |
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Pages |
32-33 |
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Keywords |
MMV10 |
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Abstract |
As the importance of outdoor recreation increasingly has been recognized due to its positive effect on human well-being and health there has been a renewed focus on how to ensure that the natural and cultural landscape can produce sufficient recreational opportunities. This is especially true in urban environments, where high land use pressure due to urbanisation often has lead to the loss of green space. To ensure that the managed landscape can supply recreational opportunities requires an understanding of what landscape characteristics (such as type and composition of land cover, topology and heterogeneity) are drivers of different kinds of outdoor recreation. Previous research in the field has to a large degree focused on establishing preferences of different kinds of environments e.g. by showing people photo- graphs and asking questions (Gundersen and Frivold 2008); recently an increasing number of studies have been employing Public Participatory GIS-approaches to collect large amounts of data on human landscape usage (e.g Korpilo, Virtanen, and Lehvävirta (2017)). Still, most such studies are linked to specific areas (e.g. a single national park) or only looking at specific features (e.g. forest type, openness, heterogeneity). |
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Call Number |
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Serial |
4211 |
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