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Title: Leveraging the value of crowdsourced geographic information to detect cultural ecosystem services
Author: Gliozzo, Gianfranco Antonino
ISNI:       0000 0004 7429 1883
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2018
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Within ecological research and environmental management, there is current focus on demonstrating the links existing between human well-being and nature conservation. There is a need for better understanding how and why people value certain places over others. At the same time, there is a lack of consolidated methodologies, and limited experimentation in the detection of places connected to the immaterial benefits we get from nature. Those benefits are termed Cultural Ecosystem Services (CES). This research analyses the potential of Crowdsourced Geographic Information (CGI) to support the detection of CES with large scale insights derived from the analysis of digital cultural practices. CGI is produced through social media, in situations where individuals choose to share content. Therefore, a CGI project is often the expression of a community of interest and different projects have different supporting communities with different demographics and cultural profiles. The research combines multiple projects pertaining to three different categories of CGI to avoid focusing only on a community or on a digital cultural practice. Using ecological and social considerations, this thesis contributes to the evaluation of such projects as potential analytical tools for CES research. The degree of appreciation of a specific place is derived from the number of people creating, sharing, or refining the information about it. The sequence of decisions and actions that leads to the sharing of information leaves digital proxies of spatial preferences, with people sharing specific information considering the place not only “worth visiting” but also “worth sharing”. Using south Wales and London as case studies, we demonstrate how the analysis of CGI can be included in methodologies used to detect CES. These results highlight how the inclusion of CGI, can be very effective in addressing some of the current priorities in conservation. It could potentially be used for better prioritisation, planning and management of natural and cultural resources towards a more sustainable development.
Supervisor: Haklay, M. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available