Metadata Factsheet

1. Indicator name

Average share of the built-up area of cities that is green/blue space for public use for all.

2. Date of metadata update

2022-11-03 12:00:00 UTC

3. Goals and Targets addressed

3a. Goal

N/A

3b. Target

Target 12.

4. Rationale

The value of public spaces is often overlooked or underestimated by policy makers, leaders, citizens and urban developers. There are several reasons for this, such as lack of appreciation of the value of these spaces to the functioning of urban systems and quality of life, prevailing urban planning processes, the lack of resources, or understanding or capacity to use public space as a complete, multi-functional urban system. Often the lack of appropriate enabling frameworks, weak political will and the absence of the means of public engagement compound the situation.

The Sustainable Development Goals (SDGs) have for the first time provided a platform where public spaces can be globally monitored. Indicator 11.7.1 measures the share of land allocated to public spaces and the total population with access of these spaces by age, gender and disability. The share of land that a city allocates to streets and open public spaces is not only critical to its productivity, but also contributes significantly to the social dimensions and health of its population. The size, distribution and quality of a city’s overall public space act as a good indicator of shared prosperity. A well developed and properly designed network of streets increases connectivity, promotes walking and social interactions but also income, gender, race or disability status and one that promotes multiple activities not only encourages their use, but also contributes to the urban character and quality of urban life.

Cities that improve and sustain the use of public space, including streets, enhance community cohesion, civic identity, and quality of life. A prosperous city develops policies and actions for sustainable use of, and equitable access to public space. In many cities however, there has been neglect of public space - both in quantity and quality, which has been further exacerbated by uncontrolled rapid urbanization which has created disorderly settlement patterns with alarmingly low shares of public space, as well as a dramatic reduction of public spaces. There is a need to expand the ratio of land allocated to public spaces and improve their qualities to make cities and urban areas more efficient, liveable, prosperous, and sustainable. Reclaiming urban spaces for people encourages development of other street activities that bring life to a city. Equally, a well distributed and hierarchical system of open public spaces that can be accessed by all regardless of is part of how we can humanize our cities and make our streets and public areas more communal.

5. Definitions, concepts and classifications

5a. Definition

The following is the definition of the SDG 11.7.1 indicator and consequently there could be small variations in the definition for the’ Average share of the built-up area of cities that is green/blue space for public use for all’.

Indicator 11.7.1 has several interesting concepts that required global consultations and consensus. These include; built-up area, cities, open spaces for public use, etc. As a custodian agency, UN-Habitat has worked on these concepts along with several other partners.

City: A range of accepted definitions of the “city” exist, from those based on population data and extent of the built-up area to those that are based solely on administrative boundaries. These definitions vary within and between nations, complicating the task of international reporting for the SDGs. Definitions of cities, metropolitan areas and urban agglomerations also vary depending on legal, administrative, political, economic or cultural criteria in the respective countries and regions. Since 2016UN-Habitat and partners organized global consultations and discussions to narrow down the set of meaningful definitions that would be helpful for the global monitoring and reporting process. Following consultations with 86 member states, the United Nations Statistical Commission, in its 51st Session (March 2020) endorsed the Degree of Urbanisation (DEGURBA) as a workable method to delineate cities, urban and rural areas for international statistical comparisons. [1] This definition combines population size and population density thresholds to classify the entire territory of a country along the urban-rural continuum, and captures the full extent of a city, including the dense neighbourhoods beyond the boundary of the central municipality. DEGURBA is applied in a two-step process: First, 1 km2 grid cells are classified based on population density, contiguity and population size. Subsequently, local units are classified as urban or rural based on the type of grid cells in which majority of their population resides. For the computation of indicator 11.7.1, countries are encouraged to adopt the degree of urbanisation to define the analysis area (city or urban area).

Built-up area of cities: Conventionally, built up areas of cities are areas occupied by buildings and other artificial surfaces. For indicator 11.7.1, built up areas, as the indicator denominator has the same meaning as “city” (see definition of city above).

Public space: The Global Public Space toolkit defines Public Space as all places that are publicly owned or of public use, accessible and enjoyable by all, for free and without a profit motive, categorized into streets, open spaces and public facilities. Public space in general is defined as the meeting or gathering places that exist outside the home and workplace that are generally accessible by members of the public, and which foster resident interaction and opportunities for contact and proximity. This definition implies a higher level of community interaction and places a focus on public involvement rather than public ownership or stewardship. For the purpose of monitoring and reporting on indicator 11.7.1, public space is defined as all places of public use, accessible by all, and comprises open public space and streets.

Land allocated to streets refers to the total area of the city/urban area that is occupied by all forms of streets (as defined above). This indicator only includes streets available at the time of data collection and excludes proposed networks.

Open public space: is any open piece of land that is undeveloped or land with no buildings (or other built structures) that is accessible to the public without charge, and provides recreational areas for residents and helps to enhance the beauty and environmental quality of neighbourhoods. UN-Habitat recognizes that different cities have different types of open public spaces, which vary in both size and typology. Based on the size of both soft and hard surfaces, open public spaces are broadly classified into six categories: national/metropolitan open spaces, regional/larger city open spaces, district/city open spaces, neighbourhood open spaces, local/pocket open spaces and linear open spaces. Classification of open public space by typology is described by the function of the space and can include: green public areas, riparian reserves, parks and urban forests, playground, square, plazas, waterfronts, sports field, community gardens, parklets and pocket parks.

Potential open public space: the identification of open public spaces across cities can be implemented through, among other sources, analysis of high to very high resolution satellite imagery, from base-maps provided by different organizations (eg OpenStreetMap, Esri, etc) or as crowd-sourced and volunteered data. While these sources provide important baseline data for indicator 11.7.1, some of the identifiable spaces may not meet the criteria of being “accessible to the public without charge”. The term “potential open public space” is thus used to refer to open public spaces which are extracted from the above-mentioned sources (based on their spatial character), but which are not yet validated to confirm if they are accessible to the public without charge.

Streets are defined thoroughfares that are based inside urban areas, towns, cities and neighbourhoods most commonly lined with houses or buildings used by pedestrians or vehicles in order to go from one place to another in the city, interact and to earn a livelihood. The main purpose of a street is facilitating movement and enabling public interaction. The following elements are considered as streets space: Streets, avenues and boulevards, pavements, passages and galleries, Bicycle paths, sidewalks, traffic island, tramways and roundabouts. Elements excluded from street space include plots (either built-up), open space blocks, railways, paved space within parking lots and airports and individual industries.

Land allocated to streets refers to the total area of the city/urban area that is occupied by all forms of streets (as defined above). This indicator only includes streets available at the time of data collection and excludes proposed networks.

For more details and illustrations on the definition of the different types of open spaces considered for indicator 11.7.1 see SDG 11.7.1 step by step training module

(https://unhabitat.org/sites/default/files/2020/07/indicator_11.7.1_training_module_public_space.pdf)

5b. Method of Computation

The following is the definition of the SDG 11.7.1 indicator and consequently there could be small variations in the definition for the’ Average share of the built-up area of cities that is green/blue space for public use for all’.

The method to estimate the area of public space has been globally piloted in over 600 cities and this follows a series of methodological developments that go back to the last 7 years. The finalized methodology is a three-step process:

a) Spatial analysis to delimit the city/urban area which will act as the geographical scope for the spatial analysis and indicator computation;

b) Spatial analysis to identify potential open public spaces, expert consultations and/or field work to validate data and assess the quality of spaces and calculation of the total area occupied by the verified open public spaces;

c) Estimation of the total area allocated to streets

d) Estimation of share of population with access to open public spaces within 400 meters walking distance out of the total population in the city/ urban area and disaggregation of the population with access by sex, age and persons with disabilities

a.Spatial analysis to delimit the city/urban area

Following consultations with 86 member states, the United Nations Statistical Commission in its 51st Session (March 2020) endorsed the Degree of Urbanisation (DEGURBA) as a workable method to delineate cities, urban and rural areas for international statistical comparisons. Countries are thus encouraged to adopt this approach, which will help them produce data that is comparable across urban areas within their territories, as well as with urban areas and cities in other countries. More details on DEGURBA and its application are available here:https://unstats.un.org/unsd/statcom/51st-session/documents/BG-Item3j-Recommendation-E.pdf

b.Spatial analysis to identify potential open public spaces, ground verification and estimating their total area

This step involves mapping of potential open public spaces within the urban boundaries defined in step one above and estimation of their area. Identification of potential open public spaces is based on the spatial character of each space and is also informed by existing country/ city land use maps and open space inventories. To compute this component of the indicator, follow these steps:

  1. An inventory of Open Public Spaces should be the initial source of information. Additional legal documents, land use plans and other official sources of information can be used to complement the data from the inventory. If the focus urban area or city has a detailed and up-to-date database of its open public spaces, use the information to plot such spaces in GIS software and compute their areas. Where necessary, clean data to remove components which are not applicable in the computation of this sub-indicator (e.g. recreation areas which attract a fee such as golf courses, etc).
  2. Since many cities and countries do not have an open public spaces inventory, satellite imagery can be used to extract information on potential open public spaces. The identification of such spaces from imagery should be based on careful evaluation of the character of each space against the known forms of open public spaces within that city / country. High resolution satellite imagery or Google Earth imagery can be used in this analysis. Open data sources such as OpenStreetMap (OSM) have some polygon data on open spaces in many cities. While this data may not be comprehensive for all cities, it can contribute to the data collection efforts and can be explored.
  3. Using the data extracted from step 2 above, undertake validation to remove spaces which are not open for public use (e.g. private non-built up land within the urban area), or to add new spaces that might have been omitted during the extraction stage. This can be achieved through analysing the character of spaces (e.g. size, shape, land cover, etc), comparison of identified spaces with known recreational areas within the city or with data from OpenStreetMap, or consultations with city leaders, local civil society groups, community representatives among others. UN-Habitat, in consultation with partners, experts and data producers have developed a detailed tool to facilitate the verification of each space and collection of additional data on the space quality and accessibility. This tool is freely available and allows for on-site definition/ editing of the space’s boundaries. It also contains standard and extended questions which collect data relevant to the indicator, including location of the spaces, their ownership and management, safety, inclusivity and accessibility. This data provides basic information about each space, as well as information relevant for disaggregation - such as access issues linked to age, gender and disabilities, as requested for by the indicator. The tool is dynamic and allows cities to include extra questions which generate information that is useful for their decision making (Tool is available at https://ee.kobotoolbox.org/x/#IGFf6ubq). It should however be noted that the validation approaches which require primary data collection are capital intensive and may not be feasible for most countries in the short term. Validation based on existing city-level data and continuous stakeholder engagement should thus be adopted since they have been shown to produce reliable results at lower costs.
  4. Calculate the total area covered by the verified open public spaces. Once all open public spaces have been verified, calculate their area in GIS or other database management software. The share of land occupied by these spaces is then calculated using the formula

c) Computation of land allocated to streets (LAS)

Where street data by width and length fields is available/specified, the following methodology could be used:

  1. Select only the streets included in the city / urban area (or clip streets to the city/urban boundary)
  2. From GIS (or alternative software), calculate the total area occupied by each street by multiplying its length with width. Add up all individual street areas to attain the total amount of land occupied all streets within the defined urban area.

Where detailed data on streets is not available, there is need to map out each street line (or the entire area covered by the streets), measure its length and width, which are required for the area computation. For small urban areas, it is possible to manually digitize all streets, but this is more complex for large urban areas and cities. For these large urban areas, an alternative technique for computing land allocated to the streets is one that adopts sampling principles.An approach that uses the Halton sampling sequence is recommended, specifically because the sequence generates equidistant points, increasing the degree of sample representativeness. To compute LAS using this method, follow the following steps:

  1. Using the urban extent boundary identified earlier, generate a Halton sequence of sample points (Halton sequence refers to quasi-random sequence used to generate points in space that are ex-post evenly spread i.e. Equidistant). The number of points used for each city varies based on its area.In large study areas of more than 20 km2, a density of one circle per hectare is used while in small study areas of less than 20 km2 a density of 0.5 circle per hectare is used.
  2. Buffer the points to get sample areas with an area of 10 hectares each.
  3. Within each 10-hectare sample area, digitize all streets in GIS software and compute the total amount of land they occupy.
  4. Calculate the average land allocated to streets for all sample areas using the following formula:


Open source datasets such as OpenStreetMap (OSM) have a good amount of street data on many cities, which is increasingly being updated and extended to cover new areas. This data can also be used as a starting point to understand the pattern of streets in a city. Upon verification of the OSM street categorization for each city, sampling can be used to estimate the average width of each street category, which can in turn help compute the share of land allocated to streets.

The final computation of the indicator is done using the formula:


d) Estimation of share of population with access to open public spaces and disaggregation by population group

To help define an “acceptable walking distance” to open public spaces”, UN-Habitat organized a series of consultations with national statistical officers, civil society and community groups, experts in diverse fields, representatives from academia, think tanks, other UN-agencies, and regional commissions among other partners. These consultations, which were held between 2016 and 2018 concluded that a walking distance of 400 meters - equivalent to 5 minutes’ walk was a practical and realistic threshold. Based on this, a street network-based service area is drawn around each public open space, using the 400 meters access threshold. All populations living within the service areas are in turn identified as having access to the public open spaces, based on the following key assumptions:

  • Equal access to each space by all groups of people – i.e. children, the disabled, women, elderly can walk a distance of 400 meters (for 5 minutes) to access the spaces (in actual sense, these will vary significantly by group).
  • All streets are walkable – where existing barriers are known (e.g. un-walkable streets, lack of pedestrian crossings, etc), these can be defined in the delimitation of the space service area.
  • All public open spaces have equal area of influence – which is measured as 400 meters along street networks. In real life situations, bigger spaces have a much larger area of influence.
  • All buildings within the service area are habitable, and that the population is equally distributed in all buildings/built up areas

The estimation of total population with access to open public spaces is achieved using the two broad steps described below:

  1. Create 400 meters walking distance service area from each open public along the street network. This requires use of the network analyst tool in GIS software and street data (such as that from City Authorities or from Open Sources such as OpenStreetMap). A network service area is a region that encompasses all accessible areas via the streets network within a specified impedance/distance. The distance in each direction (and in turn the shape of the surface area) varies depending on, among other things, existence of streets, presence of barriers along each route (e.g. lack of foot bridges and turns) and walkability or availability of pedestrian walkways along each street section. In the absence of detailed information on barriers and walkability along each street network, the major assumption in creating the service areas is that all streets are walkable. Since the analysis is done at the city level, local knowledge can be used to exclude streets which are not walkable. The recommendation is to run the service area analysis for each OPS separately then merge all individual service areas to create a continuous service areapolygon. Step by step guidance on how to create the service area is provided in the detailed SDG 11.7.1 training module (https://unhabitat.org/sites/default/files/2020/07/indicator_11.7.1_training_module_public_space.pdf)
  2. In GIS, overlay the created service area with high resolution demographic data, which should be disaggregated by age, gender, and disability. The best source of population data for the analysis is individual dwelling or block level total population which is collected by National Statistical Offices through censuses and other surveys. Where this level of population data is not available, or where data is released at large population units, countries are encouraged to create population grids, which can help disaggregate the data from large and different sized census/ population data release units to smaller uniform sized grids. For more details on the available methods for creation of population grids explore the links provided under the references section on “Some population gridding approaches”. A generic description of the different sources of population data for the indicator computation is also provided in the detailed Indicator 11.7.1 training module (https://unhabitat.org/sites/default/files/2020/07/indicator_11.7.1_training_module_public_space.pdf).Once the appropriate source of population data is acquired, the total population with access to open public spaces in the city/urban area will be equal to the population encompassed within the combined service area for all open public spaces, calculated using the formula below.


5c. Data collection method

The following is the definition of the SDG 11.7.1 indicator and consequently there could be small variations in the definition for the’ Average share of the built-up area of cities that is green/blue space for public use for all’.

The method to estimate the area of public space has been globally piloted in over 600 cities and this follows a series of methodological developments that go back to the last 7 years. The finalized methodology is a three-step process: a) Spatial analysis to delimit the city/urban area which will act as the geographical scope for the spatial analysis and indicator computation; b) Spatial analysis to identify potential open public spaces, expert consultations and/or field work to validate data and assess the quality of spaces, and calculation of the total area occupied by the verified open public spaces; c) Estimation of the total area allocated to streets; d) Estimation of share of population with access to open public spaces within 400 meters walking distance out of the total population in the city/ urban area and disaggregation of the population with access by sex, age and persons with disabilities.

5d. Accessibility of methodology

Methodology for SDG 11.7.1 is available and has been piloted in over 1000 cities globally. Data on the indicator is published by UN-Habitat (https://data.unhabitat.org)

5e. Data sources

City land use plans, high to very high resolution satellite imagery (open sources), documentation outlining publicly owned land and community-based maps are the main sources of data

5f. Availability and release calendar

The monitoring of the indicator can be repeated at regular intervals of 3-5 years, allowing for three reporting points until the year 2030. However, annual updates to the existing database will be done and hence data releases based on annual updates will be available every year. Monitoring in 3-5-year intervals will allow cities to determine whether the shares of open public space in the built-up areas of cities are increasing significantly over time, as well as deriving the share of the global urban population living in cities where the open public space is below the acceptable minimum.

5g. Time series

Baseline data on SDG 11.7.1 available for 2020

5h. Data providers

Ministries in charge of urban development, national mapping agencies, national statistical offices

5i. Data compilers

UN-Habitat is the lead agency on the global reporting for this indicator and as such, has since 2016 coordinated the efforts of various partners, on methodological developments and piloting of data collection. Key among these partners have included National Statistical Offices, New York University, ESRI, FAO, UNGGIM, UCLG, Local government departments, the European Commission, UN regional commissions, KTH University-Sweden, Urban Observatories, etc. Working in partnership with these partners, UN-Habitat has undertaken trainings and capacity development activities in cities, countries and regions, which have contributed to enhanced data collection and setting up of systems to monitor and report on the indicator.

5j. Gaps in data coverage

The currently available data covers cities and urban areas of different sizes but is not classified by typology of open public space i.e. green, blue and artificial surfaces.

5k. Treatment of missing values

All qualifying cities/countries are expected to fully report on this indicator more consistently following implementation and full roll out of this methodology. In the early years of this indicator, we had data gaps due to no data being collected at the time, as opposed to missing data. In most of the cases, missing values to-date reflect a non-measurement of the indicator for the city. However, because national statistical agencies will report national figures from a complete coverage of all their cities, some cities may take longer to be measured or monitored. As a result, UN-habitat has worked with partners to develop a concept of applying a National Sample of Cities. With this approach, countries will be able to select a nationally representative sample of cities from their system of cities, and these will be used for global monitoring and reporting purposes for the period of the SDGs. The fully developed methodology on this concept has been rolled out and countries that are unable to cover the full spectrum of their cities are already applying this approach. See:

https://unhabitat.org/sites/default/files/2020/06/national_sample_of_cities_english.pdf

6. Scale

6a. Scale of use

Scale of application: Global, Regional, National

Scale of data disaggregation/aggregation:

Global/ regional scale indicator can be disaggregated to national level:

National data is collated to form global indicator:

Additional information: The indicator is applicable from city to national and regional/global levels. Measurement is done at the city level (for all cities and/or using a sample of representative cities) from where data can be aggregated to national, regional and global levels.

6b. National/regional indicator production

Global SDG 11.7.1 methodology is applicable to national and local city levels (see https://unstats.un.org/sdgs/metadata/files/Metadata-11-07-01.pdf). Since countries have the responsibility to produce data on the indicator, the underlying data is available to them through existing national and local data sharing mechanisms. Data produced through the efforts of international organizations such as UN-Habitat is openly available to countries for use

6c. Sources of differences between global and national figures

Minimal to no differences are likely to emerge for this indicator since measurement is done at the city level, with data aggregated to national, regional then global levels. Data produced by international organizations is to be shared with countries for validation, and nationally produced data will be treated as the most authoritative data. The only likely source of variations may be on the application of the globally harmonized approach to defining cities and urban areas, where countries may choose to use their national definitions as opposed to the harmonized approach. Data for this indicator should thus be accompanied by an explanation on the definition of city/urban area used in the computations.

6d. Regional and global estimates & data collection for global monitoring

6d.1 Description of the methodology

Data produced at the city/urban level within each country is aggregated to produce a national value based on the national sample of cities approach developed by UN-Habitat, through which a weighting scheme is developed for each city as a factor of its national representativeness (See: https://unhabitat.org/sites/default/files/2020/06/national_sample_of_cities_english.pdf). The national aggregates from different countries are then used to produce regional and global estimates.

Anticipating the challenge of limited data availability from countries in the earlier years of the indicator, the global sample of cities developed jointly by UN-Habitat, New York University and the Lincoln Institute of Land Policy presents a consistent approach to producing regional and global aggregates. The global sample of cities includes a list of cities which are representative of all regions and for which data can be produced and used to produce weighted regional and global values on the indicator performance (see https://www.lincolninst.edu/sites/default/files/pubfiles/atlas-of-urban-expansion-2016-volume-1-full.pdf).

6d.2 Additional methodological details

6d.3 Description of the mechanism for collecting data from countries

7. Other MEAs, processes and organisations

7a. Other MEA and processes

7b. Biodiversity Indicator Partnership

Yes

8. Disaggregation

Based on availability of high-resolution population data, population with access to open public spaces should be disaggregated by age, gender and disability.

Wherever possible, it would also be useful to have information disaggregated by:

  • Location of public spaces (intra-urban)
  • Quality of the green/blue space by safety, inclusivity, accessibility, greenness, and comfort
  • Type of green/blue space as a share of the city area
  • The share of green/blue space in public use which are universally accessible, particularly for persons with disabilities.
  • Type of human settlements

9. Related goals, targets and indicators

10. Data reporter

10a. Organisation

UN-Habitat

10b. Contact person(s)

Robert Ndugwa: robert.ndugwa@un.org

11. References

Axon Johnson Foundation, Public Spaces and Place making, Future of Places, http://futureofplaces.com/

UN-Habitat (2013) Streets as Public Spaces and Drivers of Urban Prosperity, Nairobi

UN-Habitat (2014) Methodology for Measuring Street Connectivity Index

UN-Habitat (2015) Spatial Capital of Saudi Arabian Cities, Street Connectivity as part of City Prosperity Initiative

UN-Habitat (2015) Global Public Space Toolkit from Global Principles to Local Policies and Practice

UN-Habitat (2018). SDG Indicator 11.7.1 Training Module: Public Space. United Nations Human Settlement Programme (UN-Habitat), Nairobi. Available at https://unhabitat.org/sites/default/files/2020/07/indicator_11.7.1_training_module_public_space.pdf

Kaw, Jon Kher, Hyunji Lee, and Sameh Wahba, editors. 2020. The Hidden Wealth of Cities: Creating, Financing, and Managing Public Spaces. Washington, DC: World Bank. doi:10.1596/978-1-4648-1449-5. License: Creative Commons Attribution CC BY 3.0 IGO

SDG 11.7.1 metadata, 2020. https://unstats.un.org/sdgs/metadata/files/Metadata-11-07-01.pdf

Back to top

Feedback: The information on this site is provided to the best of our current knowledge and may be used to aid discussions on indicators for the post-2020 framework. UNEP-WCMC is keen to ensure that our data is accurate and up to date. We welcome any feedback on the quality, reliability, and accuracy of the information on this site. If you see any errors or missing information, please get in touch get in touch.