Abstract
Integrating cultural dimensions into the ecosystem service framework is essential for appraising non-material benefits stemming from different human-environment interactions. This study investigates how the actual provision of cultural services is distributed across the landscape according to spatially varying relationships. The final aim was to analyse how landscape settings are associated to people’s preferences and perceptions related to cultural ecosystem services in mountain landscapes. We demonstrated a spatially explicit method based on geo-tagged images from popular social media to assess revealed preferences. A spatially weighted regression showed that specific variables correspond to prominent drivers of cultural ecosystem services at the local scale. The results of this explanatory approach can be used to integrate the cultural service dimension into land planning by taking into account specific benefiting areas and by setting priorities on the ecosystems and landscape characteristics which affect the service supply. We finally concluded that the use of crowdsourced data allows identifying spatial patterns of cultural ecosystem service preferences and their association with landscape settings.
Original language | English |
---|---|
Pages (from-to) | 237–248 |
Number of pages | 12 |
Journal | Ecological Indicators |
Volume | 64 |
Early online date | 21 Jan 2016 |
DOIs | |
Publication status | Published - May 2016 |
Keywords
- Non-material ecosystem benefits
- Cultural service preferences
- Social perceptions
- Photoseries analysis
- Spatially varying relationships
- Land use planning
- Recreational choice
Fingerprint
Dive into the research topics of 'Crowdsourcing indicators for cultural ecosystem services: a geographically weighted approach for mountain landscapes'. Together they form a unique fingerprint.Profiles
-
Urska Demsar
- School of Geography & Sustainable Development - Senior Lecturer, Director of Postgraduate Studies (Research)
- Bell-Edwards Geographic Data Institute
- Environmental Change Research Group
Person: Academic, Research Support