A TYPOLOGY OF URBAN GREEN SPACES, ECO- SYSTEM SERVICES PROVISIONING SERVICES
Report: D3.1: AND DEMANDS
Work package 3: Functional linkages Partners involved: UL, UBER, TUM, SRC, FCRA, UH, FFCUL Researchers: C. Braquinho, R. Cvejić, K. Eler, P. Gonzales, D. Haase, R.Hansen, N. Kabisch, E. Lorance Rall, J. Niemela, S. Pauleit, M. Pintar, R. Lafortezza, A. Santos, M. Strohbach, K. Vierikko, Š. Železnikar Description: The report outlines the different types of urban green spaces, ESS provision- ing and demand for green space as a part of the EU FP7 (ENV.2013.6.2-5- 603567) GREEN SURGE project (2013-2017)
Primary authors: Rozalija Cvejić, Klemen Eler, Marina Pintar, Špela Železnikar (UL, Slovenia), Dagmar Haase, Nadja Kabisch, Michael Strohbach (UBER, Germany) V10 •May 13th2015
LIST OF CONTRIBUTING PARTICIPANTS TO WP3
No. Legal name (short name) and working months Country Organisation type
1 Kobenhavns Universitet (UCPH) 5 Denmark Research Organisation 2 Helsingin Yliopisto (UH) 3 Finland Research Organisation 3 Humboldt Universität zu Berlin (UBER) 35 Germany Research Organisation 4 Technische Universität München (TUM) 6 Germany Research Organisation 5 Wageningen University (WU) 2 Netherlands Research Organisation 6 Stockholms Universitet (SRC) 8 Sweden Research Organisation 7 Forestry Commission Research Agency (FCRA) 10 United Kingdom Public Body 8 ICLEI European Secretariat (ICLEI Europe) 1 Germany SME 10 Università degli Studi di Bari 'Aldo Moro' (UNIBA) 1 Italy Research Organisation 13 Sveriges Lantbruksuniversitet (SLU) 6 Sweden Research Organisation 14 Fundação da Faculdade de Ciências 18 Portugal Non-profit Da Universidade de Lisboa (FFCUL) Research Organisation 15 Univerza v Ljubljana (UL) 44 Slovenia Research Organisation 16 Technische Universität Berlin (TUB) 1 Germany Research Organisation 24 Eco-Metrica (ECO) 6 United Kingdom SME
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CONTENTS
1 INTRODUCTION 8 1.1 General introduction to the deliverable D3.1 8 1.2 Introduction to the urban green spaces inventory 9 1.3 Introduction to ecosystem service provisioning by urban green space 10 1.4 Introduction into the demand for urban green space 13
2 METHODOLOGY 14 2.1 Urban green space elements inventory 14 2.2 Assessment of urban green space demand for the two scale levels, European Urban Atlas cities and Urban Learning Labs 15 2.2.1 European scale 15 2.2.2 Urban Learning Lab scale 17
3 RESULTS 18 3.1 Inventory of urban green space elements 18 3.1.1 Urban green space elements 18 3.1.2 Empirical evidence for functional links between urban green space elements and ecosystem services 29 3.1.3 Assessments of selected urban green space elements for European and Urban Learning Lab cities 46 3.2 Assessment of urban green space demand for the two scale levels, European Urban Atlas cities and Urban Learning Labs 49 3.2.1 European scale 49 3.2.2 Urban Learning Lab scale 52
4 DISCUSSION 57 4.1 Urban green space elements inventory 57 4.2 Ecosystem service provisioning by urban green space 57 4.3 Assessment of urban green space demand for the two scale levels, Urban Learning Lab and European Urban Atlas cities 58
5 REFERENCES 60
6 SUPPLEMENT 66
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LIST OF FIGURES
Figure 1: Green walls in the city of Augsburg, Germany. (Photo: M. Strohbach) 7 Figure 2: Ecosystem services as an integral of natural capital, goods and benefits for human well-being and drivers of change (left) and different categories of ecosystem services that ecosystems provide (right) (http://enviroatlas.epa.gov/enviroatlas) 12 Figure 3: Method for accessibility calculation in ARC GIS 16 Figure 4: The forest cover of the core city areas of Urban Atlas cities (EEA, 2010) in percent shown for the bottom 20, top 20 and for the ULL cities Bari, Berlin, Edinburgh, Ljubljana and Malmö. 46 Figure 5: The green urban areas cover of the core city areas of Urban Atlas cities (EEA, 2010) in percent shown for the bottom 20, top 20 and for the ULL cities Bari, Berlin, Edinburgh, Ljubljana and Malmö. 46 Figure 6: The agricultural land, semi-natural areas, and wetland cover in the core city areas of Urban Atlas cities (EEA, 2010) in percent shown for the bottom 20, top 20 and for the ULL cities Bari, Berlin, Edinburgh, Ljubljana and Malmö. 47 Figure 7: Share of city areas covered by forests. Calculation based on Urban Atlas data (EEA 2010). 47 Figure 8: Share of city areas covered by green urban areas. Calculation based on Urban Atlas data (EEA 2010). 48 Figure 9: Share of city areas covered by agricultural, semi-natural areas and wetlands. Calculation based on Urban Atlas data (EEA 2010). 48 Figure 10: UGS in the ULL city Berlin. They cover 46 % of the city. Green roofs (detail in frame on top right) cover only 0.1% of the city or 12% of the total building area (Source: Senatsverwaltung für Stadtentwicklung und Umwelt Berlin). 49 Figure 11: Share of population with access to UGS (≥2 ha) within 500 m in administrative city boundaries. Note: Calculation based on GEOSTAT 1 km² grid and Urban Atlas land cover data. 52 Figure 12: Land use/cover as share of total area based on Urban Atlas 20006 (EEA, 2010). 54 Figure 13: Accessibility of urban green and forest areas of a minimum size of 2 ha within 500 m distance. Note: In colour are only those grid cells which are within a distance to a 2ha green space. The respective colour of those grid cells represents the number of people living in that grid cell. Calculation is based on GEOSTAT 1km² grid and Urban Atlas land cover data. No street or public transport net was included in the analysis. 55 Figure 14: Per capita green space (m²/inh.) and population density at district level for the ULL cities Berlin and Ljubljana. 56
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LIST OF TABLES
Table 1: Data used for calculation of demand for UGS at European scale. 17 Table 2: Data used for calculation of demand for UGS at ULL scale 17 Table 3: The elements of the UGS inventory with a description and photos of examples. The full inventory is stored in an excel spreadsheet. 18 Table 4: Empirical evidence for the connection between UGS and provisioning services. Because no link between UGS and medicinal resources was found in this review, the column is also not shown here. 31 Table 5: Empirical evidence for the connection between UGS and regulating services. Pollination and biological control were removed from table because they are usually provided by organisms and not particular UGS. Because no link between UGS and erosion prevention and maintenance of soil fertility was found in this review, the column is also not shown here. 34 Table 6: Empirical evidence for the connection between UGS and habitat or supporting services. Because no link between UGS and maintenance of genetic diversity was found in this review, the column is not shown here. 38 Table 7: Empirical evidence for the connection between UGS and cultural services. 42 Table 8: Land use/land cover area and per capita values for European urban regions 51 Table 9: Area of land cover/land use in the ULL case study cities. 53
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LIST OF ABBREVIATIONS
ESS ecosystem service ULL Urban Learning Lab/ Urban Learning Labs UGS urban green space/ urban green spaces GI green infrastructure DOW description of work UGI urban green infrastructure WP work package PPP public private partnership EU European Union
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Figure 1: Green walls in the city of Augsburg, Germany. (Photo: M. Strohbach)
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1 INTRODUCTION
1.1 General introduction to the deliverable D3.1
The concept of Green Infrastructure (GI) became increasingly important and prominent in the last decade and across the different spheres of science, policy and planning. It is understood as a strategic approach to develop “an interconnected network of green space that conserves natural ecosystem values and functions, and that provides associated benefits to human populations” (Benedict and McMahon, 2002). At the pan-European scale, the GI approach can be central to achieving the 2020 biodiversity target (SCU-UWE, 2012; European Commission, 2013). Accord- ing to the DOW of GREEN SURGE, “[…] urban GI is a planning approach aimed at creating net- works of multifunctional green space in urban environments” (DOW, p11 and Milestone 34).
Historically, most cities were almost devoid of green spaces, but cities were relatively small and most people lived in rural areas. It wasn’t until the 19th century that the importance of parks and other urban green for residents was recognized to some extent (Swanwick et al., 2003). Today, it is understood that urban green spaces (UGS) are essential for well-functioning and liveable cities because they (1) play a recreational role in everyday life; (2) contribute to the conservation of biodiversity; (3) contribute to the cultural identity of the city; (4) help maintaining and improv- ing the environmental quality of the city; and (5) bring natural solutions to technical problems (e.g., sewage treatment) in cities (Sandström 2002). Besides an ever growing evidence base for the benefits of UGS, the increasing interest in them is driven by several other factors according to Swanwick et all. (2003):
Widespread concern at the decline in the quality and condition of many parks and other ur- ban green spaces due in part to their generally low priority in the political agenda at both national and local levels;
Growing emphasis on the need for more intensive development in urban areas, focused around the concept of the high-density 'compact city' as the model for future cities in Eu- rope, raising questions about the role of green space in this model;
Parallel emphasis on the development of brownfield rather than greenfield land, and a recognition that more intensive urban development may sometimes involve the sacrifice of existing areas of urban green space […]
Within the strategy or the approach of urban green infrastructure (UGI), green space elements as parts of the urban ecosystem, ranging from larger woodland and nature areas to private gardens, green roofs to sustainable urban drainage systems, play a major role. Some of these elements, in particular those which are privately owned, as well as vertical green elements, have been rarely investigated in quantitative and functional terms. This is part of the work in WP3.
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According to the DOW of the GREEN SURGE project, WP3 studies the functional linkages be- tween UGS and respective types of green infrastructure and the ecosystem services (ESS) pro- vided by them on one hand, and their impacts on biodiversity, human health and well-being, so- cial cohesion and green economy on the other hand.
The deliverable D3.1 is based on the results achieved with the fulfilment of the two following tasks, and on the Milestones 23 and 24, dedicated to these tasks in the DOW:
Task 3.1: Identification, description and quantification of the full range of urban green spaces This task will develop a comprehensive concept and listing of urban green spaces (i.e. different types of urban green spaces) in urban settings varying from larger public parks, urban woodlands, green fields and street/park trees to private green spaces such as gardens, allotments, and roof, wall and domestic greenery as well as blue components such as lakes, rivers, riparian zones etc. (joint task with WP2). Methods will include a specific literature and data review on urban green space descriptions and analysis from different European cities including results from our own field work, remote sensing results and relevant case studies from other continents for comparison
Task 3.2: Identification and quantification of the demand on ESS provided by urban green spaces This task will involve identification and quantification of the demand on ESS provided by urban green space at two scales, ULLs and Europe (Urban Atlas cities) (joint task with WP2). Methods will include an extensive and criteria-based literature review on the demand on urban ESS at the spatial level of specific cities (ULL and 15 reference cities) and across Europe using the Urban Atlas cities. The review will result in quantitative rankings and qualitative models of urban ESS use by different groups of beneficiaries including residents, planning institutions, economic actors and interest groups.
The main part of this deliverable, consequently, includes the inventory of green space elements, a list and a discussion of the potential ESS provisioning by different green space elements and an analysis of the demand/accessibility of green spaces in European cities. In addition, for the pan- European dataset of the Urban Atlas we show which UGS elements can be identified and quanti- fied using data provided by the European Environment Agency (EEA).
1.2 Introduction to the urban green spaces inventory
Well-designed, well-managed, and well-connected green spaces are integral to the urban green infrastructure (UGI) approach studied within GREEN SURGE. Green spaces, however, are very diverse, ranging from city parks to green walls and rooftop gardens, from urban forests to allot- ment gardens. They basically encompass all vegetation found in the urban environment but they also include blue spaces such as lakes or rivers and their adjacent green. Because of this diversi- ty, as a prerequisite for understanding how green spaces can be functionally connected with each other and with the built environment as green infrastructure, an inventory of UGS elements was compiled for the use within the entire GREEN SURGE project.
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Several inventories have been proposed, for example by Bell et al. (2007), who differentiated between parks and gardens; natural and semi-natural spaces; green corridors; allotments, com- munity gardens and urban farms; outdoor sport facilities; amenity green spaces; provision for chil- dren and young people; cemeteries, disused churchyards and other burial grounds; other public spaces. Swanwick et al. (2003) produced an inventory of 25 UGS types, falling into 10 subgroups and four main groups (amenity green space, functional green space, semi-natural habitats, and linear green space). Other inventories are grouped based on usage (Hofmann and Gerstenberg, 2014), based mainly on scale (Byrne and Sipe, 2010), or cover informal UGS (Rupperch and Byr- ne, 2014). Some typologies combine UGS with other open spaces such as squares, pedestrian areas, cycling areas (DTLR, 2002; Bell et al., 2006).
Probably no inventory can cover all the peculiarities that exist in European cities due to their natural conditions (geomorphological, climatic, biological), historical backgrounds and social demand. In addition, no inventory can be final – social initiatives, technological progress, envi- ronmental awareness and creativity of city planners, urban dwellers and others perpetually lead to new types of UGS (e.g., community gardens, roof allotments, rain gardens, bioswales, con- structed wetlands but also mobile backyard gardens or different forms of guerrilla gardening).
The great diversity of UGS made it necessary to establish an inventory for the use within GREEN SURGE, which has a distinct green-infrastructure-perspective as compared to existing invento- ries. The resulting inventory in Milestone 23, which is part of this deliverable, is based on exiting inventories, internal project meetings and discussions, and a commented draft disseminated to all GREEN SURGE partners. Hence, it includes all UGS considered relevant for GREEN SURGE and particularly for assessing the functional linkages between UGI on the one hand and ecosystem services and biodiversity on the other.
1.3 Introduction to ecosystem service provisioning by urban green space
Ecosystem services are benefits people derive from the functioning of nature or from ecosystem processes (Figure 2). In cities, we call these services urban ecosystem services (urban ESS; TEEB 2011; Haase et al., 2014). Urban ESS have been classified in a variety of ways; most commonly, they are divided into four categories: provisioning services, regulating services, habitat or sup- porting services, and cultural services (MEA 2005; Cowling et al. 2008; TEEB 2011). In more detail, UES can be grouped into the following categories (EASAC, 2009; TEEB, 2011):
1. Provisioning Services are ecosystem services that describe the material or energy out- puts from ecosystems. They include: Raw materials: Ecosystems provide a diversity of materials for fuel and con- struction (plant oils, biofuels and wood that are directly derived from wild and cultivated plant species). Fresh water: Ecosystems play a vital role in the global hydrological cycle, as they regulate the flow and purification of water. Food: Ecosystems provide the conditions for growing food. Medicinal resources: Ecosystems provide plants used as traditional medi- cines and raw materials for the pharmaceutical industry.
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2. Regulating Services are the services that ecosystems provide by acting as regulators. Local climate and air quality: Ecosystems regulate air quality, provide shade and influence rainfall and water availability, removing pollutants from the atmosphere, Carbon sequestration and storage: Ecosystems store and sequester green- house gases, remove carbon dioxide from the atmosphere, improve the capac- ity of ecosystems to adapt to the effects of climate change. Moderation of extreme events: Ecosystems moderate extreme weather events or natural hazards (storms, tsunamis, floods, avalanches,...), ecosys- tems and living organisms create buffers against natural disasters. Waste-water treatment: Ecosystems filter both animal and human waste and act as a natural buffer to the surrounding environment.
3. Cultural services include the non-material, socio-ecological benefits (including psycho- logical and cognitive benefits) people obtain from contact with the environment. Recreation, physical and mental health (for example walking or play- ing sports in green areas) Tourism Aesthetic appreciation and inspiration for culture, art and design Spiritual experience and sense of place: different sacred places or plac- es with a religious meaning.
4. Habitat and supporting services underpin almost all other services by providing living spaces for organisms. Habitats for species Maintenance of genetic diversity.
The Millennium Ecosystem Assessment concluded that 60 % of the world’s ecosystems are de- graded or used unsustainably, having adverse effects on ESS provisioning and human well-being (MEA 2005). Because almost no ecosystem remains un-impacted by humans and humans cannot exist without ecosystems, protection and sustainable use of ecosystems are no longer an isolated interest but a key element of global sustainable development. The observed rapid degradation of the ability of ecosystems to generate services not only necessitates a better understanding of how to maintain important ecosystem functions but also requires that this knowledge is put into a broad institutional and governance context (TEEB 2011).
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Figure 2: Ecosystem services as an integral of natural capital, goods and benefits for human well- being and drivers of change (left) and different categories of ecosystem services that ecosystems provide (right) (Source: http://enviroatlas.epa.gov/enviroatlas).
Today, cities are facing enormous challenges, such as climate change, demographic aging, and natural resource depletion. Ecosystems and their natural capital play an important role in facili- tating transformations needed to address these challenges. Understanding how urban ecosys- tems work, how they change, and what limits their performance can add to the general under- standing of ecosystem change and governance in an ever more human-dominated world (Elmqvist et al. 2013). In general, functioning ecosystems provide the flexibility in urban land- scapes to build adaptive capacity and cope with problems such as increased risks of heat waves and flooding.
Although urban social–ecological system analyses have been found to be promising for enhanc- ing our understanding of how exactly ecosystems and green infrastructure can help address the moderation of climate change effects, large knowledge gaps, particularly for cities, are still pre- sent. For example, urban ecosystems were vastly underrepresented in the world’s largest as- sessment of ecosystems. The TEEB study (2011) made one of the first successful attempts to explicitly represent urban ecosystems in their ‘‘Manual for Cities”, which includes also a discus- sion of the benefits of UGS but still, a comprehensive assessment of ecosystem services in urban areas does not exist, let not alone an assessment of all major urban areas in Europe.
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1.4 Introduction into the demand for urban green space
Urban residents’ mental and physical health and well-being can benefit from the ecosystem ser- vices provided by green spaces. The demand for UGS can therefore be roughly approximated by the number of urban population. The application of per capita UGS values and accessibility threshold values can provide a broad overview-kind of assessment of green space provision for a whole city without looking into the inner differentiation of the city itself (Larondelle and Haase, 2013). Green spaces can be broadly defined as any vegetated areas found in the urban environ- ment, including parks, forests, open spaces, lawns, residential gardens, or street trees (see 1.2). For the purpose of this analysis, a narrower definition is used (see 2.2).
The benefits of green space are broad and diverse (for an overview see a review by Kabisch et al., 2015): UGS help to preserve and enhance biodiversity within urban ecosystems (Tzoulas et al., 2007). Green spaces provide fresh air, reduce noise and elevated air temperatures through their cooling capabilities (Bowler et al., 2010; Spronken-Smith and Oke, 1998). Social benefits include positive influence on psychological and mental health (Ulrich et al., 1991; Völker and Kistemann, 2013) via stress reduction (Chiesura, 2004; Kaplan, 1985) and relaxation (Kuo et al., 1998). Within a broader social view, UGS act as meeting places in neighbourhoods (Martin et al., 2004) and play an important role in the interactions of residents of different population groups with others in their community by providing space (Kabisch and Haase, 2014). Finally, UGS often pro- vide the primary contact with local flora and fauna and the natural environment for urban resi- dents and thus increase environmental learning (Krasny et al., 2013).
Because of the many benefits green spaces provide, their availability and accessibility to resi- dents in cities have been the focus of planning and research for some time. Van Herzele and Wiedemann (2003) applied a spatial GIS (Geographical Information System)-based indicator system to cities in Belgium to plan accessible and attractive green spaces. Germann-Chiari and Seeland (2004) used GIS and regression analyses to assess the distribution and access of UGS by social target groups in three cities in Switzerland. Comber et al. (2008) used a GIS approach for Leicester, UK, to assess UGS accessibility for different ethnic and religious groups. Balram and Dragićević (2005) used multiple methods involving semi-structured interviews and a collabora- tive GIS workshop for accessibility assessments. In the US, the focus of research and planning has been on the distribution of tree canopy rather than green space. Heynen (2003) for example, found that minorities and residents with low socio-economic status had a lower canopy cover in their neighbourhood. Danford et al. (2014) studied the difficulties in reaching an equitable tree canopy distribution in Boston, MA, USA.
Some European cities provide per capita threshold values for UGS or for minimum accessibility for a defined area. For instance, the city of Berlin, Germany, aims at providing at least 6 m² urban green per person (Senatsverwaltung für Stadtentwicklung und Umwelt, 2013), while Leipzig, Germany, aims at 10 m² per capita (Stadt Leipzig, 2003). In the UK, it is recommended that – as a national target – city residents should have access to a natural green space of minimum 2 ha within a distance of 300 m from home (Handley et al., 2003). Berlin’s Department of Urban De- velopment and the Environment recommends that every resident should have access to urban green of minimum 0.5 ha within a 500 m distance from home. Similarly, Hutter et al., (2004) rec- ommend green space of 1.0 – 10 ha for every resident within 500 m.
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2 METHODOLOGY
2.1 Urban green space elements inventory
The inventory is based on existing inventories and general literature on UGS1, internal project meetings and discussions, and a commented draft disseminated to all GREEN SURGE partners. Moreover, several revisions of the database prepared for Milestone 23 were included in the cur- rent typology. Thus, the inventory reflects the needs of GREEN SURGE but can also serve needs from outside the project. As it is linked to Urban Atlas and Corine land use/ land cover, it bridges scales from regional to local. It also supports cross-city comparisons. The inventory includes green, partly green and grey as well as blue spaces (waters, wetlands). It also includes green space usually not considered urban, but which can be located close to the city or even within the city itself (like arable land, forests, grasslands, sparsely vegetated areas). Thus, the inventory can also be applied to larger urban regions.
The UGS inventory is contained in a spreadsheet with four tabs: Definitions, UGS elements, Urban Atlas legend and the Corine land cover (CLC) legend. The main tab of the spreadsheet is UGS ele- ments. There, each UGS is listed and grouped into one of eight broader categories (based mainly on scale, location within city and function). Additional columns in the spreadsheet are:
synonyms if available; a description of each element; a column where it is indicated if the element concerns a green or a blue space; a column indicating the type of management of the UGS, either in form of state, coopera- tions, institutions, PPP, associations, private etc.; a column indicating whether the UGS element is private or publicly accessible; a column which indicates if public engagement or stewardship is generally possible in regards to the respective element; a column highlighting possible data sources if data is used for certain purposes; column indicating data availability for ULL; column indicating data availability at European scale (i.e. if an element can be identified on the European data level (Urban Atlas) scale); three columns that show corresponding land cover types (CORINE), land use types (Ur- ban Atlas) and habitat types (EUNIS); urban ecosystem services based on the TEEB for city categories (TEEB 2011). The col- umns contain empirical evidence from the literature for functional links between the UGS elements and ESS.
1 Ahern (2007); Alberti (2008); Baycan-Levent et al. (2009); Bell et al. (2006); Bell et al. (2007); Benedict and McMahon (2001); Bolund and Hunhammar (1999); Botkin and Beveridge(1997); Byrne and Sipe (2010); Cameron et al. (2012); Carr et al. (1992); Comber et al. (2008); DTLR (2002); Dunnett et al. (2002); EEA (2007); EEA (n.d.); Hofmann et al. (2014); Kabisch et al. (2015); Keeley et al. (2013); Kowarik et al. (2011); Landscape Institute (2009); McMahon (2000); Natural England (2009); Neuenschwander et al. (2014); Niemelä et al. (2010); Pfoser (2012); Rupprecht et al. (2014); Sadler et al. (2010); Sandström et al. (2002); Swanwick et al. (2003); Tzoulas et al. (2007); Van Herzele and Wiedemann (2003); Van Leeuwen et al. (2010); Völker and Kistemann (2013); Wooley (2003)
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We include the corresponding Urban Atlas and Corine land cover classes, because these two pub- licly available land use/cover data sets are used for UGS and related ESS analysis and quantifica- tion on EU level. Some of the columns are still empty and need input after extensive discussion with project partners and also in-depth analyses during the project. Therefore, we emphasize that this work and the whole inventory is a living document which will be further developed and completed during the whole project time.
2.2 Assessment of urban green space demand for the two scale levels, European Urban Atlas cities and Urban Learning Labs
2.2.1 European scale
To assess the demand for UGS, both land use data (land cover data) and demographic data are used for calculation of statistical and GIS models. Land cover data stem from the European Urban Atlas land cover dataset obtained from (EEA 2010). The data in the Urban Atlas refer to 301 larger urban zones which refer to commuting zones around cities. Urban Atlas data are based on satellite images with a 2.5 m spatial resolution and, thus it provides comparable land use data for all of the European core cities and respective larger urban zones with more than 100,000 inhab- itants. The analyses in Milestone 24 and this deliverable focus exclusively on the core cities. Therefore, core cities were delineated using the core city layer from the Urban Audit (European Commission, 2004), which refers to administrative city boundaries.
In the Urban Atlas, 21 thematic classes, including diverse urban fabric, transportation, industrial and environmental classes, are distinguished (EEA, 2010). This classification of urban land cover and land use is, thus, finer than commonly used datasets of land-cover/land use. In particular, the Urban Atlas includes groups of different urban fabric classes according to density and a ‘‘land without current use’’ class, which represents brown fields. For green assessments the classes “green urban areas” and “forest areas” are used. Unfortunately, the class “agricultural areas, semi-natural areas and wetlands” combines land that can potentially serves as green space (i.e. grasslands, semi-natural land) with land of low recreational value (i.e. arable land). We therefore excluded it from our analysis. We also decided not to include Urban Atlas class 142 “sports and leisure facilities” in our definition of UGS because “sports and leisure facilities” includes race courses and areas of sport compounds (e.g., football stadiums, tennis courts, golf courses), which a) can be covered by hard surfaces (except of golf courses) to a high degree, and b) might be not publicly available and thus not accessible to all urban residents (they may provide other im- portant ESS, nevertheless). Both restrictions might lead to an underestimation of both per capita green space values and its accessibility. The Urban Atlas land use data refer to the year 2006 (a follow-up version that should be based on 2012 imagery is in preparation and expected to be published in 2015).
Population data is provided by the Urban Audit Data Explorer (http://www.eea.europa.eu/data- and-maps/data/external/urban-audit-database) and by national statistical agencies and are used to calculate per capita values. The data refer to the selection period 2012/2013 and are provided for core cities and are, thus, comparable to the Urban Atlas spatial delineation (see
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Kabisch and Haase, 2013 for a methodological comparison). In total, 290 cities in 26 countries are part of this analysis. We had to exclude some of the Urban Atlas cities were no or insufficient population data was available.
Using both, Urban Atlas data and population data, we calculated the total amount of the land use classes per city and the per capita values of green spaces provision on city level.
Finally, the 1 km² grid dataset of population data for the EU from 2011 was used for calculating the access to green space (≥ 2 ha) within a 500 m distance. The grid dataset was produced by the ESSnet project GEOSTAT which was launched in co-operation with the European Forum for Geo- Statistics (EFGS). For accessibility calculations, a 500 m buffer around green and forest areas within administrative boundaries of cities was calculated within GIS (ARCMap 10.0, Figure 3). All grid cells which had their centroids within the city area were selected and respective population numbers were aggregated per cities. Then the grid cells were combined with the buffer of the green space (using the Arc Map toolbox function “intersect”). If a grid cell was only partly within the buffer zone, percentage share of area within buffer was calculated and used for calculating the respective population numbers within this part of the grid cell. All data used for calculation at European scale is presented in Table 1.
Figure 3: Method for accessibility calculation in ARC GIS
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Table 1: Data used for calculation of demand for UGS at European scale. Data Temporal scale Source Administrative city boundaries 2004 GISCO Urban Audit (http://ec.europa.eu/eurostat/web/gisco)
Demography GEO STAT Grid 2011 GISCO 2014 (http://ec.europa.eu/eurostat/web/gisco)
Urban green space (class 141 and class 2006 Urban Atlas 2006 (EEA, 2010) forest areas class 30)
Urban residential area (classes 111- 2006 Urban Atlas 2006 (EEA, 2010) 1124)
2.2.2 Urban Learning Lab scale
Data for calculating the demand of the case study cities reflect land use/cover data and demo- graphic data (Table 2). Land use data are based on the Urban Atlas data base for comparability reasons. Data for demographic calculations stem from local administrative agencies. They in- clude population number for specific years. District data is available for the ULLs Berlin (Germa- ny) and Ljubljana (Slovenia). Although not being a case study city, we also included the Polish city of Łódź into the case study analysis to discuss a case from Eastern Europe.
Table 2: Data used for calculation of demand for UGS at ULL scale Data Temporal scale source
Administrative city boundaries 2004 GISCO Urban Audit
District borders Berlin, Edinburgh, Ljubljana 2012 Local communal sta- tistical agencies
Demographic data (population number) 2013 Local communal sta- tistical agencies
Land cover/use data (class 141 and class 2006 Urban Atlas 2006 forest areas class 30) (EEA, 2010)
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3 RESULTS
3.1 Inventory of urban green space elements
3.1.1 Urban green space elements
The inventory contains 44 UGS elements (Table 3). They fall into eight categories (Table 4). More detail can be found in the living document spreadsheet.
Table 3: The elements of the UGS inventory with a description and photos of examples. The full inventory is stored in an excel spreadsheet. No. UGS element Description Example 01 balcony green Plants in balcony and ter- races, planted mostly in pots.
02 ground based green wall Ground based climbing plants intended for orna- mental (and sometimes food production) purposes.
03 facade-bound green wall Plants growing in facade- bound substrate, e.g. con- tainers or textile-systems.
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No. UGS element Description Example 04 extensive green roof Roof vegetation on thin substrate with little or no irrigation and management. Vegetation established ei- ther artificially by seeding or planting or naturally: moss- es, succulents, few herbs and grasses.
05 intensive green roof Roof vegetation on thick substrate with irrigation and management. Vegetation established either artificially by seeding or planting or naturally: perennials, grass- es, small tress, rooftop farming.
06 atrium Green area surrounded / enclosed in a building planted mostly with orna- mental plants.
07 bioswale Vegetated and gently sloped pit for filtering sur- face runoff.
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No. UGS element Description Example 08 tree alley and street tree, Trees planted along roads hedge and paths either solitary or in rows. Hedges along roads or paths.
9 street green and green Non-tree, mostly shrubby or verge grassy verges along roads or other built or natural ele- ment
10 house garden Areas in immediate vicinity of private houses cultivated mainly for ornamental pur- poses and/or non- commercial food produc- tion.
11 railroad bank Green space along railroads.
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No. UGS element Description Example 12 green playground, school Green areas intended for ground playing or outdoor learning.
13 riverbank green Green space sideways the rivers, streams and canals, usually with foot or bike paths.
14 large urban park Larger green area within a city intended for recrea- tional use by urban popula- tion, can include different features such as trees, grassy areas, playgrounds, water bodies, ornamental beds, etc.
15 historical park/garden Similar to large urban parks, but with distinct manage- ment due to heritage status.
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No. UGS element Description Example 16 pocket park Small park-like areas around and between buildings veg- etated by ornamental trees and grass, publicly accessi- ble.
17 botanical garden Educational and ornamental areas planted with large diversity of plant species.
18 zoological garden Areas with animals kept in cages and enclosures often combined with planted trees, ornamental beds and cultivated grass.
19 neighbourhood green Semi-public green spaces, space vegetated by grass, trees and shrubs in multi-story residential areas.
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No. UGS element Description Example 20 institutional green space Green spaces surrounding public and private institu- tions and corporation build- ings.
21 cemetery and churchyard Burial ground often with covered by lawns, trees and other ornamental plants.
22 green sport facility Intensively cultivated and fertilized grass turf toler- ant to frequent trampling for sport activities (e.g., golf courses, football fields).
23 camping area Green areas reserved for camping.
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No. UGS element Description Example 24 allotment Small garden parcels culti- vated by different people, intended for non- commercial food production and recreation.
25 community garden Areas, collectively gardened by a community for food and recreation.
26 arable land Regularly ploughed arable land for crop production.
27 grassland Pastures or meadows.
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No. UGS element Description Example 28 tree meadow/ meadow Fruit and nut trees, mixed orchard agricultural and fruit or biofuel production.
29 biofuel production / agro- Land devoted to dedicated forestry biofuels like short rotation coppice.
30 horticulture Land devoted to growing vegetables, flowers, berries, etc.
31 forest (remnant woodland, Natural or planted areas of managed forest, mixed dense tree vegetation. forms)
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No. UGS element Description Example 32 shrubland Natural or secondary shrub- land, e.g., heath, macchia, etc.
33 abandoned, ruderal and Recently abandoned areas, derelict area construction sites, etc. With spontaneously occurring pioneer or ruderal vegeta- tion.
34 rocks Areas covered by sparsely vegetated rocky areas.
35 sand dunes Areas covered by sparsely vegetated sandy areas, shaped by wind or water.
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No. UGS element Description Example 36 sand pit, quarry, open cast Sites with removed top soil mine and vegetation for resource extraction.
37 wetland, bog, fen, marsh Areas with soil permanently or periodically saturated with water and characteris- tic flora and fauna.
38 lake, pond Natural and artificial stand- ing water bodies containing non-saline water with (semi)natural aquatic com- munities, banks artifi- cial/managed or natural.
39 river, stream Running waters, including springs, streams and tem- porary water courses, riverbanks artificial/ man- aged or natural.
40 dry riverbed, rambla Land depression formed by flowing water but usually dry. Can be managed or unmanaged and is usually rich in biodiversity and of- ten used for recreation.
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No. UGS element Description Example 41 canal Artificial non-saline water courses with man-made substrate.
42 estuary Downstream part of the river, subject to tidal effects with mixing of freshwater and seawater.
43 delta Landform at the mouth of a river formed by sediment deposits.
44 sea coast Contact areas (littoral) be- tween the sea and the land of different characteristics, e.g. sand beaches, cliffs, coastal dunes.
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3.1.2 Empirical evidence for functional links between urban green space elements and ecosystem services
In the following section, we present evidence from the literature for functional links between UGS elements and ESS (Table 4 -
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Table 7). There are several field studies and modelling attempts running in GREEN SURGE that will identify estimates of ecosystem services provisioning of single elements of UGS in more de- tail, such as allotment gardens, parks, brownfields and meadows. The quantitative results of these studies will be included into the living documents spreadsheet of UGS elements later in the project. So far, we highlight the contribution of UGS types to ESS provisioning in a semi- quantitative, more qualitative way based on a selective review of literature which includes the paper database of a large review about urban ecosystem services (Haase et al., 2014). The refer- ences are provided in the supplement.
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Table 4: Empirical evidence for the connection between UGS and provisioning services. Because no link between UGS and medicinal resources was found in this review, the column is also not shown here.
Category No. Green space element Food Raw materials Fresh water
1 balcony green
2 ground based green wall
3 facade-bound green wall
4 extensive green roof
intensive green roof Rooftop gardens could grow a large
building greens building 5 share of Bologna’s vegetables (Orsini et al., 2014).
6 atrium
c- 7 bioswale
tree alley and street tree, 8 hedge
street green and green 9
verge
ture house garden Residential gardens make up the big- 10 gest part of Chicago’s urban agricul-
ture sites (Taylor and Lovell, 2012). GS connected GS infrastru to grey U 11 railroad bank
green playground, school
GS and GS 12 U private, commercial, private, industrial, institutional ground
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Category No. Green space element Food Raw materials Fresh water
riverbank green
13
green riverbank
14 large urban park
15 historical park/garden
16 pocket park
17 botanical garden/arboreta
18 zoological garden
neighbourhood green During WW II, neighbourhood green 19 space was changed into tenant gardens
(Zerbe et al., 2003). parks andrecreation 20 institutional green space
21 cemetery and churchyard
22 green sport facility
23 camping area
allotment Large quantities of vegetables can be
m- 24 grown in allotment and community gardens. In Chicago, community gar- dens make up 20% of the urban agri- community garden culture area (TEEB, 2011; Taylor and
munitygardens 25 Lovell, 2012). allotments andco
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Category No. Green space element Food Raw materials Fresh water
26 arable land
27 grassland
28 tree meadow / orchard
biofuel production / agro- 29 forestry
agriculturalland horticulture Urban farms used for growth of veg- etables make up 4.7% of Chicago’s 30 urban agriculture area (Taylor and Lovell, 2012).
forest (remnant wood- Forests provide food in urban areas Forests provide raw materials in ur- 31 land, managed forests, (Niemelä et al., 2010; Yokohari and ban areas (Niemelä et al., 2010;
mixed forms) Bolthouse, 2011). Yokohari and Bolthouse, 2011).
32 shrubland
abandoned, ruderal and Land conversion on brownfields of- Marginal land can be sustainably derelict area fers great potential for food produc- used for biofuel production under
tion, except for on polluted sites. In certain conditions, e.g., low contam-
33 Chicago, gardens on vacant lots ination (Zhao et al., 2014). naturaland feral areas - make up 27% of Chicago’s urban ag- riculture area (Taylor and Lovell, 2012; Haase et al., 2014).
34 rocks natural,semi
35 sand dunes
36 sand pit, quarry, open cast
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Category No. Green space element Food Raw materials Fresh water
mine
37 wetland, bog, fen, marsh
38 lake, pond Fresh water and sea ecosystems pro- vide food in urban areas (Niemelä et river, stream
39 al., 2010).
40 dry riverbed, rambla
spaces 41 canal Fresh water and sea ecosystems pro-
blue vide food in urban areas (Niemelä et 42 estuary al., 2010). 43 delta
44 sea coast
Table 5: Empirical evidence for the connection between UGS and regulating services. Pollination and biological control were removed from table because they are usually provided by organisms and not particular UGS. Because no link between UGS and erosion prevention and maintenance of soil fertility was found in this review, the column is also not shown here.
Local climate and air quality Carbon sequestration and stor- Moderation of extreme Category No. Green space element Waste-water treatment regulation age events
1 balcony green
2 ground based green wall Enhance air quality, reduce urban heat island effect, 3 facade-bound green wall reduce heating and cooling
4 extensive green roof costs (Bohemen et al., Green roofs have great Green roofs can take up building greens building potential to reduce storm pollution form rainwater 5 intensive green roof 2008; Cook-Patton and
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Local climate and air quality Carbon sequestration and stor- Moderation of extreme Category No. Green space element Waste-water treatment regulation age events
Bauerle, 2010; Sternberg water runoff in low rainfall (Cook-Patton and Bauerle, et al. 2010 and 2011; events (Mentens et al., 2010). Wong et al. 2010). 2006; Cook-Patton and Bauerle, 2010).
6 atrium
t- bioswale Bioswales reduce the Bioswales reduce the pol- 7 amount of stormwater lution load of stormwater
runoff (Pataki et al., 2011). runoff (Pataki et al., 2011). GSconnec
U tree alley and street tree, Provide cooling, wind con- Street trees can store car- hedge trol and air pollution re- bon under certain condi- 8
GS and GS moval (Tyrväinen et al., tions (Novak, 2002).
U 2005).
street green and green 9
verge
house garden Gardens improve localised Private gardens store low Gardens help mitigate air cooling (Cameron et al., amounts of carbon in trees flooding (Cameron et al., 2012). in Leicester, UK, and Leip- 2012).
edto grey infrastructure 10 zig, Germany (Davies et al., 2011, Strohbach and Haase, 2012).
11 railroad bank
green playground, school 12 private, commercial, private, industrial, institutional ground
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Local climate and air quality Carbon sequestration and stor- Moderation of extreme Category No. Green space element Waste-water treatment regulation age events
riverbank green
13
green riverbank
The Cascine Park in Flor- large urban park ence, Italy, was shown to have retained its capacity to 14 remove pollutant (TEEB, 2011).
15 historical park/garden
16 pocket park
17 botanical garden/arboreta
18 zoological garden
neighbourhood green parks andrecreation 19 space
20 institutional green space
21 cemetery and churchyard
22 green sport facility
23 camping area i-
allotment
r- t-
24
and
dens
allo
ments
ty ga ty commun
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Local climate and air quality Carbon sequestration and stor- Moderation of extreme Category No. Green space element Waste-water treatment regulation age events
community garden 25
26 arable land
27 grassland
28 tree meadow / orchard
biofuel production / agro- 29
agriculturalland forestry
30 horticulture
forest (remnant wood- Forests provide cooling, Forests in cities can store land, managed forests, wind control and air pollu- large amounts of carbon
31 mixed forms) tion removal (Tyrväinen et (Strohbach and Haase, al., 2005). 2012).
32 shrubland
abandoned, ruderal and
33
derelict area naturaland feral areas
- 34 rocks
35 sand dunes
sand pit, quarry, open cast 36
natural,semi mine
wetland, bog, fen, marsh Wetlands in Berlin are Upstream wetlands reduce Functioning urban wet- 37 used for carbon mitigation flooding after heavy rain- lands contribute strongly
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Local climate and air quality Carbon sequestration and stor- Moderation of extreme Category No. Green space element Waste-water treatment regulation age events
(Klingenfuß, 2013). fall events (TEEB, 2011). to waste water treatment (Cairns and Palmer, 1995; Niemelä et al., 2010; TEEB, 2011).
38 lake, pond
39 river, stream
40 dry riverbed, rambla
41 canal
bluespaces 42 estuary
43 delta
44 sea coast
Table 6: Empirical evidence for the connection between UGS and habitat or supporting services. Because no link between UGS and maintenance of genetic diversity was found in this review, the column is not shown here.
Category No. Green space element Habitats for species
1 balcony green Balconies provide habitat for wild bees in Leipzig, Germany (Everaars et al., 2011).
ground based green wall Green walls enhanced the habitat of house sparrows and European starlings in Stoke-on-Trent and Newcastle-under- 2 Lyme, UK, (Chiquet et al., 2012).
3 facade-bound green wall building greens building 4 extensive green roof Diverse roofs can support diverse communities (Cook-Patton and Bauerle, 2010; Fernandez-Canero and Gonzales-
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Category No. Green space element Habitats for species
5 intensive green roof Redondo, 2010).
6 atrium
7 bioswale u-
tree alley and street tree, Streetscapes with old trees supported a higher abundance and richness of bird species than other streets in Mel- 8
hedge bourne, Australia (White et al., 2005).
street green and green Diverse streetscapes with native vegetation enhance abundance and richness of species (Leather, 2004; White et al., 9
verge 2005; Lososová et al. 2011).
GS connected GS to grey
U house garden Diverse gardens enhance abundance and richness of species (Smith et al., 2006; Goddard et al., 2010; Lososová et al., 10
infrastructure 2011; Cameron et al., 2012). GS and GS
U 11 railroad bank
green playground, school tional
private, commercial, private, industrial, instit 12 ground
riverbank green
13
green riverbank
large urban park Large parks have an outstanding value for urban biodiversity (Donnelly and Marzluff, 2004; Lososová et al. 2011; 14 Strohbach et al., 2013).
15 historical park/garden
recreation 16 pocket park Pockets parks slightly increase number of observed bird species (Strohbach et al., 2013).
17 botanical garden/arboreta
parks and 18 zoological garden
19 neighbourhood green
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Category No. Green space element Habitats for species
space
20 institutional green space
21 cemetery and churchyard
22 green sport facility
23 camping area
allotment Tenant gardens showed relatively high plant species richness in a study in Berlin, Germany (Zerbe et al., 2003).
m- 24
community garden
munitygardens 25 allotments andco
26 arable land
27 grassland In a study in Leipzig Germany, high bird species richness was associated with grassland (Strohbach et al., 2009).
28 tree meadow / orchard
biofuel production / agro- 29
agriculturalland forestry
30 horticulture
forest (remnant wood- Urban forests are biodiversity hot-spots (Tyrväinen et al., 2005; Strohbach et al., 2009). -
31 land, managed forests,
mixed forms) areas
32 shrubland Mid successional sites with grassland and shrub vegetation host diverse assemblages (Lososová et al., 2011). natural,semi naturaland feral 33 abandoned, ruderal and
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Category No. Green space element Habitats for species
derelict area
34 rocks
35 sand dunes
sand pit, quarry, open cast 36 mine
37 wetland, bog, fen, marsh
38 lake, pond In a study in Leipzig Germany, high bird species richness was associated with lakes and ponds (Strohbach et al., 2009).
river, stream In a study in Leipzig Germany, high bird species richness was associated with rivers and streams (Strohbach et al., 39
2009).
40 dry riverbed, rambla
41 canal bluespaces 42 estuary
43 delta
44 sea coast
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Table 7: Empirical evidence for the connection between UGS and cultural services. Aesthetic appreciation and Recreation and mental and Spiritual experience and sense Category No. Green space element Tourism inspiration for culture, art and physical health of place design
1 balcony green
2 ground based green wall
3 facade-bound green wall
4 extensive green roof Green roofs can enhance Green roofs can enhance overall human well-being the aesthetic environment intensive green roof building greens building 5 (Cook-Patton and Bauerle, (Cook-Patton and Bauerle, 2010). 2010).
6 atrium
7 bioswale
GS
tree alley and street 8 tree, hedge
street green and green 9 verge
house garden Gardens can provide stress Gardens are shaped by Positive memories of
relief (Cameron et al., aesthetic desires (Cameron childhood are often linked
10 2012). et al., 2012). to gardens and provide ial, industrial, institutional ial, U strong sense of place
(Cameron et al., 2012). GS connected GS togrey infrastructure U 11 railroad bank
and green playground,
private, commerc private, 12 school ground
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Aesthetic appreciation and Recreation and mental and Spiritual experience and sense Category No. Green space element Tourism inspiration for culture, art and physical health of place design
riverbank green Structurally rich riverbanks
are associated with psy- 13
green chological well-being (Dal- riverbank limer et al., 2012).
large urban park Parks contribute to the physical and psychological 14 well-being (Fuller et al., 2007; Niemelä et al., 2010).
15 historical park/garden
pocket park Small public are used pri- marily for rest and restitu- 16 tion and socialising (Pes- chard et al., 2012).
botanical gar- 17 den/arboreta
parks andrecreation 18 zoological garden
neighbourhood green 19 space
20 institutional green space
cemetery and church- 21 yard
22 green sport facility
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Aesthetic appreciation and Recreation and mental and Spiritual experience and sense Category No. Green space element Tourism inspiration for culture, art and physical health of place design
23 camping area
allotment Gardening in community
m- 24 gardens and allotments community garden Gardening in community enhance social capital gardens is associated with (Yokohari and Bolthouse, 25 health benefits (Yokohari 2011; Cameron et al.,
munitygardens and Bolthouse, 2011; 2012). allotments andco Cameron et al., 2012).
26 arable land
27 grassland
28 tree meadow / orchard
biofuel production / ag- 29
agriculturalland roforestry
30 horticulture
e- forest (remnant wood- Urban forests provide rec- Urban forests are im- Urban forests can improve land, managed forests, reational opportunities, portant for tourism home and work environ- mixed forms) and have a positive impact (Tyrväinen et al., 2005). ments and may have a 31 on psychological well- strong cultural and histori-
being (Tyrväinen et al., cal value (Tyrväinen et al.,
as 2005; Niemelä et al., 2005). naturaland feral ar - 2010).
semi 32 shrubland
abandoned, ruderal and 33 natural, derelict area
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Aesthetic appreciation and Recreation and mental and Spiritual experience and sense Category No. Green space element Tourism inspiration for culture, art and physical health of place design
34 rocks
35 sand dunes
sand pit, quarry, open 36 cast mine
37 wetland, bog, fen, marsh
38 lake, pond Recreational opportunities are provided especially by river, stream 39 water ecosystems (Nie-
melä et al., 2010).
40 dry riverbed, rambla
41 canal Recreational opportunities bluespaces are provided especially by 42 estuary water ecosystems (Nie- 43 delta melä et al., 2010). 44 sea coast
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3.1.3 Assessments of selected urban green space elements for European and Urban Learning Lab cities
For an overview on the amount of green space in European cities, we quantified some of the UGS components using the Urban Atlas data (EEA, 2010). Maps and plots are shown for forests (UGS class 31; Figure 4; Figure 7), green urban areas (UGS classes 13 - 20; Figure 5; Figure 8) and agri- cultural, semi-natural areas, wetlands (UGS class 26-30, 32, 34, 35, 37; Figure 6; Figure 9). In addition, we created a map of UGS for Berlin (Figure 10).
Figure 4: The forest cover of the core city areas of Urban Atlas cities (EEA, 2010) in percent shown for the bottom 20, top 20 and for the ULL cities Bari, Berlin, Edinburgh, Ljubljana and Malmö.
Figure 5: The green urban areas cover of the core city areas of Urban Atlas cities (EEA, 2010) in percent shown for the bottom 20, top 20 and for the ULL cities Bari, Berlin, Edinburgh, Ljubljana and Malmö.
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Figure 6: The agricultural land, semi-natural areas, and wetland cover in the core city areas of Urban Atlas cities (EEA, 2010) in percent shown for the bottom 20, top 20 and for the ULL cities Bari, Berlin, Edinburgh, Ljubljana and Malmö.
Figure 7: Share of city areas covered by forests. Calculation based on Urban Atlas data (EEA 2010).
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Figure 8: Share of city areas covered by green urban areas. Calculation based on Urban Atlas data (EEA 2010).
Figure 9: Share of city areas covered by agricultural, semi-natural areas and wetlands. Calcula- tion based on Urban Atlas data (EEA 2010).
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Figure 10: UGS in the ULL city Berlin. They cover 46 % of the city. Green roofs (detail in frame on top right) cover only 0.1% of the city or 12% of the total building area (Source: Senatsverwal- tung für Stadtentwicklung und Umwelt Berlin).
3.2 Assessment of urban green space demand for the two scale levels, European Urban Atlas cities and Urban Learning Labs
3.2.1 European scale
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Table 8 shows mean values for total area, residential area, forest areas, and green urban areas for Northern, Southern, Eastern and Western European cities. The sample was grouped accord- ing to macro-geographical regions (United Nations Institute of Social Affairs, 2010). In Western and Northern Europe, the share of residential area is comparatively higher which gives a first hint on the long and ongoing sprawl process after WW II there. Not surprisingly, forest areas are most frequent in Northern European cities. Cities in Eastern and Southern Europe show lowest values for green areas within their city boundaries. This reflects the ideal of the dense southern European city where in a number of cities narrow roads have been most important to provide shadow during hot summers. This is also represented in comparatively low values for per capita green space.
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Table 8: Land use/land cover area and per capita values for European urban regions Western Southern Eastern Northern Indicator Europe Europe Europe Europe Total area (ha) 29625.04 25595.24 18958.96 48816.15
Total residential area 4936.69 2489.48 2665.92 5661.93 Forest 4168.85 2487.7 3035.86 16700.32
Green urban areas 853.24 399.2 462.06 1288.32
Water bodies 842.72 639.52 518.87 3096.19 Per capita green space 27.25 10.97 13.71 32.95 (m² per inh.) Per capita green +forest 233.97 137.39 157.52 1277.95 (m² per inh.) per capita water area 32.52 28.01 27.05 229.18 (m² per inh.)
The spatial differentiation of total urban green and forest areas in the different European regions is also reflected in accessibility values. Figure 11 shows a European map in which the share of population which has access to green and forest areas of a minimum size of 2 ha within a 500 m distance. More than two thirds of the population living in Scandinavian countries or in countries in Western Europe such as Austria or North-Western Germany has access to green space in their vicinity. In addition, a number of cities in the Eastern European countries of Poland, Slovakia and the Czech Republic show high values. Notably cities in Southern-Eastern or Southern European countries show comparatively low values. In a number of cities in Hungary, Bulgaria or Romania only one third or less have access to UGS ≥ 2 ha within a 500 m distance from their home. This is also the case for Southern European cities notably in Greece and some cities in Italy and Spain. Those cities in Eastern and South-Eastern European countries with lower accessibility values may lack a sound green space management after their entry into the market economy and new construction dominates the land use change. For Southern Europe, the traditional built density of the cities comes together with higher efforts to maintain green spaces under conditions of con- siderable summer aridity. Moreover, Southern European cities’ area contains considerable rock surface.
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Figure 11: Share of population with access to UGS (≥2 ha) within 500 m in administrative city boundaries. Note: Calculation based on GEOSTAT 1 km² grid and Urban Atlas land cover data.
3.2.2 Urban Learning Lab scale
The ULL cities in GREEN SURGE are Berlin, Malmö, Ljubljana, Edinburgh, and Bari. In this Mile- stone, we additionally studied Łódź as an Eastern European city. Berlin is the largest city with more than 89,000 ha (Table 9). Residential area in Berlin comprises nearly 30 % of the city area while open spaces including forest areas, green spaces and water bodies do also represent nearly 30 %. Among all case study cities, Berlin has the highest popula- tion number with more than 3.5 million inhabitants. Per capita green space (including forest and urban green) is high with more than 60 m² per inhabitant. Malmö in Sweden is one of the smaller case study cities. The city had around 313,000 inhabitants by 2013. Share of UGS is comparatively high which results in a value of 36 m² per capita green space (including forest areas). Ljubljana is the capital of Slovenia. The city has only 248 ha of UGS but a very high forest area of more than 11,000 ha which is based on its topographical situation. Ljubljana’s population was
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280,600 in 2013. Per capita green space is comparatively low with around 9 m² per inhabitant while it is very high when also forest areas are considered (422.30 m²/inh.) Bari, situated in Italy is the smallest case study city with around 11,000 ha. Forest area is small with only 7 ha while UGS comprise 182 ha. With around 313,000 inhabitants per capita green space is calculated with around 6 m² and is the lowest value among the cities. Bari also only comprises 5 ha of water bodies within administrative city boundaries. The Scottish city of Edinburgh is situated in northern UK. The city had nearly half a million in- habitants in 2013. More than one fifth of the city area is residential area. Around 3,000 ha of land are UGS and forest areas. Per capita UGS is relatively high with 31 m² per inhabitants and even higher is the value when forest areas are considered as well. Finally, the city of Łódź in Poland is the second largest city of the case studies with around 719,000 inhabitants. Per capita values for UGS and forest areas are similar to those of Berlin with 12.5 and 60.0 m² per inhabitant respectively. Figure 12 shows the land use values as share of the total city area for the ULL cities.
Table 9: Area of land cover/land use in the ULL case study cities. Edin- City Berlin Malmö Ljubljana burgh Bari Łódź
Total area Urban Atlas (ha) 89,042 15,309 27,563 26,218 11,374 29,428 Residential area (ha) 28,791 3,060 3,122 5,424 1,992 6,720 Green space (ha) 5,727 1,029 248 1,515 182 898 Forest (ha) 15,578 107 11,602 1,379 7 3,417 Water area (ha) 5,077 184 273 260 5 59 Population nr. 2013 (in 1000) 3,502 313 281 483 313 719 per capita green (m²/inh) 16.35 32.86 8.85 31.39 5.81 12.50 per capita green + forest (m²/inh) 60.84 36.28 422.30 59.97 6.04 60.03 per capita water area (m²/inh) 14.50 5.87 9.72 5.38 0.15 0.82 Share of pop who has access to 67.66 84.08 56.79 88.32 21.44 75.79 green space (2 ha within 500m)
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Figure 12: Land use/cover as share of total area based on Urban Atlas 20006 (EEA, 2010).
Figure 13 shows the results of the accessibility calculations for the case study cities. For the in- terpretation of the accessibility values presented in the maps it has to be noted that they show all grid cells in colour which are within a distance to a 2ha green space. The respective colour of the grid cell (from yellow to red) shows the number of people living in that grid cell. Thus, the colour simply represents the number of people in that cell but says nothing about quality of access (in terms of “good” or “bad” access) or a certain share of people with access. As an example: if a grid cell is within a 2ha green space distance of 500m and has a high population number (of more than 6000), this grid cell is represented in red. Again, they reflect the results from the total and per capita values. Berlin as the largest city of the sample has a high share of UGS. Over the whole city area, high numbers of residents have access to green space in their vicinity. Similar results were found for Ljubljana, Edinburgh and Malmö. In Łódź, notably people living near the city border have access to forest areas and those living in the inner parts of the city to green urban areas. Bari shows only some areas in which people have access to urban green of a minimum size of 2 ha.
For any conclusions in terms of green space provision within the ULL cities, it needs to be men- tioned again that in the calculation of all cases only the Urban Atlas classes “forest” and “green urban areas” were included because of the mentioned shortcomings in the data base. Therefore, cemeteries, allotment gardens, green sports areas and brownfield sites could not be included. These land uses are summarized in other classes such as “industrial, commercial, public, military and private units” where no further distinction is made. The raster-based type of analysis does not include the road and path network of the cities and show always the “bird’s eye view”.
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Figure 13: Accessibility of urban green and forest areas of a minimum size of 2 ha within 500 m distance. Note: In colour are only those grid cells which are within a distance to a 2ha green space. The respective colour of those grid cells represents the number of people living in that grid cell. Calculation is based on GEOSTAT 1km² grid and Urban Atlas land cover data. No street or public transport net was included in the analysis.
At district level, UGS distribution (including forest areas) is different. Figure 14 shows per capita green space and population density values for the districts of Berlin, Germany and Ljubljana, Slovenia. In Berlin, districts situated near the city border have higher shares of urban green and notably forest areas as in the southwest of the city. Accordingly, per capita values are high in these districts. By comparison, the map of the population density shows that density is highest in inner city areas. This is also the case for Ljubljana although population density values are overall lower than in Berlin. Per capita values for urban green and forest areas are highest in the north and the east of the city with values of more than 500 m² per inhabitant. These per capita values represent the land use distribution in the city. Share of forest area is high in those districts near
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the city border and population numbers are low. Per capita values, thus, result to be exceptional- ly high in these areas.
Figure 14: Per capita green space (m²/inh.) and population density at district level for the ULL cities Berlin and Ljubljana.
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4 DISCUSSION
4.1 Urban green space elements inventory
In total, 44 UGS elements were identified and grouped into eight broad categories (see, e.g., Table 4). This categorisation is not a typology in a strict sense and alternative ways of grouping the UGS elements are possible and legitimate. Alternative possibilities for structuring could include physical appearance, spatial extent and spatial complexity, social function, ownership and access, quantity and quality of ecosystem services they provide, role for biodiversity conservation, the intensity of human influence, or relevant planning purpose and open space strategy. The eight groups identified here help structuring the inventory, but the focus of this deliverable and GREEN SURGE in general is on the single UGS elements and not on the categories. We defined the categories building greens; riverbank green; parks and recreation; allotments and community gar- dens; agricultural land; natural, semi-natural and feral areas; blue infrastructure; private, com- mercial, industrial, institutional UGS; and UGS connected to grey infrastructure.
Many UGS elements are too small to appear in data that covers the whole EU (e.g. green roofs). Some categories are probably to fine for the ULL level of GREEN SURGE (e.g., it might not be known whether green roofs are extensive of intensive). In that case, the UGS elements can be combined with each other (intensive and extensive green roofs green roofs). Other UGS ele- ments might be too broad for some purposes, in particular forests2. Here we recommend split- ting these elements into sub-elements (e.g., forest coniferous and deciduous forest). Larger UGS, like parks are often composed of many structurally and functionally different subunits such as playgrounds, sport grounds, forest patches, small botanical gardens, lakes and streams, me- morial sites, orchards, etc. Such UGS, however, possess ecosystem services stretching beyond the services of individual subunits and it is reasonable to maintain in the inventory both levels of scale.
4.2 Ecosystem service provisioning by urban green space
As shown in Table 4 - Table 6, a wide range of ESS are provided by various UGS elements. Not all ESS are equally well represented in terms of empirical or model-based knowledge about their performance. The performance of UGS very much depends on the specific configuration and the spatial context (Ahern 2007), so tables provide a simplified picture. Nevertheless, the knowledge about the effects of some UGS elements is considerable, for example for green roofs and green walls and of more classical elements of UGS like forests and parks. Particularly green roofs pro- vide a number of ESS, ranging from air temperature regulation and respective cost savings for heating and cooling up to rainwater infiltration and habitat provision. They have the potential to act as a kind of “second green skin” of cities with dense centres and limited open space on the ground. The assessment also shows the importance of many UGS for habitat provisioning.
2 Forests can be categorized according to their age, species composition, usage, etc. For some aspects, like recreation, it may not make a difference whether a forest is deciduous or coniferous, and therefore the UGS element “forest” is sufficient. For other aspects, like ecosystem service provisioning, the species composition or age of a forest is highly influential and the UGS element should be further divided.
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For most UGS elements, more information on ecosystems service provisioning will be filled in throughout the project as empirical and modelling analyses in GREEEN SURGE are ongoing. Looking forward, D3.2 will provide more knowledge about the health effects of UGS in cities as one specific and upcoming issue in the urban ESS and UGI discussion. In addition, assessments of ecosystem services and biodiversity for combinations of different UGS in GI will also be made throughout the project. For some elements, however, the link to ecosystem service production and biodiversity depends on a range of factors (e.g., the bird diversity of parks depends on man- agement and vegetation structure) and on how they are integrated into UGI.
4.3 Assessment of urban green space demand for the two scale levels, Urban Learning Lab and European Urban Atlas cities
The results of the calculation for the demand of UGS show a heterogeneous picture across the EU. The ULL cities, which act as case studies in the GREEN SURGE project stand as an representa- tive example for the general trend of values in Western, Southern, Eastern and Northern urban Europe.
Accordingly, the low forest and tree cover in Southern Europe explains the below-average per capita urban green and accessibility values in Southern European cities such as in Bari. Addition- ally, cities along the Mediterranean coastline have a high degree of soil sealing and rock surface, which further explains lower values for green space accessibility (Kasanko et al., 2006).
The above-average values for green, forest and water areas in Northern European cities result from the biophysical conditions and the forest richness of the respective countries in general. Malmö as the Swedish case study city in Northern Europe is situated at the Baltic see. It has the highest share of water area and respectively high per capita water area.
Western European cities present a diverse picture. Whereas in many cities, urban sprawl reduc- es green space of any type outside the core cities, in their inner parts, green spaces have been started to be better preserved and enhanced. Some cities do have a very high share of UGSs such as Berlin. This is mainly due to an increased awareness of planning, protecting and investing in nature has been developing in the last years. Further, an increase in ecological ‘‘green’’ lifestyles such as urban gardening activities are appearing in cities such as Berlin and may lead to the di- verse picture of green space provision and access.
Łódź is an example of an Eastern European city. Per capita values are below average but still represent a certain provision of urban green and forest areas for city residents. The accessibility map however shows that a number of inhabitants benefit from access to green. Larondelle et al. (2014) concluded that for the case of Eastern European cities, the ecosystem services provision based on green land use is very dynamic and hard to predict. Authors noted that biophysical pre- conditions are different according to location in Europe making comparisons between, for exam- ple, the more Mediterranean Bulgarian cities and semi-continental cities in Poland and the Czech Republic difficult.
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Data issues Due to the broad focus of this Milestone, green space was defined rather narrowly based on Ur- ban Atlas classification. Only those areas were included in the analyses which are represented in the two Urban Atlas classes “forest” and “green urban areas”. Due to the classification in Urban Atlas, which summarizes different land uses in one class, important green spaces such as ceme- teries, allotment gardens or green brownfield sites could not be included. Future research within GREEN SURGE will look at how different green spaces (including cemeteries or allotment gar- dens) can supply the demand for ecosystem services by residents. For a detailed analysis, land use maps with higher resolution will be used at ULL scale.
Finally, accessibility threshold values are differently used in literature. Thus, a comparative anal- ysis using different threshold values such as a 300 m distance for 2 ha or a 1500 m distance for 50 ha as well as the inclusions of a street network is planned for future work.
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6 SUPPLEMENT
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