Access to green space in England

Question 1

Correction:

Accepted Answer

We appreciate all the feedback we have received so far on this statistic in development. We continue to welcome your thoughts on this work and will consider how it can shape future releases on access to natural spaces. Some feedback brought to our attention some issues with the data. As a result, we have implemented the following changes:

Access points to some green spaces smaller than 10 ha were erroneously included in the modelling for Scenario 5, which has now been corrected. This has resulted in a notable difference in the results for the percentage of households with access to green space, declining from 53% to 33%. It also impacted Scenarios 6 and 7, although to a lesser extent, with a decrease of 3 and 5 percentage points, respectively.
A minor issue with the way Ordnance Survey access points were processed has been identified. A subset of the OS green space data contains multipolygons, and previously, some access points were being assigned to the incorrect individual polygon in the multipolygon set. This meant that some access points were inheriting incorrect size attributes and therefore being included or excluded erroneously across all scenarios. This change had a very minor impact across all scenarios.
During the course of these corrections, we also identified that woodlands were not fully represented in Scenarios 1 and 2. This has now also been rectified and explains the larger changes seen in these scenarios: the percentage of households with access to green space increased from 78% to 87% for Scenario 1 and from 91% to 93% for Scenario 2. For households in rural areas, the percentage of households with access to green space increased greatly from 50% to 72% in Scenario 1.

Last updated: 2025

Latest data available: 2024

Question 2

Contact

Accepted Answer

Enquires on this publication to: access.statistics.feedback@defra.gov.uk

Tel: 03459 335577 (Defra enquiries) Find out more about call charges at – GOV.UK

Responsible Statistician: Clare Betts

Website: Biodiversity and wildlife statistics – Gov.UK

Question 3

Key messages

Accepted Answer

The definition of ‘access’ and ‘green space’ used has a large impact on the results.
With a broad definition of green space, many urban households have access.
Only when access to the wider countryside is considered a green space experience do rural areas have similar provision to green space as urban areas.
Refining the size and type of green space as well as the distance to it, greatly reduces the number of households with access, in both rural and urban areas.
Tighter limits on the distance to green space appears to have a greater impact than the size of the green space on the number of households with access.

Question 4

Introduction

Accepted Answer

As this is an official statistic in development, we welcome feedback on the novel methods used in the development of this indicator. For example, feedback on whether this new indicator measures something users feel should be measured, and how well it does so.

Official statistics in development are official statistics that are undergoing a development; they may be new or existing statistics, and will be tested with users, in line with the standards of trustworthiness, quality, and value in the Code of Practice for Statistics.

To give feedback, email the production team at access.statistics.feedback@defra.gov.uk.

These statistics describe the percentage of households that are within different walking distances of different types of green space for small neighbourhoods in England.

The statistics published here build on previous work produced by Natural England (Accessible Greenspace Standards) which recommends that everyone, wherever they live, should have an accessible natural green space. This previous work was based on straight line distances between households and green spaces.

In producing these statistics, we have calculated the distance to green space for every household in England measured along a network of walkable streets and paths. The results are summarised by Middle layer Super Output Area (MSOA), although results by Output Area are available in the published datafile (both using Census 2021 geographies). Each Output Area in England is made up of between 40 and 250 households, and usually has a resident population of between 100 and 625 persons. Middle layer Super Output Areas are made up of groups of Output Areas. They comprise between 2,000 and 6,000 households and usually have a resident population between 5,000 and 15,000 persons. There are over 6,800 MSOAs in England.

The network model used to calculate walking distances was run several times with different types of green space included, and using different distance thresholds between households and green space. We refer to these different model runs as scenarios:

All green space – considered all accessible green spaces 2 hectares or larger, and a distance threshold of 1 km
All green space with rights of way – considered all accessible green spaces 2 hectares or larger as well as rural rights of way as a type of green space experience, and a distance threshold of 1 km
Doorstep standard – considered all accessible green spaces of at least 0.5 ha within 200 metres (under 5 mins walk from home). This scenario corresponds to Natural England’s Doorstep Accessible Greenspace standard
Local standard – considered all accessible green spaces of at least 2 ha within 300 metres (5 mins walk from home). This scenario corresponds to Natural England’s Local Accessible Natural Greenspace
Neighbourhood standard – considered all accessible green spaces of at least 10 ha within 1 km (15 minutes’ walk from home). This scenario corresponds to Natural England’s Neighbourhood Accessible Natural Greenspace
Combined – Scenarios 3 to 5 combined, where a household is considered to have access to green space if they meet the criteria of the doorstep scenario (Scenario 3) and the Local standard (Scenario 4) and the Neighbourhood standard (Scenario 5) concurrently
Partial-combined – a mixture of Scenarios 3 to 5. In this scenario, households are considered to have accessible green space where the Neighbourhood standard (Scenario 5), and one of either the Doorstep standard (Scenario 3) or Local standard (Scenario 4) have been met

For more information on these scenarios, see Scenarios in the background and methodology section.

Question 5

Access to green space in England

Accepted Answer

The percentage of households in England with access to green space varied between 5% and 93%, depending on the definition of ‘green space’ and ‘accessible’ used (Figure 1). This wide range reflects the impact of varying the size and type of green space, or the distance between household and green space considered to be accessible. For instance, Scenario 2 reports a very high percentage of households with access to green space (93%) because it uses a very broad definition of ‘green space’ and a large distance threshold between households and green space.

Figure 1: The percentage of roughly 25,800,000 households in England with access to green space, calculated using 7 definitions of ‘green space’ and ‘access’.

The ‘all green space’ definition estimates a high percentage of households with accessible green space (87%), which is likely to be because it uses a very broad definition of ‘green space’. This is further increased when rights of way in non-urban areas are included as a green space experience in Scenario 2 (93%).

Scenarios 3, 4 and 5 are equivalent to the Natural England’s Accessible Greenspace Standards. Under Natural England’s Doorstep standard, it is estimated that 15% of households have access to green space whilst a previous estimate published by Natural England was 33%. Under Natural England’s Local standard, an estimated 12% of households have access to green space compared to a previous estimate of 25% published by Natural England. Under Natural England’s Neighbourhood standard, an estimated 33% of households have access to green space. This is a reduction compared to the estimate previously published by Natural England (49%), as shown in other scenarios. This reflects the impact of using a network based approach to estimate realistic walking routes for individual households. Overall, the differences between the network based results and straight-line distance derived statistics are consistent across the three standards.

Scenario 6 (combined standard) estimated the lowest percentage of households with access (5%), which required households to have access to all three green space standards concurrently (a space at least 0.5 ha within 200 metres, a space of at least 2 ha within 300 metres and a space of at least 10 ha within 1 km). Scenario 7 (partial-combined standard) relaxed this requirement a little and subsequently estimated 18% of households having access to green space.

There is a great deal of variation in access to green space, even at the very local level. On average a Middle layer Super Output Area (MSOA) has between 1% and 99% of households with accessible green space (Figure 2). The distribution of households with access to green space across the country is very different depending on the definitions applied; the majority of MSOAs in the ‘All green space’ and ‘All green space with rights of way’ scenarios (1 and 2) have a high percentage of households with access to green space. Similarly, the majority of MSOAs under the Local standard and Combined standard scenarios (4 and 6) have a very high percentage of households with no access to green space. Many MSOAs in the Doorstep standard and Partial-combined standard scenarios (3 and 7) have a low percentage of households with access to green space.

Figure 2: The distribution of percentage of households within MSOAs with access to green space, calculated using 7 definitions of ‘green space’ and ‘access’.

Notes for Figure 2:

The area under the curve represents the distribution of MSOAs across the gradient of percentage of households with access to green space. The area under the curve is coloured to highlight this distribution, with the darkest area representing the central 50% of the data, medium blue 75% of the data, and the lightest blue 95% of the data distribution.
The median of each distribution is marked by a vertical black line.

For some scenarios, there is a marked difference in the percentage of households with access to green space between urban and rural areas (Figure 3). In particular, the percentage of households with access to green space for ‘All green space’ and the Neighbourhood standard (Scenarios 1 and 5) is higher in urban areas than rural areas.

Figure 3: The distribution of percentage of households within MSOAs with access to green space, calculated using 7 definitions of ‘green space’ and ‘access’, grouped by urban or rural classification.

Notes for Figure 3:

20 Output Areas could not be assigned a rural / urban classification and so were excluded from the analysis.
The median of each distribution is marked by a vertical line.

The percentage of households with no access to green space varied considerably between the different scenarios (Table 1). For instance ‘All green space with rights of way’ (Scenario 2) estimated relatively few households with no access in both rural and urban areas (6% and 7% respectively), whilst the Neighbourhood standard (Scenario 5) estimated 85% of households with no access in rural areas, and only 63% in urban areas.

Table 1. The percentage of households with no access to green space, calculated using 7 different definitions of ‘green space’ and ‘access’ and split between rural and urban areas.

Scenario	Rural	Urban
1. All green space	28	10
2. All green space with rights of way	6	7
3. Doorstep standard	88	84
4. Local standard	94	87
5. Neighbourhood standard	85	63
6. Combined standard	97	95
7. Partial-combined standard	87	81

Question 6

Discussion

Accepted Answer

The results from the different scenarios highlight the importance of clearly defining green space, both type and size, as well as the distance assumed to be accessible. Large differences are seen between the scenarios using Natural England’s criteria (scenarios 3-7) compared to the more broadly scoped scenarios (1 and 2). In the first two scenarios, including access points to non-urban rights of way improved the national percentage of households with access to green space. This is likely due to the extensive nature of the rights of way network within England, and the fact they not only traverse other types of green space but cover areas where other types of green space are absent. Within the Natural England scenarios, the impact of limiting the distance to green space to 200 m (Scenario 3 - Doorstep standard) and 300 m (Scenario 4 - Local standard) greatly reduced the national percentages of households with access. However, even with a 1 km distance threshold (Scenario 5 – Neighbourhood standard) still showed relatively low levels of access, likely due to the 10 ha size threshold, severely limiting the availability of green spaces.

Comparing the results from the ‘All green space’ and ‘All green space with rights of way’ scenarios (1 and 2) especially highlight the rural and urban divide in some of the data. In the ‘All green space’ scenario (1), the broad definition of green space, including both municipal green spaces like parks alongside other designations such as nature reserves, shows that most urban households have opportunities to access green space. However, although spaces such as nature reserves, open access land and woodlands were included, the fragmented and scattered nature of these spaces mean that large numbers of rural households are not considered to have access to them. The addition of rural rights of way in Scenario 2 made a big difference for rural households, due to the extensive nature of rural rights of way, providing many more opportunities for a green space experience, in particular where other types are lacking. Whilst we have tried to address the lack of green space access points in rural areas by representing rights of way, the approach does make several assumptions and therefore green space provision may be under or overrepresented in some areas.

The types of green space used in scenarios 3 to 7 (based on Natural England’s standards) are much more restricted than those used in the ‘All green space’ and ‘All green space with rights of way’ scenarios (1 and 2), and this is clearly reflected in both the totals in Figure 1 and the distributions of data shown in Figure 2. While there are common green space types between all scenarios, the exclusion of some types in the Doorstep standard scenario (3) and reduction in the distance threshold from 1 km to 200 m led to a very large reduction in access to green space. Despite the size threshold also being reduced, so that small green space features are included (e.g. 0.5 ha playing fields), many households are not located within a short walk of such features. A very similar set of green space types was used in the Local standard scenario (4), but the increase in the size threshold to 2 ha further reduced the percentages of households with access. This is despite a 50% increase in the distance threshold to 300 m. It is only when the distance was raised to 1 km in the Neighbourhood standard scenario (5) that the national estimate improves (Figure 1).

These statistics are designed to complement and build upon work in the Natural England Green Infrastructure Framework. The work by Natural England has two main methodological differences to this analysis which is likely to explain the lower values in these statistics for the scenarios using Natural England’s criteria (Scenarios 3 to 7) when compared to previously published data. Firstly, the network based approach to calculating the shortest path used in the production of these statistics uses a network of paths and roads to calculate realistic travel distances between two points. The previous work undertaken by Natural England used a straight-line approach. Given the non-linear nature of roads and paths, the distance between households and green spaces is going to be greater than a straight-line distance. Secondly, in these statistics we use the location of households to represent where people live, whereas previous analyses by Natural England assumed an even distribution of the population across smaller Lower layer Super Output Areas. We also used access points to represent the locations individuals can likely access green space, rather than assuming the entire perimeter of a green space is accessible. This changes the assumptions around how and where people access green space, and will also explain some differences between these statistics and existing work.

While we used the Accessible Greenspace Standards to help define distance thresholds and green space types in some scenarios, differences in the methodology used to generate access points using rights of way data (see Technical Annex) and the versions of datasets, such as Ordnance Survey Open Greenspace, differ between this and the previous analysis.

Providing data at a fine granular level, such as Output Areas, allows for the investigation of spatial patterns in the data, and ultimately understanding where interventions may be targeted. For example, identifying clusters of Output Areas that have very little green space provision may provide the best opportunity to either improve access to existing green spaces or introduce a new green space. However, it is worth noting that reported low levels of access could be due to limitations in the data available at the time this analysis was done (see Caveats for more details). Our development plan aims to build on this work and improve the quality and coverage of data used.

In these analyses, green space access points are considered equal in terms of both quality and the potential number of people they could serve. This approach enables us to baseline the national picture on access to green space. However, we acknowledge that green space quality and the experiences they provide to people vary greatly, both depending on their capacity and popularity, as well as the type of environment found within them. Quantifying the quality of green space in a universal way across the different types used in this work is challenging, but could be explored in the future. Further analyses could be conducted to understand how many households share a particular green space as their nearest in the network model.

Question 7

Official statistics in development designation

Accepted Answer

Our statistical practice is regulated by the Office for Statistics Regulation (OSR). OSR sets the standards of trustworthiness, quality and value in the Code of Practice for Statistics that all producers of official statistics should adhere to. You can read about how Official Statistics in Defra comply with these standards on the Defra Statistics website.

This publication is an official statistic in development. Official statistics in development are official statistics that are undergoing a development; they may be new or existing statistics, and will be tested with users, in line with the standards of trustworthiness, quality, and value in the Code of Practice for Statistics.

Details of how we plan to develop these statistics are laid out in the Development Plan. We particularly welcome feedback from users on the methodology and presentation of the statistics set out in this release, and our future plans for development. For example, feedback on whether this new indicator measures something users feel should be measured, and how well it does so.

Question 8

Background and methodology

Accepted Answer

A shortest path algorithm was used to find the closest green space access point to each household, given the walkable routes available. This type of model has three major components:

Source locations – the places where the shortest path calculation begins. For this statistic, source locations are households.

Destination locations – the places where the model aims to find the shortest path to. For this statistic, destination locations are green space access points.

Network – consisting of links and nodes. Links represent transport infrastructure in line form, e.g. roads and paths, and nodes show the locations at which they interconnect. Together they form a traversable network, where each link has a length and two associated nodes. The path with the smallest sum of lengths between source and destination locations forms the shortest path.

More detail for each of these components is provided below.

Doorstep Greens access points

The Doorstep Greens initiative provides new or renovated areas of public open space close to people’s homes that could be enjoyed permanently by the local community. The initiative is aimed at targeting communities who experience disadvantage and where regeneration of the local environment and outdoor recreation provision is most needed. They could be small or large, and in urban or rural locations. As per Natural England’s Green Infrastructure methodology, access points were created where public rights of way intersect doorstep greens.

Country Parks access points

Country Parks are accredited by Natural England. They are public green spaces often at the edge of urban areas which provide places to enjoy the outdoors and experience nature in an informal semi-rural park setting. As per Natural England’s Green Infrastructure methodology, access points were created where public rights of way intersect country parks.

Local Nature Reserves access points

Local Nature Reserves (LNRs) are a statutory designation made under Section 21 of the National Parks and Access to the Countryside Act 1949, usually designated by principal local authorities. They are places with wildlife or geological features that are of special interest locally, and offer people opportunities to study or learn about nature or simply to enjoy it. As per Natural England’s Green Infrastructure methodology, access points were created where public rights of way intersect local nature reserves.

Open access land access points

The Countryside and Rights of Way Act 2000 (CRoW Act) normally gives a public right of access to land mapped as ‘open country’ (mountain, moor, heath and down) or registered common land. Additionally, some land is subject to pre-existing access rights which predate the CRoW Act; this is known as Section 15 land. Collectively this ‘open access land’ is free to access in its entirety and can be accessed on foot by any available route. Open access land data was created by combining polygon datasets for CRoW access land and Section 15 land as published by Natural England. Access points were created where public rights of way, roads (excluding motorways) or paths likely provided access to open access land.

Woodland access points

Whilst woodlands do form parts of other green spaces, they can also be considered as a distinct type of green space. However, it cannot be assumed that woodlands are open access, so access points were generated where woodlands intersected public rights of way and the rights of way within the woodland parcel were a minimum contiguous distance (250 m). Woodland data were acquired from the Natural England Green Infrastructure mapping dataset.

National Nature Reserves access points

National Nature Reserves (NNRs) were established to protect some of our most important habitats, species and geology, and to provide opportunities to the public to experience wildlife at first hand and to learn more about nature conservation. There are currently 221 NNRs in England with a total area of over 110,000 hectares - approximately 0.8% of the country’s land surface. NNRs are not by default open access land. Therefore, considering where public rights of way enter and traverse them is an appropriate way to gauge access opportunities. Access points were generated where rights of way intersected national nature reserve boundaries and the rights of way within the NNR parcel were a minimum contiguous distance (250 m).

Golf course access points

Similarly to National Nature Reserves, golf courses are typically not openly accessible to the public. Golf course boundaries were extracted from the OS Open Greenspace data product. Access points were generated where rights of way intersected golf course boundaries and the rights of way within the golf course were a minimum contiguous distance (250 m).

Rights of way access points

In non-built-up areas, there are fewer municipal green spaces, and the rights of way network provides people with an opportunity to access more natural green spaces. An access point dataset was generated representing the locations where the Ordnance Survey road and path network likely provide access to parts of the public rights of way network that are of a minimum contiguous distance (250 m) in non-built-up areas.

Network

A network consisting of nodes and links was constructed using the pandana package in Python. Figure 4 shows an example network. Each link in the network has an associated length (in meters), as well as a start and end node. Nodes are used to connect links, and also represent start and end points for the shortest path analysis. Two datasets were used to construct the network; Ordnance Survey MasterMap Highways Network Paths and Roads. These data are provided in a network ready format. Roads, paths and connecting links (links which indicate when roads can be accessed from paths and vice versa) are provided with corresponding start and end node identifiers. Lengths of each link are provided for roads and paths, while for connecting links a length of 1 m was manually added. Connecting links are often not physical features, so 1 m was deemed an appropriate corresponding value, as a value >0 was required for the model to run. Motorways were excluded from the roads data before building the network.

Figure 4: The components used in the shortest path analysis.

Notes for Figure 4:

A diagram showing the relationships between households, network links, network nodes, greenspace and greenspace access points.
Links and nodes are joined together to make a continuous set of roads and paths, households are located along one edge, and a greenspace access point is shown where a link meets a greenspace.

Method for creating the statistics

To understand the distance between households and access points, using infrastructure such as roads and paths, a network based approach to analysis was undertaken.

Given the large amount of computing resource required for the shortest path calculations (due to the density of roads and paths in some parts of England), a tiling approach was used (Figure 5). A regular 5 x 5 km polygon grid was created across the extent of England. This grid was then clipped to the boundary of England (buffered by 10 km) to identify and retain only the terrestrial grid squares. The 10 km buffer was used to remove any ambiguity in coastal areas, retaining grid cells with any likely household locations.

For each grid cell, the following was undertaken:

Extract the households that intersect the grid cell.
Extract the green space access points (relevant to the given scenario) that intersect the grid cell and any of the 8 neighbouring grid cells. For coastal grid cells, there will be fewer than 8 neighbouring grid cells.
Extract the network data that intersect the grid cell and any of the 8 neighbouring cells.
Create a network with the extracted network data using the python package pandana.
Identify the nodes in the network that relate to the households. These are now referred to as source nodes. See section on Households and node relationships.
Identify the nodes in the network that relate to the green space access points. These are now referred to as destination nodes. See section on Greenspace access points and node relationships.
Calculate every unique pair of source nodes and destination nodes.
Run the shortest path algorithm for every unique pair of source and destination nodes. This algorithm sums the length attribute of each link in the network that it traverses when calculating a path, resulting in a total length (in meters) for each shortest path.
For each source node, select the shortest distance recorded to any of the destination nodes.
Join the shortest distances back to the household data, so that every household has an associated shortest distance.

For a given scenario, once all the above steps were undertaken for every grid cell, the outputs were combined, producing a table of all households in England and their shortest distance to a green space.

Households and associated model output data were then spatially joined to Output Area geographies and summary statistics per Output Area were calculated.

The ONS produces a rural/urban classification scheme for Output Areas, the most recent of which uses the 2011 Output Areas. We have used the 2021 Output Areas to aggregate the results of the shortest path analysis and mapped this on to the 2011 Output Areas and the corresponding ONS rural/urban classification.

Figure 5: Tiling approach taken in the shortest path modelling.

Notes for Figure 5:

A 5 kilometer by 5 kilometer box surrounded by 8 boxes of the same size in a grid.
In the central box are data points showing households, network links, network nodes and greenspace access points.
In the surrounding boxes, only network links, network nodes and greenspace access points are present.

Scenarios

Varying combinations of different types of access points and the size of corresponding green spaces were used to provide destinations in each of the scenarios. Below are the details of which combinations were used, which are summarised in Table 2. More detail can be found in Scenario details.

Some scenarios use a 1 km distance threshold between household and green space access point. This distance was chosen to represent an approximated 15 minute walk at 4.0 km/h.

Where woodlands, National Nature Reserves and golf courses were included (scenarios 1 and 2), this was only done so where the minimum contiguous right of way green space experience was at least 250 m.

In Scenario 2 (All green space and rights of way), rights of way access points were included. These access points represent the points at which the path/road network intersects rights of way, and the rights of way continue for at least 250 m in mainly non-urban areas.

The Accessible Greenspace Standards combined scenario (6) combined scenarios 3, 4 and 5 where a household was considered to have access to green space if they met the criteria of the Doorstep standard (Scenario 3) and the Local standard (Scenario 4) and the Neighbourhood standard (Scenario 5) concurrently.

Scenario 7 (Accessible Greenspace Standards partial combined) considered households to have access to green space where the Neighbourhood standard (Scenario 5), and one of either the Doorstep standard (Scenario 3) or Local standard (Scenario 4) had been met.

Table 2. A summary of the thresholds and types of green space included in scenarios 1 to 5.

	1. All green space	2. All green space and rights of way	3. Doorstep standard	4. Local standard	5. Neighbourhood standard
Green space size threshold	2 hectares	2 hectares	0.5 hectares	2 hectares	10 hectares
Distance threshold	1 km	1 km	200 m	300 m	1 km
Cemeteries (OS Greenspace)	Included	Included
Play Spaces (OS Greenspace)	Included	Included
Playing Fields (OS Greenspace)	Included	Included	Included
Public Parks or Gardens (OS Greenspace)	Included	Included	Included	Included	Included
Religious Grounds (OS Greenspace)	Included	Included
Millenium Greens	Included	Included	Included	Included	Included
Country Parks	Included	Included	Included	Included	Included
Doorstep Greens	Included	Included	Included	Included	Included
Local Nature Reserves	Included	Included	Included	Included	Included
Open Access Land	Included	Included	Included	Included	Included
Woodlands	Included	Included
National Nature Reserves	Included	Included
Golf Courses	Included	Included
Rights of way		Included

Caveats, limitations, and uncertainties

Access points

Green space access point data from the Ordnance Survey (OS) Open Greenspace data product is comprehensive but may be missing access points which would be suitable for the analysis used to produce these statistics. Some green spaces may not have associated access points in the source data and would therefore not be considered in the analysis.

Some of the access point data are outputs of a spatial analysis where public rights of way intersect the boundary of different types of green space. The public rights of way data used in the analysis are known to be incomplete; a small number (48) of highways and local authorities across England did not provide data to the compilation process undertaken by Natural England. Therefore, in some parts of England, there will be fewer access points for certain types of green space available as destinations in the shortest path calculations.

To account for low quality or inaccurate digitisation of rights of way data, features that were used in conjunction with public rights of way data to create access points were buffered by 10 m. For example, if a right of way connected a road to a parcel of open access land in reality, but the data showed the right of way ending outside of the land parcel, an access point would not have been generated. The buffering approach was used to capture situations such as these and ensure that access points were generated. While this minimises some issues with the accuracy of the rights of way data, it introduces bias, potentially creating access points at locations where in reality, they may not exist.

Some green spaces are fragmented by features such as roads. In the above method, whilst in reality they may be joined by bridges or road crossings, such green spaces are not merged, and their individual sizes considered in any size-based filtering for scenarios. Thus, some green spaces may not be included in our analysis which should be, especially those scenarios with larger size thresholds.

Some green spaces are fully open and accessible across their entire perimeter. In these cases, the access point approach does not correctly represent access and therefore the shortest path calculations may over-estimate distances required to access such green spaces.

For access points generated as part of this analysis, some assumptions have been made about the relationship between the features assessed. For example, when a road intersects a right of way, an access point has been generated. In many cases, this will be a junction that allows someone to access the right of way from the road. However, in a small number of cases, the two-dimensional representation may be inaccurate – a topological relationship may be present, but access may not be provided in reality. For example, the road may be elevated and pass over the right of way, with no way to exit the road and join the right of way.

Walkability

Where possible, walkability has been factored into the path and road network data used. Motorways have been removed from the data so that roads of these types are not deemed as possible routes when the shortest path is calculated. This therefore leaves the assumption that all other road types are suitable, which may not be the case, for instance dual carriageways. In the future we would like to include data on pavements to make our assumptions of ‘walkability’ more accurate.

Definition of a household

Unique Property Reference Numbers (UPRN) were filtered such that only residential properties were included (see the Technical Annex). As described by the Office for National Statistics in their census geographies description, Output Areas should typically contain 40 to 250 households. In this analysis, in a very small number of Output Areas, there is a greater number of households due to the presence of certain types of accommodation. For example, some Output Areas encompass halls of residence at a university campus, and therefore contains a greater number of households than many other Output Areas in the dataset. Equally, a small number of Output Areas contain very few households.

Distance from households to nodes

A methodology has been implemented in these analyses to account for the distance more accurately from the ‘front door’ of a household to green space access points, even if nodes in the network are some distance away (see Technical Annex for more details). While this correction has been applied to majority of households, there are some which do not have the corresponding network relationship information to make the calculations and therefore the adjustment is not applied. In this analysis 0.09% of households do not use this method to adjust distance to green space calculated, and the straight line distance from household to the nearest associated road node was used instead. For these households this likely leads to an underestimation of the distance to the nearest green space.

Distance from access points to nodes

Unlike addresses, green space access point data (both existing and those created for these analyses) do not have attributed roads to use in the process of pairing with nodes in the network, so the nearest node (using straight line distance) to each access point is used as the destination node. In some cases, this may add excessive distance to the results while in other cases it may be an underestimation as a straight line distance does not account for the layout of infrastructure such as paths and roads.

Border areas

These statistics are produced for England. However, as the borders with Scotland and Wales are fully accessible, in reality, occupants of households may cross national borders to access green space. Only the green space access points provided in the Ordnance Survey Open Greenspace dataset cover Wales and Scotland, and therefore provide potential destinations in the model. For all other access points generated, their spatial extent is limited to England. Therefore, for households close to the border, there may be an overestimation in the distance to green space access points.

Rights of way integration

Ordnance Survey Mastermap Highways (Roads and Paths) data does partially represent the public rights of way network in England, especially in urban and suburban areas where rights of way are likely to be physical paths and roads. However, it does not provide full coverage, and therefore some areas will have a lack of coverage in the network part of the model.

Rights of way data collated by Natural England are more complete, but are not ‘network ready’, i.e. they are not provided with topological relationships to Ordnance Survey link and node data. These data have been used to generate access points where relationships with rights of way are required, but have not been integrated into the network. See Development Plan section for plans to pursue this work. Consequently, the model likely overestimates distances between households and green spaces, especially in rural areas.

Disconnected parts of the network

Small parts of the roads/path network are disconnected from the wider network as a whole. This could be a natural feature of the data, or due to the tiling approach taken or due to the removal of links such as motorways. If a household or access point is associated with a node in a disconnected part of the network, then shortest path calculations in these areas may be incorrect.

Question 9

Development Plan

Accepted Answer

As an official statistic in development, we intend to continue to improve the datasets and methodology used in the analyses as well as the outputs produced. The development of the statistics will be guided by feedback from users, while we also plan to address the areas listed below.

Developments planned for the next statistical release to be published in 2025:

Blue spaces are outdoor environments that prominently feature water, such as rivers, lakes and the sea, and are accessible to people. Currently, no blue space access point dataset (comparable to green space access point data) exists for England. Therefore, we plan to develop this dataset as part of the Natural England Green Infrastructure work programme, so that it can be used both in work relating to that programme and the development of these statistics.
Currently, the roads network used in all scenarios includes restricted access roads. We plan to add weightings to the network to strongly discourage the use of such roads in shortest path calculations. In this release, the decision to include them has been based on the fact that, for some households, the nodes that form part of restricted access roads are the source nodes for the shortest path analysis. Therefore, removing these features would reduce the accuracy of shortest path calculations for those households.
Ordnance Survey road network data contains an attribute which describes the presence of pavements alongside roads. We plan to assess the quality and then integrate this into the network model, weighting roads of certain types that have pavements more favourably than those without. An assessment on the coverage of these data is required.
Ordnance Survey road and path network data contains an attribute which describes the elevation gained when traversing each segment of path or road. We plan to assess the quality and then integrate these data to weight routes which involve elevation gain, accounting for the extra time required to walk up hill.
Currently, distances between green space access points and network nodes are not incorporated into the shortest path calculations. We plan to implement a similar method used for address to node relationships to better account for the distance between these features.

Longer term development plans:

Currently, results from the analyses are presented in terms of household units. We are keen to explore whether we can incorporate the latest 2021 census data to produce statistics at the population level. In future development of this work, we plan to explore household to population relationships and will assess whether a robust relationship between the two can be established and applied to the data.
We would like to further refine our household classification by exploring whether the Ordnance Survey AddressBase Plus data can be linked with other data such as Valuation Office Agency data to further refine the assumption that an address is an occupied residential property.
Rights of way data are only partially represented in the Ordnance Survey Mastermap Highways (Paths and Roads) data. We plan to convert rights of way data compiled by Natural England into a network ready dataset, remove duplications in the Ordnance Survey data and run scenarios that utilise a fuller complement of rights of way.
We plan to explore if it is possible to integrate activity data from third-party sources to potentially generate new access points, but also validate the assumptions made in our access point generation.
The next release of the Indices of Multiple Deprivation is planned for 2025. We would like to explore the possibility of producing statistics that can contribute to this work.

Question 10

Acknowledgements

Accepted Answer

Thank you to the many people and organisations who have contributed by providing data and useful insights which contributed to developing the method behind these statistics.

Question 11

Technical Annex

Accepted Answer

Datasets

This section describes the datasets that were used in the analyses and how they were transformed.

Ordnance Survey AddressBase Plus

Ordnance Survey published version 12/09/2023 (Epoch 103).

These data consist of point geometries with a variety of attributes allowing users to classify and subset addresses, and link the data to other Ordnance Survey products such as MasterMap Highways. More information can be found at https://www.ordnancesurvey.co.uk/products/addressbase-plus.

This dataset was used under the Public Sector Geospatial Agreement.

Table 3 shows the AddressBase Plus class codes used to create a subset of the Unique Property Reference Number data.

Table 3. AddressBase Plus class codes used to create a subset of UPRN data.

Class Code	Class Description
RD	Residential Dwelling
RD01	Residential Dwelling - Caravan
RD02	Residential Dwelling - Detached
RD03	Residential Dwelling - Semi-detached
RD04	Residential Dwelling - Terraced
RD06	Residential Dwelling - Caravan
RD07	Residential Dwelling - Caravan
RD08	Residential Dwelling - Self Contained Flat (Includes Maisonette/Apartment)
RD10	Residential Dwelling - Privately Owned Holiday Caravan/Chalet
RH	Residential House in Multiple Occupation
RH01	Residential House in Multiple Occupation - HMO Parent
RH02	Residential House in Multiple Occupation - HMO Bedsit Other Non SelfContained Accommodation
RH03	Residential House in Multiple Occupation - HMO Not Further Divided
RI01	Residential Institution - Care/Nursing Home
RI02	Residential Institution - Communal Residence
RI03	Residential Institution - Residential Education

Ordnance Survey MasterMap Highways Network - roads

Ordnance Survey published version 03/10/2023.

These data are a unified network consisting of links (linestring geometries) and nodes (point geometries). The ID naming convention also allows for convenient integration with Ordnance Survey MasterMap Highways Network – Paths and Ordnance Survey AddressBase Plus data. More information can be found at https://www.ordnancesurvey.co.uk/products/os-mastermap-highways-network-roads.

This dataset was used under the Public Sector Geospatial Agreement.

Ordnance Survey MasterMap Highways Network - paths

Ordnance Survey published version 03/10/2023

These data are a unified network consisting of links (linestring geometries) and nodes (point geometries) for both paths and connecting links. Connecting links are features that link paths and roads. More information can be found at https://www.ordnancesurvey.co.uk/products/os-mastermap-highways-network-paths.

This dataset was used under the Public Sector Geospatial Agreement.

Ordnance Survey Open Greenspace

Ordnance Survey published version 01/05/2024

These data contain both polygon geometries representing green spaces such as public parks, playing fields, sports facilities and others, along with a set of access point geometries, More information can be found at https://www.ordnancesurvey.co.uk/products/os-open-greenspace

This dataset is provided under the Open Government Licence.

Contains OS data © Crown copyright [and database right] [2024].

Natural England Green Infrastructure - public rights of way

Natural England published version 1.2.

This dataset is a compilation of rights of way (linestring geometries) from highway authorities across England. Note: data for 48 authorities are not included. More information can be found at https://designatedsites.naturalengland.org.uk/GreenInfrastructure/UserGuide/Section03.aspx#prow.

This dataset is provided under the Open Government Licence.

Natural England Green Infrastructure - woodlands

Natural England published version 1.2.

This dataset is a compilation of data from Ordnance Survey, the National Forest Inventory and the Ancient Woodland Inventory. More information can be found at https://designatedsites.naturalengland.org.uk/GreenInfrastructure/UserGuide/Section03.aspx.

This dataset is provided under the Open Government Licence.

Office for National Statistics Output Areas

Office for National Statistics published version December 2021 (V8).

The “Output Areas (December 2021) Boundaries EW BFC V8” dataset was used to aggregate model outputs. This is the full resolution dataset, clipped to the coastline of England.

More information can be found at https://geoportal.statistics.gov.uk/datasets/ons::output-areas-december-2021-boundaries-ew-bfe-v9/about

The “Output Area (2021) to LSOAs to MSOAs to LEP to LAD (May 2022) Best Fit Lookup in EN” dataset was used to map the 2021 Output Areas to 2021 Middle layer Super Output Areas.

More information can be found at https://geoportal.statistics.gov.uk/datasets/ons::output-area-2021-to-lsoas-to-msoas-to-lep-to-lad-may-2022-best-fit-lookup-in-en/about

The “Output Area (2011) to Output Area (2021) to LAD (December 2022) Best Fit Lookup in EW” dataset was used to map 2021 Output Areas onto 2011 Output Areas.

More information can be found at https://geoportal.statistics.gov.uk/datasets/ons::output-area-2011-to-output-area-2021-to-lad-december-2022-best-fit-lookup-in-ew/about

Source: Office for National Statistics licensed under the Open Government Licence v.3.0

Contains OS data © Crown copyright and database right 2024.

Office for National Statistics Rural/Urban classification

Office for National Statistics published version January 2016.

The “Rural Urban Classification (2011) of Output Areas in EW” dataset was used to map urban/rural classifications on to the 2021 Census Output Areas.

More information can be found at https://geoportal.statistics.gov.uk/datasets/53360acabd1e4567bc4b8d35081b36ff/about

Source: Office for National Statistics licensed under the Open Government Licence v.3.0

Contains OS data © Crown copyright and database right 2024.

Office for National Statistics Countries

Office for National Statistics published version December 2023.

The “Countries (December 2023) Boundaries UK BFE” dataset was used to define the areas in which the shortest path calculations were run, in this case, England.

More information can be found at https://geoportal.statistics.gov.uk/datasets/ons::countries-december-2023-boundaries-uk-bfe/about

Source: Office for National Statistics licensed under the Open Government Licence v.3.0

Contains OS data © Crown copyright and database right 2024.

Office for National Statistics Built Up Areas

Office for National Statistics published version December 2022.

The built up areas dataset was used in the production of access points. This is a generalised dataset, created using 25m grid squares (GB BGG).

More information can be found at https://geoportal.statistics.gov.uk/datasets/ad30b234308f4b02b4bb9b0f4766f7bb/

Source: Office for National Statistics licensed under the Open Government Licence v.3.0

Contains OS data © Crown copyright and database right 2024.

Natural England National Nature Reserves (England)

Natural England published version 19/03/2024.

A dataset containing polygon geometries showing the boundaries of National Nature Reserves in England. More information can be found at https://www.data.gov.uk/dataset/726484b0-d14e-44a3-9621-29e79fc47bfc/national-nature-reserves-england.

This dataset is provided under the Open Government Licence.

Natural England Local Nature Reserves (England)

Natural England published version 10/05/2024.

A dataset containing polygon geometries showing the boundaries of Local Nature Reserves in England. More information can be found at https://www.data.gov.uk/dataset/acdf4a9e-a115-41fb-bbe9-603c819aa7f7/local-nature-reserves-england.

This dataset is provided under the Open Government Licence.

Natural England Millenium Greens (England)

Natural England data published 05/07/2018.

A dataset containing polygon geometries showing the boundaries of Millenium Greens in England. More information can be found at https://www.data.gov.uk/dataset/2aee95fc-80aa-4c5b-9377-74971fdc31c6/millennium-greens-england-polygons.

This dataset is provided under the Open Government Licence.

Natural England Doorstep Greens (England)

Natural England data published on 05/02/2024.

A dataset containing polygon geometries showing the boundaries of Doorstep Greens in England. More information can be found at https://www.data.gov.uk/dataset/6a80e5a7-017e-49ba-a981-5cd0c727086f/doorstep-greens-england-polygons

This dataset is provided under the Open Government Licence.

Natural England Country Parks (England)

Natural England data published on 18/11/2022.

A dataset containing polygon geometries showing the boundaries of Country Parks in England. More information can be found at https://www.data.gov.uk/dataset/e729abb9-aa6c-42c5-baec-b6673e2b3a62/country-parks-england.

This dataset is provided under the Open Government Licence.

Natural England CRoW Act 2000 – Access Layer

Natural England data published on 15/02/2020.

A dataset containing polygon geometries showing the boundaries of Access Land as mapped under the CRoW Act.

More information can be found at https://www.data.gov.uk/dataset/05fa192a-06ba-4b2b-b98c-5b6bec5ff638/crow-act-2000-access-layer

This dataset is provided under the Open Government Licence.

Natural England CRoW Act 2000 – Section 15 Land

Natural England data published on 15/11/2023

A dataset containing polygon geometries for land subject to pre-existing public access rights that on CRoW access land apply instead of the CRoW rights.

More information can be found at https://www.data.gov.uk/dataset/f7255820-97d1-4891-aa7c-b6a2baa1e2b6/crow-act-2000-section-15-land

This dataset is provided under the Open Government Licence.

Access points

Access points used across the scenarios were a combination of both pre-created (already published) and those created specifically for these analyses.

Pre-created access points

Ordnance Survey Open Greenspace Access Points

Greenspace access points were acquired from the Ordnance Survey Open Greenspace data product. This data product also provides data representing the location and extent of green spaces, such as public parks, playing fields, sports facilities, play areas and allotments, which are likely to be accessible to the public. The point dataset joins to the polygon dataset allowing each point to be associated to a particular green space. The size and type of associated green space was then used to filter access points to match scenarios.

Access points created for these analyses

Doorstep Greens / Millenium Greens / Local Nature Reserves / Country Parks

It was assumed that once accessed, Doorstep Greens, Millennium Greens, Local Nature Reserves and country parks are free to access in their entirety. All four of these green space types are provided as polygon data by Natural England, and the public rights of way data is available from Natural England’s Green Infrastructure project. The following methodology was followed to create access points for these types of green space:

Polygons representing the green space feature were buffered by 10 m. This was to account for the poor topological representation of some rights of way. Buffering was used to link up very close types of that green space feature, where a minor road/path may provide a barrier in the data but provide minimal disruption to the green space experience in reality.
The buffered polygons were dissolved to ensure the removal of internal overlapping boundaries. Internal polygon boundaries were removed to create a single polygon for neighbouring (within 10 m) green space parcels.
For each polygon created in previous steps, the area was calculated.
The original polygons representing green space features were then erased from the buffered polygons created in the previous steps. This resulted in polygons representing the buffer zone (area between the original green space boundary and the buffered green space boundary) which were associated with an area figure for each green space network.
Sections of public rights of way falling within the green space buffer zones were extracted.
Access points were generated from the start and end points of the extracted public rights of way sections.

The rationale for the buffer zone approach was to make sure that rights of way that fell within the buffer zone (i.e. within 10 m of the original green space polygon boundaries) but did not cross the buffered green space polygon boundary (usually because they met a path or road within the buffer zone) were captured as likely access points (Figure 6). This did result in the production of a greater number of access points, but it did not impact the shortest path calculations, as the destination is only ever one location per household.

Golf courses / National Nature Reserves / woodlands

Golf Courses, National Nature Reserves and Woodlands are not by default fully accessible. Therefore, access points were generated for these green space types where public rights of way intersect them and the public right(s) of way are contiguous within the green space for at least 250 m. Golf courses were extracted from the OS Open Greenspace data product, National Nature Reserve polygons are produced by Natural England and Woodlands data was acquired from the Natural England Green Infrastructure dataset. Rights of way data also from the Natural England Green Infrastructure dataset were used. The following methodology was followed to create access points for these types of green space (Figure 6):

Polygons representing the green space feature were buffered by 10 m. This was to account for the poor topological representation of some rights of way. Buffering was used to link up very close types of that green space feature, where a minor road/path may provide a barrier in the data but provide minimal disruption to the green space experience in reality.
A subset of rights of way was created by intersecting them with the polygons created in step 1.
Rights of way lines were buffered by 5 m, combined and dissolved to create polygons representing contiguous rights of way.
The polygons created in the previous step, were subset, keeping those where the perimeter is at least 500 m (representing approximately 250 m of contiguous rights of way).
The green space polygons from step 1 were subset, selecting those that contained the contiguous rights of way polygons created in step 4. This subset of green space polygons had at least 250 m of contiguous rights of way within them.
The subset of green space polygons from the previous step were altered, erasing the original green space polygons from them. This resulted in polygons representing the buffer zone (area between the original green space boundary and the buffered green space boundary).
Sections of rights of way falling within the green space buffer zones were extracted.
Access points were generated from the start and end points of the extracted right of way sections.

The rationale for the buffer zone approach was to make sure that rights of way that fell within the buffer zone (i.e. within 10 m of the original green space polygon boundaries), but did not cross the buffered green space polygon boundary (usually because they met a path or road within the buffer zone) were captured as likely access points. This does result in the production of a greater number of access points, but this does not impact the shortest path calculations, as the destination is only ever one location per household.

Figure 6: The approach to generating access points, where at least 250 m of contiguous rights of way are present within the green space.

Notes for Figure 6:

A diagram showing a greenspace, represented by an irregular shaped polygon with a buffer around its perimeter. Overlaid on top is a set of lines representing rights of way, these also have a buffer around them.
At the locations where the rights of way cross the borders of the greenspace polygon and its buffer, access points are shown as diamonds.
At two points (once inside, and once outside the buffer of the greenspace polygon) the rights of way join onto nodes and links, represented by circles and lines respectively.
Three boxes annotate the diagram showing that the rights of way are greater than or equal to 250 m in length, that the buffer is used to resolve topological issues and that access points are generated where Rights of Way meet the network within the buffer zone.

Open access land

The Countryside and Rights of Way Act 2000 (CRoW Act) normally gives a public right of access to land mapped as ‘open country’ (mountain, moor, heath and down) or registered common land. Additionally, some land is subject to pre-existing access rights which predate the CRoW Act; this is known as Section 15 land. Collectively this ‘open access land’ is free to access in its entirety and can be accessed on foot by any available route. Open access land data was created by combining polygon datasets for CRoW access land and Section 15 land as published by Natural England. The following methodology was then used to create the access points:

Open access land polygons were buffered by 10 m. This was to account for the poor topological representation of some rights of way and to link up very close green space features, where a minor road/path may provide a barrier in the data but provide minimal disruption to the green space experience in reality.
Internal polygon boundaries were removed to create single polygon for neighbouring (within 10 m) open access land parcels.
For each polygon created in previous steps, the area was calculated.
Access points were generated where routes (paths, roads (excluding motorways) and rights of way) intersected the boundary of open access land polygons created in previous steps.

Public rights of way

In non-built-up areas, there are fewer municipal green spaces, and the rights of way network provides people with an opportunity to access green spaces. An access point dataset was generated representing the locations where the Ordnance Survey Highways road and path network likely provide access to parts of the public rights of way network that are of a minimum contiguous distance in non-built-up areas. Along with the OS Mastermap Highways data, the Public Rights of Way and Built Up Areas datasets were used to achieve this (Figure 7). The following procedure was undertaken:

Rights of way lines were extended by 10 m in both directions (to account for differences in the accuracy of connections between datasets).
Extended rights of way lines were intersected with Ordnance Survey Mastermap Roads and Paths data, forming a rights of way access point dataset.
Rights of way lines were buffered by 5 m, unioned and dissolved to create polygons representing contiguous rights of way.
The contiguous polygons were intersected with the Built Up Areas data, and the proportion of the polygon in a built-up area calculated.
The total perimeter of each contiguous polygon was calculated.
The contiguous polygons were subset firstly by selecting those with a perimeter of at least 500 m and then those that have a proportion of built-up area coverage less than or equal to 25%.
The subset of contiguous polygons was intersected with access points created in step 2 to create a subset of access points.
Built-up areas were negatively buffered by 250 m, creating a ‘core built-up area’ polygon dataset.
The subset of access points created in step 7 were further subset, removing those that intersected the ‘core built-up area’ polygons.

The rationale for the filtering criteria in step 6 is that a perimeter of 500 m would equate to approximately 250 m of right of way, a substantial amount of contiguous accessible path/road. The built-up area coverage of less than or equal to 25% was used to capture parts of the rights of way network that begin or end in built-up areas but provide access to rural areas. From an examination of the data, 25% provided a good balance to screen out majorly built-up parts of the rights of way network, while keeping those that were majority non-built-up with a relatively small built-up component. The second pass spatial filtering using ‘core built-up areas’ (step 8) is used to exclude access points that are deep within urban areas, despite the overall connected network being majority non built-up.

Figure 7: The approach to producing rights of way access points using two criteria.

Notes for Figure 7:

A diagram showing a set of connected lines representing rights of way. A buffer surrounds the rights of way, showing that they are one contiguous network of routes. At one point the network of routes overlaps an irregular shaped polygon which represents a built-up area.
Also present are network nodes and links, represented by lines and circles.
Diamond symbols represent access points where the rights of way meet the network nodes and links.
Boxes with annotation text describe the criteria used to generate the access points.

Network

Households and node relationships

OS AddressBase Plus point geometries are typically not directly represented by nodes in the network. This means that there is a discrepancy in the distances calculated in the shortest path analysis, and the actual distance from the ‘front door’ of the household to a green space. A two stage process was undertaken to account for these differences:

Stage 1, when available, the relationship between OS AddressBase Plus and OS Mastermap Highways data was used to identify the network node associated with the household (Figure 8A).

The links associated with each address were joined to the household data using the ‘osRoadLinkTOID’ attribute.
The two nodes associated with the link were joined to the household data.
The straight-line distances between the household and each of the two nodes were calculated.
The node with the shortest distance was identified as the starting node for a given household.
For households without an ‘osRoadLinkTOID’ attribute, the start node was identified by finding the nearest node (using straight-line distance) in the network. This differs from the previous steps, as the closest node may not be a node associated with a road/path used to access an address.

Stage 2, the distance between the household and its associated road/path, and the distance from the closest point on the road/path to the household to nodes at either end of the associated road/path was calculated. The three distance values were then used to adjust the shortest path distance once it was calculated (Figure 8B).

Using the same associated links and nodes as described in stage 1, the straight line distance from a household to its associated road was calculated.
From the point on the road/path identified in step 1, the distance along the road/path to each of the two associated nodes was calculated.
Using the shortest path model outputs to indicate which roads were traversed, the relevant node distance from step 2 was selected and added to/subtracted from the distance calculated in step 1.
Using the three values calculated in steps 1 and 2, along with outputs from the shortest path model that indicated which nodes were traversed, an adjustment was made to the shortest path distance, to account for the route taken from the ‘front door’ of the household.

For the small number of households with no associated road/path data, the straight-line distance to the node was used instead. Using the above calculations and adjustment, a more accurate distance to green space access points was calculated for each household.

Figure 8: Household to node relationships. Firstly, the nearest associated node is identified (A), and then the distance from the household to that node calculated (B).

Notes for Figure 8:

A diagram with two parts, A and B.
In part A the diagram shows one household and a network made of nodes and links, represented by lines and circles. One of the links is annotated as the associated link for the household. The nodes (circles) at either end of that link are labelled as associated nodes. There are dashed lines between the household each of the associated nodes. An annotation text box explains that the distance to one of the nodes is shorter than the other and therefore that node is selected as the ‘starting node’ for the shortest path calculation.
In part B, the same household and network links and nodes are shown. Additionally, there is a dashed line from the household to the associated link, and another dashed line to the associated node. These two lines are labelled as distance A and distance B respectively. From the start node, a yellow highlighted follows the network links to show the shortest path taken. An annotation text box described how distances A and B are added to the shortest path distance for a more realistic distance calculation.

Green space access points and node relationships

Unlike address points, access points do not have corresponding links/nodes as they are derived from a variety of sources. Therefore, the nearest node (straight line distance) in the network was assigned as the destination node in the shortest path calculation.

Scenario details

Scenario 1 – All green space

The following were included where the size of the green space is greater than or equal to 2 hectares:

Cemeteries (OS Greenspace)
Play Spaces (OS Greenspace)
Playing Fields (OS Greenspace)
Public Parks or Gardens (OS Greenspace)
Religious Grounds (OS Greenspace)
Millenium Greens
Country Parks
Doorstep Greens
Local Nature Reserves
Open Access Land

The following were included where the minimum contiguous right of way green space experience was >=250 m:

Woodlands
National Nature Reserves
Golf Courses

Access points for the above green spaces are a combination of OS Greenspace data and locations where rights of way intersect any polygon representing the above typologies. A distance threshold between household and green space access point of 1 km was used. This distance was chosen to represent an approximated 15 minute walk at 4.0 km/h (a walking speed taken from: https://assets.publishing.service.gov.uk/media/5dfa46f2ed915d54ab87c859/notes-and-definitions.pdf).

Scenario 2 – All green space and rights of way access points

All of the green spaces listed in Scenario 1 and additionally:

Rights of way access points

A distance threshold between household and green space access point of 1 km was used.

Scenario 3 – Accessible Greenspace Standards Doorstep standard

The following were included where the size of the green space is greater than or equal to 0.5 hectares:

Playing Fields (OS Greenspace)
Public Park or Garden (OS Greenspace)
Millenium Greens
Country Parks
Doorstep Greens
Local Nature Reserves
Open Access Land

A distance threshold between household and green space access point of 200 m was used.

Scenario 4 – Accessible Greenspace Standards Local standard

The following were included where the size of the green space is greater than or equal to 2 hectares:

Public Park or Garden (OS Greenspace)
Millenium Greens
Country Parks
Doorstep Greens
Local Nature Reserves
Open Access Land

A distance threshold between household and green space access point of 300 m was used.

Scenario 5 – Accessible Greenspace Standards Neighbourhood standard

The following were included where the size of the green space is greater than or equal to 10 hectares:

Public Park or Garden (OS Greenspace)
Millenium Greens
Country Parks
Doorstep Greens
Local Nature Reserves
Open Access Land

A distance threshold between household and green space access point of 1 km was used.

Scenario 6 – Accessible Greenspace Standards combined standard

Scenarios 3 to 5 are combined, where a household is considered to have access to green space if they meet the criteria of the Doorstep standard (Scenario 3) and the Local standard (Scenario 4) and the Neighbourhood standard (Scenario 5) concurrently.

Distance thresholds are applied as laid out in each separate scenario.

Scenario 7 – Accessible Greenspace Standards partial combined standard

A mixture of scenarios 3 to 5. In this scenario, households are considered to have accessible green space where the Neighbourhood standard (Scenario 5), and one of either the Doorstep standard (Scenario 3) or Local standard (Scenario 4) have been met. This matches criteria described in the Natural England Green Infrastructure Standards for England (p. 32).

Distance thresholds are applied as laid out in each separate scenario.

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Key messages

Introduction