Public participation GIS versus geolocated social media data to assess urban cultural ecosystem services: Instances of complementarity
Introduction
Cultural ecosystem services (CES), defined as “all the non-material, and normally non-rival and non-consumptive, outputs of ecosystems (biotic and abiotic) that affect physical and mental states of people” (Haines-Young and Potschin, 2018), are important components of human well-being. They include spiritual, educational, inspirational, aesthetic, heritage, sense of place, recreational (Cheng et al., 2019, Haines-Young and Potschin, 2018, MA, 2005, Plieninger et al., 2013), and discovery services (Bieling, 2014, Fish et al., 2016). CES are unique in that they are rarely substitutable by technological means, making them nearly irreplaceable (Plieninger et al., 2013). The appreciation and awareness of the CES provided by urban green and blue areas (such as urban forests and parks, lawns, gardens, street trees, wetlands, ponds, lakes, rivers) have also been documented to increase the public support for environmental protection, thus potentially playing a significant role in defining and strengthening nature conservation policies (Andersson et al., 2015, Daniel et al., 2012, Gobster et al., 2007).
To support open space planning and management, it is important to understand which sites and what landscape features provide opportunities for CES and how these are distributed spatially within sites. The assessment of CES generally entails socio-cultural, economic or ecological (i.e., those considering landscape potential to provide cultural services) approaches which allow for gathering information on users’ perceptions, preferences, values, attitudes, and beliefs (Katz-Gerro and Orenstein, 2015, Plieninger et al., 2013). Despite a growing body of research, assessing CES remains a challenge due to the subjective and immaterial character of these services (Small et al., 2017). Socio-cultural methods to assess this category of services include: Delphi Survey (Edwards et al., 2012); Q Methodology (Pike et al., 2015); photo-based methods (Williams and Cary, 2001); spatial assessments based on geolocated data derived from social media (Donahue et al., 2018, Hamstead et al., 2018, Keeler et al., 2015, Langemeyer et al., 2018, Sinclair et al., 2019); GPS-based activity data gathered through ad-hoc apps (Heikinheimo et al., 2020); questionnaire-based surveys, interviews and focusing (Bieling and Plieninger, 2013, Brown et al., 2014, Brown and Weber, 2013, Fish et al., 2016, Norton et al., 2012, Teff‐Seker and Orenstein, 2019); focus group discussions (Orenstein et al., 2015, Stålhammar and Pedersen, 2017); and public participation or participatory GIS (PPGIS or PGIS) (Brown and Fagerholm, 2015, Brown and Kyttä, 2014, Brown and Weber, 2013, Bryan et al., 2010, Plieninger et al., 2013, Raymond et al., 2009). A general review and comparison of these methods is presented by Cheng et al. (2019).
In this paper, we focus on two of these methods: PPGIS, a specific type of active participation method involving a spatial component and used to enhance public involvement to inform land use planning and management (Brown and Kyttä, 2014); and a spatial assessment based on geotagged photographs from social media. Our aim is to compare their potential to assess CES and derive considerations regarding their substitutability, supplementarity or complementarity. The rationale behind this comparison is that social media-based assessments facilitate work with large amounts of data available for broader spatial and temporal scales and at relatively low cost compared to methods that entail active participation of respondents. Active participatory methods are generally more resource and labor intensive, however social media-based assessments are recent and little is know about their potential biases.
The extent to which social media-based assessments can substitute, supplement or complement PPGIS in the assessment of CES, and vice versa, is an expanding research subject (Crampton et al., 2013, Figueroa-Alfaro and Tang, 2017, Heikinheimo et al., 2017, Ilieva and McPhearson, 2018, Richards and Tunçer, 2018). A handful of recent case study-based comparative assessments are available (Heikinheimo et al., 2020, Komossa et al., 2020, Levin et al., 2017, Moreno-Llorca et al., 2020, Muñoz et al., 2020). The outcomes of this initial research on the topic indeed suggest that the social media method could contain numerous potential biases (such as poor representativeness of the different communities of users of green and blue areas – see Section 1.2) that have not yet been extensively assessed.
The specific objectives of this study are to: (1) identify strengths and weaknesses of the two methods to capture qualitative information related to landscape features of interest and CES; (2) identify and characterize potential biases of social media and PPGIS methodologies; (3) assess the substitutability, supplementarity or complementarity of the two methods, particularly with respect to the characteristics of the qualitative information conveying user preferences. To these ends we analyze: (1) the relative importance of seven categories of landscape features in co-creating the cultural value of seven green and blue spaces of the city of Haifa, Israel, as assessed with the two methods; and (2) the intensity of different types of CES enjoyed by users in each area, as captured by the two methods. The seven green and blue spaces of Haifa were selected for their diversity of landscape features potentially of interest, as detailed in Section 3.1.
Section snippets
CES assessments based on PPGIS
PPGIS refers to “spatially explicit methods and technologies for capturing and using spatial information in participatory planning processes” (Brown and Fagerholm, 2015, p. 119). More specifically, PPGIS is a mapping exercise which, based on (collective or individual) people's knowledge, experiences, and perceptions, enables the researcher to define geographically and characterize user’s cultural values or landscape features of interest. It is a place-based approach which allows to capture
Study area
This study focuses on the green and blue areas of Haifa, Israel’s third largest city. Haifa is in the northwest of the country, on the coast of the Mediterranean Sea (32°49′0″N 34°59′0″E) (see Fig. 1), and hosts about 280,000 inhabitants (CBS, 2018). The city’s climate is typically Mediterranean, with warm summers and mild, rainy winters. Average temperatures range between 8.7 ℃ (in February) and 31.4 ℃ (in August), with high summer humidity levels. Precipitation averages 630 mm/year, almost
Interest in each site as estimated with the two methods
Table 3 presents the number of users that uploaded photographs for each site and the number of times each site was mentioned during the interviews. Based on these data, Fig. 2 shows public interest in each site, as it emerged from the two methods. The Bahai Gardens stood out in this analysis, being associated with a substantially larger number of social media users than any other site but being mentioned only once in the interviews. The popularity of the Bahai Gardens in the social media data
Discussion
This paper investigates and compares the application of two socio-cultural methods for the assessment of CES in seven green and blue sites of the city of Haifa: PPGIS, which relies on in-depth discussions with respondents regarding the identification and characterization of green and blue sites of cultural and recreational interest, conducted with a relatively small sample of participants; and social media-based assessment, which relies on analysis of a relatively large number of geolocated
Conclusions
We assessed the features of the landscape which give value to seven green and blue areas of the city of Haifa as well as the CES enjoyed by visitors of these areas, by applying two different methods: PPGIS and geolocated social media-based assessment. We conclude that the two methods are complementary in many instances. For instance, we observe that, while it is possible to adequately identify preferences through both methods, the social media-based approach is particularly suitable to
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
We thank Ronit Cohen for her work on Figure 1. This research is supported by a grant to Daniel E. Orenstein from the Israel Science Foundation, Israel (Grant No. 1835/16). Yaella Depietri was partially funded by a Zeff Post-Doctoral Fellowship at the Technion.
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