Nature-based recreation, i.e., recreational activities involving physical and experiential interactions with natural environment [1
], is among the most relevant ecosystem services provided by green infrastructure, especially in urban contexts [2
]. It includes multiple open-air activities of different physical intensity, from walking the dog or strolling in a park, to hiking, running, and cycling in natural environments. The benefits of nature-based recreation on human health and wellbeing are manifold. Nature experience has a restorative effect, improves mental wellbeing, and reduces the risk of depression and mental illnesses [4
]. Scientific studies also provide evidence of increased cognitive abilities after enjoying nature [8
], and positive effects on the cognitive development of children [10
]. Opportunities for nature-based recreation encourage physical activity and active lifestyles, thus potentially reducing health risk factors such as obesity and cardiovascular disease [11
]. Furthermore, nature-based recreational activities can facilitate social interactions, foster empowerment, and promote social cohesion and support [13
In cities, urban parks are purposely created to offer day-to-day nature-based recreational opportunities to the population [16
]. Nonetheless, beyond urban parks, other typologies of green infrastructure in and around the city, including urban and peri-urban forests [17
], tree-lined streets [18
], peri-urban agriculture [19
], and even brownfields [20
] and abandoned areas [21
], support the variety of activities and experiences that are collectively referred to as nature-based recreation [22
]. On the other hand, the demand for nature-based recreation is also various, being affected by cultural and psychological factors at both societal and individual levels, which determine what types of activities are preferred and, ultimately, what makes a green space a suitable place for nature-based recreation [23
]. Accounting for the whole range of green spaces that support nature-based recreation and for the variety of demands expressed by the population is therefore essential to inform green infrastructure planning and management.
Providing adequate publicly-accessible green spaces for day-to-day recreational activities is, traditionally, among the main goals of urban plans [25
]. In this context, two types of indicators are commonly adopted to steer decisions: (i) per capita green area; and (ii) maximum distance—or accessibility—to a green space of defined dimension [28
]. Per capita green area is often adopted to express quantitative targets for urban green infrastructure. Examples include local policies such as in Berlin (6 m2
) and Leipzig (10 m2
), as well as national laws such as in Romania (26 m2
]. This simple indicator allows an easy benchmarking and comparison between cities (e.g., [31
]), but overlooks the spatial distribution of green spaces, which may determine mismatches between supply and demand [32
] and inequality amongst different neighborhoods and social groups [33
]. Accessibility indicators and targets related to a minimum green area to be provided to each citizen at a certain distance from home overcome these shortcomings and promote a spatially-explicit assessment focused on the individual perspective [34
]. An overview of green space standards and guidelines based on accessibility metrics promoted by national and international institutions has been recently compiled by Stessens and colleagues [35
Despite their usability, the discussed indicators show clear limitations when adopted to inform urban planning about nature-based recreation. First, they usually focus on urban parks or—at best—on few types of public green spaces, failing to capture the specific contribution of different green space typologies in supporting different nature-based recreational activities. Second, they provide a quantitative assessment limited to the ecological dimension, where factors related to people’s perceptions and desires, hence to the demand for nature-based recreation that pertains to the socio-economic dimension, are overlooked. To overcome these limitations, innovative approaches and methods analyzing nature-based recreation from an ecosystem service perspective have been recently developed and applied in a variety of contexts [36
], including urban areas [32
]. These methods assess nature-based recreation considering both the supply, which depends on the potential of different green spaces based on their typology and conditions, and the demand for the service, which depends on the context-specific preferences of the local population [42
]. Despite their growing popularity, the improvements potentially brought to urban planning decisions with respect to other, more common approaches and indicators, are yet to be measured.
This article presents a case study where the ESTIMAP-recreation model [44
] was applied to assess the potential and opportunities for nature-based recreation in the city of Trento (Italy), and then compared with traditional indicators based on the availability and accessibility to urban parks. The aim was to test how the model can be adapted to the local context and to what extent it can improve how nature-based recreation is currently addressed by urban planning. The case study, the adapted version of the ESTIMAP-recreation model, and the application process are described in Section 2
. The findings are presented in Section 3
and discussed in Section 4
. Finally, Section 5
draws some key conclusions.
2. Materials and Methods
2.1. Introducing the Case Study
Trento, provincial capital of Trentino, is a city of around 117,000 inhabitants located in the eastern Italian Alps. The administrative area of the city extends over 158 km2
, half of which is covered by forests. The main settlement lies in the valley floor along the River Adige, at around 200 m a.s.l., whilst the surroundings reach an elevation of 2180 m. The valley floor hosts around 70% of the population, as well as most industrial and commercial areas and infrastructures. The few unurbanized patches in the valley floor and the sunny hillsides are used for agriculture, mostly vineyards and apple orchards. The rest of the population lives in several villages spread across the hills, to the east, and on the slopes of Monte Bondone, to the west. The city is divided into 16 districts corresponding to the main residential settlements (Figure 1
). The districts are the smallest administrative units, commonly used for statistical purposes.
Thanks to its location close to mountains, the varied topography, and the peculiar urban form, Trento offers its citizens a diversified portfolio of opportunities for day-to-day nature-based recreation. Citizens benefit from the proximity to different typologies of green infrastructure where they conduct a wide range of nature-based recreational activities. In addition to typical “urban” activities commonly carried out in urban parks (e.g., playing with children, walking, and meeting with friends), popular day-to-day recreational activities in Trento include hiking, mountain-biking, skyrunning, and climbing in nearby forests and mountain areas. Providing all citizens with equal opportunities for nature-based recreation is currently among the main planning objectives of the city administration. However, measuring progresses towards such objective is complex and requires overcoming indicators of availability and accessibility to urban parks in favor of a more comprehensive assessment, able to account for multiple typologies of green infrastructure, recreational activities, and users. Therefore, the study area covers the whole territory of the city and considers the entire urban green infrastructure as potential space for nature-based recreation.
2.2. Adapting the ESTIMAP-Recreation Model to the Local Context
To assess nature-based recreation in Trento, we adopted a locally-adapted version of the ESTIMAP-recreation model. ESTIMAP-recreation is part of a suite of models for the spatially-explicit assessment of ecosystem services [46
], originally developed for EU-wide applications, but increasingly applied to assess potential and opportunities for nature-based recreation across a range of different scales and contexts, from cities to protected areas [36
]. Amongst the strengths of the model are the simple conceptual structure, the possibility of accounting for multiple types of activities, and the flexibility that makes it adaptable to the inclusion of locally-relevant information. The model is based on an “Advanced multiple-layer Look-Up Tables” approach [44
], where the final value of the indicators is obtained from a cross tabulation and spatial composition of different thematic maps. The model is structured into three successive sections. In each section, different components (i.e., thematic sets of input maps) are combined according to scores assigned by the user, based either on the literature or on expert opinion [44
The first section assesses the Recreation Potential (RP), i.e., the capacity of green infrastructure to support nature-based recreational activities based on their intrinsic characteristics, independently from their actual or potential use. The components included in the original version are water, natural protected areas, and degree of naturalness. The RP is described by a raster map with relative values ranging from 0 (no recreation potential) to 1 (maximum recreation potential in the analyzed area).
The second section assesses the Recreation Opportunity Spectrum (ROS) by combining the RP with information about proximity (i.e., in the original version, distance from roads and urban areas), thus providing an assessment of the opportunities for recreational activities offered to the citizens. The ROS is described by a raster map classified into nine categories resulting from the cross-tabulation of high/medium/low values of RP and high/medium/low values of proximity.
The third section includes an assessment of the use or demand for recreation obtained from an analysis of the spatial distribution of potential users and corresponding levels of accessibility.
Within this general structure, adjustments can be undertaken to adapt the model to specific contexts and related policy questions. With this aim, building on the application in eight case studies across Europe, Zulian and colleagues [44
] defined a protocol based on the two successive steps of conceptual adaptation
and structural adaptation
. Conceptual adaptation
requires framing the application of the model with respect to the specific policy question at hand, including issues related to the types of users and uses, the scale of analysis, and the stakeholders that should be involved in the assessment. In Trento, the conceptual adaptation of the model was aimed at reflecting the local conditions in terms of different types of recreational activities and related natural settings, at linking the results to practical information about what types of planning or management interventions are needed more, and at setting the scoring phase in a way that it allows for a meaningful participation of experts from different fields (i.e., by maximizing the similarity of the elements within the same component of the model, thus allowing for an easier comparison).
refers to changes in the original model made to respond to the needs identified in the conceptual adaptation
. It includes: (i) adapting the conceptual scheme in terms of number of components, combination of input data, scoring system, and weighting parameters; (ii) identifying and retrieving locally-relevant data, including the elicitation of scores from experts or stakeholders; and (iii) running the model and sharing results to get feedback, possibly generating a further refinement of the conceptual scheme [44
]. Following the principles expressed in the conceptual adaptation, some adjustments were made on the components of the three sections. In the version adopted for this study, the RP includes three components, namely natural features, urban green infrastructure, and land use, thus distinguishing urban and peri-urban green areas from predominantly natural and semi-natural areas outside the most urbanized part of the city. Furthermore, “proximity” is defined as the availability of facilities and infrastructures that allow access and use of green infrastructure for nature-based recreational activities. Therefore, the ROS module includes two distinct components for access-related and use-related facilities. Finally, population distribution is used to quantify the actual beneficiaries, based on the number of citizens living within a defined distance from areas classified in the highest class of ROS. Figure 2
illustrates the adapted version of the ESTIMAP-recreation model applied to the case study of Trento.
2.3. Assessing Nature-Based Recreation in Trento
The analysis was carried out within the framework of the European project EnRoute (https://oppla.eu/enroute
) by the Trento city-lab, composed of researchers from the University of Trento and municipal officers from the local administration, in collaboration with project leaders from the European Commission Joint research Centre. EnRoute stands for “Enhancing Resilience of urban ecosystems through green infrastructure” and is a project of the European Commission in the framework of the EU Biodiversity Strategy and the Green Infrastructure Strategy. It provides scientific knowledge of how the assessment of urban ecosystems and their services can support urban planning at different stages of policy and for various spatial scales, ultimately supporting policy-making for sustainable cities [52
]. The Trento city-lab decided to focus on nature-based recreation due to the interest of the local administration on the topic. First, the city lab discussed the requirements of the analysis, agreed on the adjustments to be made to the original version of the ESTIMAP-recreation model, and retrieved data and maps of the elements to be included in the different components of the model from existing municipal and provincial databases, and from OpenStreet Map [53
]. Then, to check the type of results and their overall coherence with local conditions, a testing application of the model was carried out using scores assigned by the members of the city lab.
Once the final structure of the model was defined, an on-line questionnaire was prepared to elicit the weights from a pool of local experts. The questionnaire was sent to 19 experts who had previously agreed to collaborate with the project, and 17 valid responses were collected within the deadline (December 2017). Respondents include personnel of different provincial (3) and municipal (7) departments with an interest in recreational areas and activities, including green space management, environment, planning, common goods, social services, sport, protected areas, and landscape; local practitioners (1); and academics from the University of Trento (3) and other research centers (3) working on topics related to ecosystem services, urban green infrastructure, and urban planning. The experts were asked to weight each element by assigning a score from 0 to 5 (direct assessment) according to its relevance in supporting or promoting nature-based recreation. The scores were then averaged, excluding the highest and the lowest score, and converted to a 0–1 scale.
Following the on-line consultation, the model was run for the second time with the elicited weights, and the experts were invited to discuss the resulting maps of RP and ROS in a focus group (March 2018). Twelve out of the 17 experts that completed the questionnaire participated in the discussion and contributed in defining the final list of elements of the components of the model, and the respective scores.
To estimate the number of people with adequate close-to-home recreational opportunities, we used a simple accessibility model based on the Euclidean distance from households. Areas in the highest class of ROS (i.e., high recreation potential and high proximity) were considered as destinations, while a map of residential buildings was used to identify the origins. To be as accurate as possible in the spatial analysis, we retrieved the number of residents in each census tract and considered them as homogeneously distributed on the surface covered by the footprint of residential buildings. The maximum distance was set at 300 m [30
], to take into account the difference between Euclidean and road distance [55
] and of the presence of topographic changes that may act as barriers to long-distance pedestrian movement. The indicator was computed at the district level setting all areas in the highest class of ROS as destinations, and then compared with the results of the same analysis when destinations are limited to urban parks.
While providing all citizens with adequate green spaces for nature-based recreation is among the main goals of green infrastructure planning and management, especially in cities, commonly-adopted indicators that measure the availability and spatial distribution of urban parks offer only a partial view on such a multi-faceted issue. The research investigated to what extent innovative methods considering both the supply and the demand for nature-based recreation from an ecosystem service perspective would improve the way in which it is currently addressed by urban planning. Applying a locally-adapted version of the ESTIMAP-recreation model to Trento allowed for mapping the recreation potential and recreation opportunity spectrum across the whole city, hence quantifying the share of population without adequate access to areas for nature-based recreation. The comparison of the results with indicators limited to urban parks shows significant differences, with clear implications on planning decisions, e.g., in the prioritization of interventions.
The application provided useful information to urban planning, not only by revealing the most deprived areas of the city, but also directing decisions to the most effective interventions, either the increase of green spaces or the enhancement of facilities and infrastructures to access and use recreational areas. Overall, this widens the portfolio of actions that urban planners and local decision-makers can put in place to improve nature-based recreation in cities, and highlights possible synergies with other sectors, such as agriculture, forestry, and protected areas, usually managed according to different goals and at different scales.
Further research is needed on this issue. In the case study, the model could be finetuned and the results of the application could be validated through a more direct involvement of citizens. Interviews and direct observations could provide information about the demand for different nature-based recreational activities and help to identify important features of urban parks to include in the model, as well as site-specific threshold distances to apply in the accessibility analysis. Moreover, further case studies and applications in other socio-ecological contexts are needed to confirm the results.
Nature-based recreation, together with the other cultural ecosystem services, can act as gateway to promote a sustainable planning and management of urban green infrastructure [91
]. The proposed methodology appears to be a promising tool to enhance the quality of information on which planning decisions are currently based, but it requires a successful science-policy interface and the establishment of a local community of practice that manages urban green infrastructure towards multifunctionality.