One Ecosystem :
Research Article
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Corresponding author: Grazia Zulian (graziaz@live.com)
Academic editor: Davide Geneletti
Received: 06 Aug 2021 | Accepted: 31 Jan 2022 | Published: 11 Mar 2022
© 2022 Grazia Zulian, Federica Marando, Lorenzo Mentaschi, Claudia Alzetta, Bettina Wilk, Joachim Maes
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Zulian G, Marando F, Mentaschi L, Alzetta C, Wilk B, Maes J (2022) Green balance in urban areas as an indicator for policy support: a multi-level application. One Ecosystem 7: e72685. https://doi.org/10.3897/oneeco.7.e72685
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Green spaces are increasingly recognised as key elements in enhancing urban resilience as they provide several ecosystem services. Therefore, their implementation and monitoring in cities are crucial to meet sustainability targets.
In this paper, we provide a methodology to compute an indicator that assesses changes in vegetation cover within Urban Green Infrastructure (UGI). Such an indicator is adopted as one of the indicators for reporting on the key area “nature and biodiversity” in the Green City Accord (GCA).
In the first section, the key steps to derive the indicator are described and a script, which computes the trends in vegetation cover using Google Earth Engine (GEE), is provided.
The second section describes the application of the indicator in a multi-scale, policy-orientated perspective. The analysis has been carried out in 696 European Functional Urban Areas (FUAs), considering changes in vegetation cover inside UGI between 1996 and 2018. Results were analysed for the EU and the United Kingdom. The Municipality of Padua (Italy) is used as a case study to illustrate the results at the local level.
Over the last 22 years, a slight upward trend characterised the vegetation growth within UGI in European FUAs. Within core cities and densily built-upcommuting zones, the trend was stable; in non-densely built-up areas, an upward trend was recorded. Vegetation cover in UGI has been relatively stable in European cities. However, a negative balance between abrupt changes in greening and browning has been recorded, affecting most parts of European cities (75% of core cities and 77% of commuting zones in densely built-up areas). This still indicates ongoing land take with no compensation of green spaces that are lost to artificial areas.
Focusing on the FUA of Padua, a downward trend was observed in 33.3% and 12.9% of UGI in densely built-up and not-densely built-up areas, respectively. Within the FUA of Padua, most municipalities are characterised by a negative balance between abrupt greening and browning, both in non-densely built-up and densely built-up areas.
This approach complements traditional metrics, such as the extent of UGI or tree canopy cover, by providing a valuable measure of condition of urban ecosystems and an instrument to monitor the impact of land take.
urban ecosystems, urban ecology, urban green infrastructure, change detection, NDVI, no net loss indicators
Urbanisation is a complex territorial process that refers to changes in the population distribution and to a transformation of the environment (
Urban ecosystems are defined as socio-ecological systems where most people live (
The condition of urban ecosystems affects human well-being (
The role of urban areas in addressing environmental issues is increasingly being recognised in European policies and international commitments, such as the post-2020 Global Biodiversity Framework*
Interestingly, cities take centre-stage in this strategy. Section 2.1 focuses on the development of "A coherent network of protected areas", expressing the need to enlarge and improve the "Trans-European Nature Network". In this context, UGI is acknowledged for its pivotal role in supporting Trans-European network connectivity, especially in dense urbanised areas. Section 2.2 outlines the "new EU Nature Restoration Plan" and provides ten spheres of action to "improve the health of existing and new protected areas, and bring diverse and resilient nature back to all landscapes and ecosystems". One of the areas of interests are cities. Section 2.2.8 specifically refers to “greening urban and peri-urban areas” to halt and reverse the loss of urban green . Cities with more than 20,000 inhabitants are called on to develop an Urban Greening Plan to increase urban biodiversity and improve UGI, such as forests, parks and gardens. To facilitate and support the process in 2021, the Commission initiated the “Green City Accord” (GCA)*
For monitoring the nature and biodiversity section, signatory cities will report on five mandatory indicators which should be easy to assess and monitor. One of them is "changes in vegetation cover in UGI".
The analysis of changes in vegetation cover is a common methodology, applied at a national (
Traditionally, UGI is analysed by reporting the extent of urban green, measured with reference to the city area (% of urban green) or as m2 per inhabitants (
However, the above-mentioned indicators do not capture the presence, health and dynamics of vegetation that determine the delivery of ecosystem services and provide habitats to fauna. The analysis of changes in vegetation cover, therefore, complements other metrics that report on the share of restored and protected semi-natural and natural urban areas and proximity of public green spaces to citizens. The approach is implemented in several studies. To cite only a few examples:
Several review papers and real-world experiences demonstrated that simple indicators are preferred for policy support. To cite just a few examples:
Amongst social indicators the authors report:
Other examples of indicators to measure urban green or urban biodiversity come from Manchester and Lisbon. Manchester uses “Percentage green infrastructure cover” and “Percentage of tree canopy cover” (
Here, we argue that the analysis of long-term trends in vegetation cover should be part of an indicator framework to monitor urban sustainability and urban green. Yet, the long-term assessment of vegetation cover at the urban scale requires high scientific-technical skills and associated indicators may be complex, which has implications for their communication. Hence, this might explain why indicators that quantify long-term vegetation trends are not regularly included amongst the indicators used for urban policy-making and planning.
This study fills this gap by providing a framework for the analysis of changes in vegetation cover inside UGI. The framework was developed and implemented from a policy-support and decision-making perspective. Additionally, a java-script for the automatic computation of the trend analysis on the Google Earth Engine (GEE) platform is included.
The methodology allows users to monitor land use change and land compensation, as well as the availability and quality of different typologies of urban green. Thus, it could serve as a decision support tool for the design and implementation of "no net loss" policies (
Since the analysis covers multiple governance levels and scales, from urban park to district, from municipality to European level, it further supports the harmonisation of methods and data needed to provide information for policy-making and for monitoring of implementation across scales (
The objectives of this paper are to:
The methodology was implemented in all European Functional Urban Areas (FUAs). For demonstrative reasons, an additional analysis was done at the metropolitan and sub-municipal level.
To illustrate the approach and to test its applicability in a multi-scale perspective, the model was implemented in 696 European Functional Urban Areas (FUAs), situated in the European Union (EU) and the United Kingdom (UK). During the study period, the UK was a member of the EU. Therefore, the EU and UK are abbreviated to EU-28. Three geographical levels are analysed: the European, metropolitan and municipal level.
FUAs were selected to represent the most urbanised areas in Europe. FUAs are cities and their commuting zones, composed of high-density urban centres with at least 50 thousand people, plus their surrounding commuting zones. Commuting zones are defined as all municipalities with at least 15% of their employed residents working in a certain city core (
At EU level, areas dominated by the presence of artificial land inside FUAs increased by 3.2% between 2000 and 2018 (EU-28) (
The FUA and the City of Padua have been selected as demonstrative case studies to represent the metropolitan and municipal level, respectively. Padua is located in the Po Valley between Vicenza and Venice, in the Veneto Region, northern Italy. The metropolitan area is a highly urbanised zone, with a densely populated core city and a commuting zone consisting of municipalities with different characteristics. The FUA's commuting zone includes 30 relatively small municipalities and, while hosting important protected areas (Parco dei Colli Euganei, Parco della Brenta, both Natura 2000 sites), has been characterised in the last 50 years by a polycentric process of urbanisation that fully transformed the peri-urban traditional agricultural landscape (
Padua is a town, rich of history and culture. It is one of the oldest towns in northern Italy and an important academic, economic and industrial centre. The Municipality of Padua experienced a population loss after the 1990s (-2.32% per decade between 1991-2018); nevertheless, this trend has been reversed in recent years (+ 0.22% between 2015 and 2018) (
At the municipal scale, changes in vegetation cover inside UGI were analysed at the district level. Additionally, show cases were prepared to demonstrate the effectiveness of the approach to monitor public parks. Three parks, located in different districts were selected: Park Europa (district 3); Tamanza Playground (district 2) and Girasoli playground (district 5).
Park Europa is the result of depaving and re-naturalisation of a previously-sealed surface. A century ago, this district of the city underwent a sudden development following the construction of the trade fair and several industrial factories. Here in 1920 stood a chemical factory for the transformation of cellulose into a textile fibre. The factory operated until the 1970s when it closed. Then the buildings remained abandoned and unused for decades. In the early 2000s, it was decided to convert the area into a park: the buildings were demolished and the process of decontamination of the land started. In the meanwhile, a group of architects, foresters and landscape painters began to work on the project. Tree planting was carried out in 2005 (
Temanza playground is a small area located in a densely built district which has been converted into a public pocket park in the early 2000s. The pre-existing arboreal vegetation consisted then of nine adult trees: four cedar trees and five plane trees (
Girasoli playground, located in a a vast district in the southwest of the city where agriculture interlaces with built areas. In the early 2000s, a surface of about four hectares became a public property and, in 2008, it was converted into an urban agricultural park. *
Fig.
The indicators, described in this paper have been initially developed as part of the EU Ecosystem Assessment which presents an analysis of ecosystems covering the total land area of the EU, as well as the EU marine regions (
Greenness is defined as "the amount of vegetation present in urbanised areas" (
A GEE java-script is provided, which estimates the levels of greenness (defined as the fraction of land surface covered in vegetation) and greenness trends over an urban context of choice.
The script contains the procedure needed to:
Create a raster image collection of annual urban greenness. The image is generated between 1995 and today, by merging together values calculated from the LANDSAT imagery. The user can select a preferred time-frame, but cannot precede the year 1982, when the LANDSAT 4 mission was launched.
Create a “green-mask”, estimated from the values of yearly greenness. The green mask identifies the pixels that, at least once in the observed time-frame, are classified as green (see section “Urban Green Infrastructure” for additional details) (Step B).
Perform a linear regression at the pixel level using the Theil–Sen estimator (
The output is then stored to the user's Google Drive. The user will be able to complete the calculation for the final indicators (Step D and E) using any GIS software.
Suppl. material
Urban greenness, or the amount of urban vegetation, comprises the UGI. Urban greenness is represented by public and private green spaces, characterised by different uses and management practices.
From the original greenest maps, the UGI mask was created by selecting the areas where, at least once between 1996 and 2018, the highest NDVI value was greater than 0.4 (Fig.
Similar thresholds are widely used to discriminate between moderate vegetation levels and highest possible vegetation density.
Trend detection in NDVI time series helps identify and quantify recent changes in ecosystem properties.
Changes in greenness can come from different sources and present distinct characters for what concerns the direction of change and the intensity (
Gradual changes:
Abrupt changes:
Therefore, the “greenness change” corresponds to gains or losses in urban vegetation, considering the complete timespan (in this application from 1996 to 2018). A similar methodology was applied by
The trend analysis employed a non-parametric approach, namely the Theil–Sen regression (Fig.
C.2 Average Greenest 2010: the average value of greenest in 2010 was extracted and used as reference year to be consistent with the methodology implemented to analyse trends in ecosystems condition at EU level (
C.3 From the Theil–Sen positive or negative slope represents the Delta Greenest, the changes in vegetation cover over 22 years.
C.4 Greenest % change per decade: to make the interpretation easier, changes in vegetation cover were reported as percentage of change per decade (using the equation proposed by
The “greening-browning balance” represents the difference between share of UGI (%) where major upward and downward trends in vegetation cover take place. A negative balance means browning; a positive balance means greening.
In particular, a negative balance occurs in case of vegetation loss. This phenomenon is called “Abrupt browning change”, generally caused by a relatively fast land-use change, by land-take with no compensation policies in place or by extreme weather and climate events (
On the other hand, a positive balance occurs in case of relatively rapid vegetation growth. In urban areas, an “Abrupt greening change” is due to the implementation of nature-based solutions (e.g. new urban green areas or intensive urban green space management), sustainable compensation strategies in case of land-take or changed climatic conditions (
Similar methodologies were applied by other author s. As an example,
The Theil-Sen Slope (Fig.
Thresholds used to classify five change classes (derived from
Class | Description |
NDVI ≤ -0.015 → major browning | Downward trend (Browning) due to housing policies, development of industrial and commercial areas, new grey infrastructures |
-0.015 < NDVI ≤ -0.0001 → slight browning | |
-0.0001 < NDVI ≤ 0.0001 → no changes | Stable vegetation |
0.0001≤ NDVI ≤ 0.007 → slight greening | Upward trend (Greening) due to green infrastructure management; vegetation growth, climate change |
NDVI > 0.007 → major greening |
The difference between major greening and major browning represents a proxy of “compensation measures”. If the difference is positive, the upward trend is higher than the downward trend and greening areas compensate for the loss of green spaces due to land development or other processes. If it is negative, the land development pattern did not include any solution to compensate for the green loss.
The vegetation trend analysis, described above, was conducted at pixel level.
Indicators were computed and extracted using specific reporting units, which depend on the geographic level of the analysis (for instance, core city and commuting zone at EU level, municipalities or districts at metropolitan or municipal level).
Two additional zonations were established: “densely built-up areas” (DB) and “not densely built-up areas” (NDB) using the Land Mosaic model available in the Guidos Tool box modelling suite (
The Landscape Mosaic (LM) is a tri-polar classification of a location accounting for the relative contributions of three main land cover types: agriculture, natural and artificial in the window surrounding that location. The LM is based on a “focal operation”: “Using neighborhood values from within a single raster, focal operations compare the neighborhood to one cell, then move to the next cell and compare a new neighborhood, and so on with the intention of finding a relationship or pattern which occurs within one raster”3. The size of the “moving window” is the most important parameter of this type of model because it affects the detected degree of spatial variability.
For this application, a moving window of 2.5 km2 was chosen, considering three aspects each linked to one of the three land cover types:
Additional details are provided in Suppl. material
Indicators were computed at pixel level and reported using only significant pixels (p < 0.05) inside the UGI. We included an additional level of analysis to demonstrate how the approach can be applied at neighbourhood level in a planning context. In addition, at the municipal level, urban public parks and gardens were evaluated to explore the effectiveness of this analysis as a support of local policies and management practices. Public parks and gardens are, in fact, the "heart" of accessible green spaces, the spaces where, besides regulating and provisioning services, people can actively enjoy nature. From a methodological point of view, there has been the interest to explore to what extent the indicator can be used at the municipal level for assessing nature-based solutions. Significant pixels inside public green areas were extracted and recoded by direction of change. Parks were reclassified per type and by direction of change. Parks, characterised by an abrupt greening, were analysed with regard to population living in their proximity (500 m) to see how the dynamic affects beneficiaries of ecosystem services. In addition, a qualitative analysis of a selection of public parks, characterised by an abrupt greening, was also performed using the technical documentation provided by the Municipality of Padua.
The analysis was complemented by demographic and land-composition indicators that provide a context for the interpretation of the results. In fact, European cities are extremely diverse in terms of spatial configuration, size and population dynamics and these facts are essential to fully understand the value of urban greening.
At the EU level, indicators were derived from previous studies and computed ad hoc. Population density within core cities and commuting zones and the land composition analysis were part of the EU ecosystem assessment (
At the municipal level, population density and changes in population at census and municipal level were implemented using data derived from national and regional statistics (
The aim of this study was to implement a replicable approach to assess the urban vegetation changes in a multi-scale perspective. For this reason, only consistent and open source data were used. Table
Data | Data owner | Reference | Levels |
Corine Land Cover | European Environment Agency |
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EU-metropolitan-local |
LANDSAT - collection | Chander et al. (2009) Google Earth Engine Data Catalogue (2018) |
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EU-metropolitan-local |
Tree cover density (2018) | European Environment Agency |
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EU-metropolitan-local |
FUA Urban Audit (2018) | GISCO |
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EU-metropolitan |
GHS-SMOD Degree of Urbanisation | JRC |
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EU-metropolitan |
Population -European level | EUROSTAT |
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EU |
Population - FUA level | ISTAT (Italian Statistical Institute) |
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metropolitan-local |
Population-municipal Level | Regione Veneto |
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metropolitan-local |
Districts of Padua | Municipality of Padua |
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local |
Public parks of Padua | Data received from "Settore Verde" Municipality of Padua | Municipality of Padua | local |
Land-cover data, used to establish the zonation (as described above), was derived from Corine Land Cover (CLC). CLC uses a Minimum Mapping Unit (MMU) of 25 ha for areal phenomena and a minimum width of 100 m for linear phenomena and is available at a 100 m resolution (
In this application, we did not use the Urban Atlas for three reasons:
The Urban Atlas provides the extent and form of forest, semi-natural vegetation, herbaceous vegetation and urban green. It does not allow the detection of small green patches.
The Urban Atlas is available only for 2006 (but only 319 Large Urban Zones (LUZ) are available (see the technical*
The Urban Atlas does not allow us to consider what is happening immediately outside a FUA's boundaries which is very important when assessing urban ecosystems. In Europe, many border FUAs exist, for instance, Vienna (Austria) and Bratislava (Slovakia). In this case, the LM approach may give wrong results if applied using Urban Atlas.
Data on urban green were derived from GEE. The Greenest_TOA (from now on called greenest) product was chosen. These composites are created for all the scenarios in each annual period beginning from the first to the last day of the year. All the images from each year are included in the composite, with the greenest pixel as the composite value, where the greenest pixel means the pixel with the highest NDVI value (
The FUA limits were derived from the URBAN AUDIT catalogue, version 2018.
Data used for the multi-scale assessment of Padua (FUA and Municipality) were provided by the Municipality of Padua and the Italian Institute of Statistics (
GIS and statistical analysis were carried out in GRASS-GIS 7.8 (
Results are reported in a multi-level perspective. Fig.
European level, 696 FUA (EU-28) were analysed;
Metropolitan level: the FUA of Padua, was analysed with reference to the core city and the 30 municipalities of the commuting zone.
Municipal level, results were reported at the district and the public parks level. Districts are important intermediate sub-administrative units for local level actions and activities (
Table
Significant pixels (%) |
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Core city (696 cities) | Commuting zones (608) | |||
EU level |
FUA total |
49.56 | 52.38 | |
FUA average |
54.12 | 54.18 | ||
FUA - level |
Core city (Padua) | Commuting zone (30 municipalities) | ||
FUA of Padua |
50.03 | 42.85 |
At the public green spaces level, 1396 pixels (125.64 hectares) with significant values were extracted and evaluated.
Table
NDVI (greenest) average |
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Reporting unit |
Core city (N: 696) |
Commuting zone (N: 608) |
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Densely built (DB) |
Not-densely built (NDB) |
Densely built (DB) |
Not-densely built (NDB) |
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EU FUA |
0.44 |
0.58 |
0.45 |
0.59 |
FUA of Padua |
0.37 |
0.51 |
0.41 |
0.53 |
Fig.
At EU level, the average value of greenest in 2010 within core cities is, as expected, slightly lower than in the commuting zone.
Remarkably, the values reported in DB areas and NDB are very similar in core cities and commuting zones. There are countries, such as Italy, Greece, Luxemburg, Slovakia and Czechia, where the greenest average values are practically equal in UGI, situated within DB areas, both in core cities and commuting zones. In Portugal and Spain, the values are slightly higher within NDB areas of core cities. The DB areas show lower values also in the FUA of Padua and within the districts of the Municipality. Noticeably, the FUA of Padua presents values below the EU average. This could be related to the intense process of urbanisation and sub-urbanisation that characterised the areas after the second World War (
In Padua (at FUA and Municipal level), the land covered by UGI was used to map local results to provide the order of magnitude of the local UGI. As expected, UGI in DB areas cover a relatively small area in almost all the municipalities, both in absolute and relative terms. Additionally, the average greenest values do not exceed 0.5, which represent a sparse vegetation cover. Noticeably, UGI in DB areas is present only in 58% (18) of the municipalities assessed.
In NDB areas, the UGI was present in all the municipalities. The size of UGI is larger with respect to DB (8.9 km2 on average) and covers a higher share of the reporting unit (45.8% on average). Only green areas close to built-up areas were included in UGI for this specific application. For this reason, in municipalities, such as Teolo and Montegrotto Terme (close to the Colli Euganei Regional Park), the forest was not included.
Fig.
At the FUA level, 13 municipalities over 31 (41.9%) lack of UGI in DB zones. Where the UGIs exist, the average greenest value is relatively low compared with the values in NDB areas. In Fig. 3c, data are presented at the district level. The Municipality is characterised by an uneven distribution of UGI, in terms of size and average greenest value amongst the districts.
Over the last 22 years, a general slight upward trend characterises the vegetation growth within UGI in European FUAs. Results at all geographical levels at all reporting units are reported in Table
Change in vegetation cover inside UGI (% per decade). Average values are reported at EU level and FUA level.
Long-term trend (% per decade) | ||||
Reporting unit | Core city (696) | Commuting zone (608) | ||
Densely built | Not-densely built | Densely built | Not-densely built | |
EU FUA |
0.098 |
0.227 |
0.45 |
0.59 |
FUA of Padua | 0.05 | 0.2 | 0.006 | 0.13 |
The upward trend is gradual over time, probably due to climatic conditions. Within DB areas in core cities and commuting zones, the trend is stable (average value for EU cities is between 0.098 and 0.013% per decade in DB areas, respectively in core cities and commuting zones); in NDB areas, a relative upward trend is recorded (average value for EU cities is between 0.227 and 0.24% per decade in DB areas, respectively in core cities and commuting zones). The pattern applies predominantly to Mediterranean and Eastern countries.
At the local FUA level (where reporting units are municipalities of the commuting zone and the core city), a downward trend was observed for 33.3% of the vegetation cover in UGI in DB areas and for 12.9% of the vegetation cover in NDB areas. On average, the vegetation cover tends to be stable (average 0.0 in DB areas and 0.14% per decade in NDB areas); maps of NDB areas are reported in Suppl. material
At the district level, only the third district shows a clear downward trend (Fig.
A negative balance between abrupt changes (greening and browning) has been recorded at EU level. A negative pattern is a sign that, in general, European cities did not undertake the indispensable initiatives needed to maintain an efficient UGI and no clear compensation policies have been implemented. A synthesis of balance between abrupt greening and browning at all geographic levels is presented in Table
Balance between abrupt and browning changes at all levels. The balance is expressed as the difference between share of UGI (%) where major upward and downward trends in vegetation cover occur. A negative balance means browning; a positive balance means greening.
Balance between abrupt greening and browning | ||||
Reporting unit | Core city (696) | Commuting zone (608) | ||
Densely built | Not-densely built | Densely built | Not-densely built | |
EU FUAs | -4.36 | -0.48 | -6.36 | -0.07 |
FUA of Padua | -6.57 | -2.81 | -7.97 | -4.90 |
Fig.
At the local FUA level, 29 municipalities over 31 (93.5%) are characterised by a negative balance between abrupt greening and browning in NDB areas; 16 municipalities over 18 (88.89%) present a negative balance in DB areas. In DB areas, the negative balance characterises also municipalities covered by Natura 2000 sites. At the district level, this pattern is particularly clear in the NDB areas zone (maps of NDB zones are reported in Suppl. material
A total of 1396 pixels with significant values were extracted and evaluated. For 46 over 1396 pixels, a negative change per decade (abrupt browning) is observed (3.29%). This is due to the construction of new facilities (for instance, playground areas or toilets, inside the parks). A total of 1209 over 1396 (86.6%) report a gradual increase, from 0 to 1% per decade. This can be considered a “natural” and expected gradual greening trend.
Fig.
Public parks types, direction of change and population in the close proximity of parks with abrupt greening changes.
The abrupt greening is mainly due to the opening of new parks and specific vegetation management.
A description of the case studies is presented in Table
Park | Park size (ha) | Share of park covered by significant pixels (%) | Change per decade (%) | Change per decade (% max value) | Greennest 2018 (avg) |
Park Europa | 4.80 | 79.31 | 1.35 | 2.53 | 0.60 |
Temanza Playground | 0.40 | 82.88 | 1.45 | 2.12 | 0.46 |
Girasoli Playground | 3.80 | 69.26 | 0.91 | 1.70 | 0.73 |
In Park Europa, tree planting was carried out in 2005. Since the Park was created from vacant land, the project intended to achieve two main objectives, that drove the tree selection: 1) the Park would greet visitors as soon as the last tree had been planted; 2) the Park would offer shade during the long and hot summers and, at the same time, would host different thematic gardens (food plants garden – siliceous hills vegetation – medicinal herbs – rain garden) and open spaces for concerts and meetings. In order to ensure that the tree cover grew quickly enough, fast growing tree species were selected (such as Populus ssp., Salix spp., Ulmus spp., Platanus spp.): they could ensure shady spots in a short time and accompany the slower growing of other tree species, chosen for their characteristics (for instance Quercus spp., Liquidambar). During the 15 years from its opening, no trees have been removed and tree cover has naturally increased due to the crown developing on young trees. Since Park Europa is an example of regeneration of built-up and disused urban land, it turns out to be definitely an abrupt greening, that gradually has increased from 2005 until the present day.
In Temanza Playground, until the year 2000, the plane trees branches had been periodically removed, according to an outdated pruning system called “pollarding” or “topping”. According to this pruning system, the branches are cut close to their head on top of a clear stem. The tree is then allowed to regrow after the cutting, but it must then be periodically pruned again, with the result of a periodical complete removal of the head of foliage and branches. Since 2005, the five plane trees have no longer been topped, their branches have regrown and regular maintenance has been done in order to respect them and to help the trees to reconstruct their crown. In the years since, the trees have developed a larger crown, with a stronger structural integrity and has resulted in a increased tree canopy cover. In 2012, new shrubs have been planted, together with 19 young trees which are constantly growing at a different growth rate according to the species to which each belong. The positive trend of the greening of this area is related to the combination of a change in the plane trees management (from topping to no-pruning) and to the introduction of new young trees, constantly developing their crown. Now, there is the co-existence between old trees from the now abandoned country hedges and the new plantations, that consist in tens of both fast-growing trees (Salix spp., Ulmus spp., Platanus) and slow-growing ones (Quercus spp., Acer spp.), both of them contributing to improving the greening of the area.
Girasoli playground has been developed in a former peri-urban agricultural land. Before the transformation, there were patches of arable land and linear country hedges (a mixture of plane tree, elm, maple, willow), which were managed in coppices for poles. New young trees were then planted in the plots previously used for cultivating crops and coppices were neglected, so that the ‘over-aged coppices’ have become single trees. This process explains the greening trend in this Park.
The analysis confirms previous studies that demonstrated a decline of urban green with the increase of urbanisation (
We documented a general relative decrease in vegetation cover inside the most urbanised areas in Europe between 1996 and 2018. The vegetation cover remained, indeed, relatively stable in the long term, with a slight upward trend in not-densely built areas, either in core cities and commuting zones. However, when considering the difference between abrupt greening and browning, cities are characterised by a negative balance that can be interpreted in terms of an absence of clear green compensation policies and an imbalance between urban development at the expense of green spaces.
In addition, the loss of vegetation is part of a more complex dynamic, characterised by a progressive densification of settlements, the movement of population towards urbanised areas (
The FUA of Padua well represents the effects of the long urbanisation process that characterises north-east Italy. Urban expansion, developed since the 1950s (
At the municipal level, urban districts show an uneven distribution of UGI in terms of size, greenness and direction of change in DB and NDB zones. Interestingly, in DB zones only District 3 presents a negative balance. On the other hand, in NDB zones, a negative balance characterises districts 2, 3 and 4 (see Suppl. material
At the public green spaces level, the method allows us to monitor the management practices within public parks. The vegetation cover in public green is slightly increasing and, in 6.08% of the cases, this represents an abrupt greening. This is the case of the realisation of new parks or playgrounds as presented in the three local showcases, that improved the quality of local neighbourhoods.
Scholars have demonstrated that greenness in the proximity of residential areas is fundamental for human well-being (
There is an increasing body of evidence that urban ecosystems in good condition contribute to biodiversity conservation (
One of the main challenges in protecting and expanding high quality urban green spaces is conflicting interests in land use and high competition over space, especially in densely built-up urban areas.
Other strategies should include the preservation of mature existing trees (if in healthy status) (
An overall rule should be the development of effective urban green strategies developed in coordination with strategic and holistic plans that comprise the entire region (
The Greening-Browning-Balance provides valuable insight into the overall balance between green and grey areas (i.e. infrastructure, housing etc.) in the city. Showing progress towards the before-mentioned policies implies that the balance should be zero, i.e. no net loss of urban vegetation or positive, i.e. increase in urban vegetation. Thus, the indicator is suited to provide information for no net loss policies in terms of city performance and monitoring of distance to target. At the same time, it provides decision support with regards to future planning and development applications and policy instruments. The European Commission's Roadmap to a Resource Efficient Europe (
Another application of the indicator is policy evaluation. To put nature on a path to recovery in European cities, the collaboration of private parties will be essential, considering that private space, on average, makes up to the largest part of cities. Private spaces play an important role as stepping stones in ecological corridors and providing a diversity of habitats for biodiversity to thrive in cities. The indicators capture both private and public space and could, therefore, be used to evaluate if and to what extent any policy-promoting green spaces creation has taken effect.
In this paper, we analysed the trend of urban green areas in European cities, through a multi-scale approach. This framework provides an indicator to report the status of UGI under the Green City Accord. Furthermore, the scripts implemented in GEE deliver a simple, flexible and accessible tool, easily available for researchers, administrators and stakeholders, which is suitable to provide a policy-orientated instrument. The results of the study highlighted criticalities in the status and trend of UGI in Europe, as urbanisation is continuously increasing and compensation measures are currently lacking. The current picture of the situation is showing an imbalance between green areas and impervious surfaces, with an increase in the latter at the expense of the first. UGI and nature-based solutions more in general, are being recognised as critical assets in mitigating the detrimental effects of increasing environmental stressors, such as climate change and in counteracting the ecological crisis. For the first time, the importance of urban ecosystems for nature protection is emerging, with a growing body of policies aimed to protect and implement UGI. Cities nowadays can have a constructive role for nature protection, ecosystem restoration, biodiversity and ecosystems services, rather than being exclusively considered as sources of pressure or threats. Therefore, in view of the present and future measures that need to be undertaken in the EU, aimed to systematically integrate UGI in cities, it is essential to monitor changes in vegetation within a city, with instruments capable of providing timely and accurate information for policy support. It is worth noting that UGI within cities are multi-functional systems capable of providing different ecosystem services. Therefore, an effective management of UGI must take into account their inherent complex nature and be able to identify the most appropriate strategy, but this is dependent on the availability of site-specific and spatially-explicit information.
The document contains a tutorial to reproduce the model at the local scale
the document contains the maps of greenness and changes in vegetation cover in not densely built areas at EU level, FUA level and municipal level.
https://land.copernicus.eu/local/urban-atlas
Municipality of Padua-data requested for the study