Computation Method:

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:

Spatial analysis to delimit the city/urban area which will act as the geographical scope for the spatial analysis and indicator computation;
Spatial analysis to identify potential open public spaces, field work to validate data and assess the quality of spaces and calculation of the total area occupied by the verified open public spaces;
Estimation of the total area allocated to streets;
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
Spatial analysis to delimit the city/urban area

Following consultations with 86 member states, the United Nations Statistical Commission in its 51^st 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

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:

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).
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.
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.
Calculate the total area covered by the verified open public spaces. Once all open public spaces (OPS) 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

$S h a r e o f o c c u p i e d l a n d b y O P S (%) = [\frac{T o t a l a r e a c o v e r e d b y O P S}{\begin{matrix} T o t a l a r e a o f t h e c i t y \\ \end{matrix} }]$

Computation of land allocated to streets (LAS)

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

Select only the streets included in the city/urban area (or clip streets to the city/urban boundary)
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:

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.
Buffer the points to get sample areas with an area of 10 hectares each.
Within each 10-hectare sample area, digitize all streets in GIS software and compute the total amount of land they occupy.
Calculate the average land allocated to streets for all sample areas using the following formula:

Land allocated to streets = $\frac{S u m o f L A S f r o m a l l s a m p l i n g p o i n t s}{N u m b e r o f s a m p l i n g p o i n t s}$

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 to compute the share of land allocated to streets.

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

$S h a r e o f t h e b u i l t - u p a r e a o f t h e c i t y t h a t i s o p e n s p a c e i n p u b l i c u s e (%)$

$= \frac{T o t a l s u r f a c e o f o p e n p u b l i c s p a c e + T o t a l s u r f a c e o f l a n d a l l o c a t e d t o s r e e t s}{\begin{matrix} T o t a l a r e a o f t h e c i t y \\ \end{matrix}}$

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 open public 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 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:

Create 400 meters walking distance service area from each open public space along the street network. This requires use of the network analysis 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 area polygon. 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)
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.

$S h a r e o f p o p u l a t i o n w i t h a c c e s s t o o p e n s p a c e i n p u b l i c s p a c e s (%)$

$= \frac{T o t a l p o p u l a t i o n w i t h i n 400 m s e r v i c e a r e a s}{T o t a l p o p u l a t i o n w i t h i n t h e c i t y / u r b a n e x t e n t }$

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Rætta uppseting: 11.7.1