This map was created by the GLA in 2017 as a preliminary analysis of the potential for woodland creation in London’s Green Belt, which covers 35,000 hectares. The map shows land in London’s Green Belt which could have potential for woodland creation, described as, ‘plantable areas’, based on an assessment of land use data.

IPG 6 Green Belt

Green Belt - The functions of the Green Belt are to: check the unrestricted sprawl of large built-up areas; prevent neighbouring towns from merging into one another; assist in safeguarding the countryside from encroachment; preserve the setting and special character of historic towns; and assist in urban regeneration, by encouraging the recycling of derelict and other urban land.

For more information please see our online map Unitary Development Plan 2006

This data has been derived from Ordnance Survey base mapping. (C) Crown copyright [and database rights] (2019) OS (licence 100023069).

Spatial Data layers referenced in City Development Plan Policy and Proposals & Supplementary Guidance Maps. Third party data displayed in the above mentioned maps are not included herein.

1. Cultural Ecosystem Services (CES) encompass a range of social, cultural and health benefits to local communities, for example recreation, spirituality, a sense of place and local identity. However, these complex and place-specific CES are often overlooked in rapid land management decisions and assessed using broad, top–down approaches. 2. We use the Toolkit for Ecosystem Service Site-based Assessment (TESSA) to examine a novel approach to rapid assessment of local CES provision using inductive, participatory methods. We combined free-listing and participatory geographic information systems (GIS) techniques to quantify and map perceptions of current CES provision of an urban green space. The results were then statistically compared with those of a proposed alternative scenario with the aim to inform future decision-making. 3. By identifying changes in the spatial hotspots of CES in our study area, we revealed a spatially-specific shift toward positive sentiment regarding several CES under the alternative state with variance across demographic and stakeholder groups. Response aggregations in areas of proposed development reveal previously unknown stakeholder preferences to local decision-makers and highlight potential trade-offs for conservation management. Free-listed responses revealed deeper insight into personal opinion and context. 4. This work serves as a useful case study on how the perceptions and opinions of local people regarding local CES could be accounted for in the future planning of an urban greenspace and how thorough analysis of CES provision is important to fully-inform local-scale conservation and planning for the mutual benefit of local communities and nature.

Analysis of Ordnance Survey (OS) data on access to private gardens, public parks and playing fields in Great Britain, available by country, region, Local Authority and Middle Layer Super Output Area. This page also includes Natural England survey data on garden access in England, broken down by personal characteristics such as age and ethnicity.

Overview The Green Infrastructure Areas for the Black Country (GIBC) data identifies green infrastructure, green infrastructure function (or ecosystem service) and pinch point mapping for the Black Country area which includes Wolverhampton, Walsall, Sandwell and Dudley. The analysis was carried out in two stages and as a result of this, four datasets were produced: ‘GIBC 01 - Typology & Functionality OS’ ‘GIBC 02 – Pinch Points OS’ ‘GIBC 03 – Pinch Points Consortium Housing’ ‘GIBC 04 – Pinch Points Housing Land Availability’ First Stage Processing Ordnance Survey data was used as the base layer for all the processing. The first process produced the ‘GIBC 01 - Typology & Functionality OS’ dataset. This dataset is then subsequently used as a basis for the production of the second, third and fourth datasets during the second stage. In the first stage each OS polygon was assigned a green infrastructure category based on the SPADES project from the list below.
Green Infrastructure Categories are: Garden Green corridor Pocket park Park or garden Outdoor sports facility Children’s play space Youth area Broadleaved woodland Mixed woodland Coniferous woodland Natural and semi-natural open spaces Pasture or meadow Wetland Watercourse Fresh water body Allotments Orchard Cemetery or churchyard Open space around premises Agricultural land Road island/verge Railway corridor Abandoned, ruderal and derelict area The OS polygon was then assigned “A function beneficial to people” dependent on the Green Infrastructure Category already assigned. The 26 categories that perform a “function beneficial to people” are: Accessible water storage Carbon storage Community cohesion Connection with local environment Corridor for wildlife Culture Encouraging green travel Evaporative cooling Flow reduction through surface roughness Habitat for wildlife Heritage Inaccessible water storage Learning Local food production Pollination Pollutant removal from soil/water Providing jobs Recreation - private Recreation - public Recreation - public with restrictions Shading from the sun Trapping air pollutants Visual contribution to landscape character Water conveyance Water infiltration Water interception In its simplest form the process flow looks like this: OS base layer → assigned green infrastructure → assigned function (Eg - OS polygon → coniferous woodland → shading from the sun) The first dataset, ‘GIBC 01 - Typology & Functionality OS’, therefore shows the following: The green infrastructure category The function beneficial to people Shows areas of greatest need for this function. Shows areas whereby the function has been met. Shows areas whereby the function has not been met. Second Stage Processing The second stage expands on the first by establishing which areas suffer from stress associated with investment in growth and redevelopment of land. These areas are known as ‘pinch points’. Wherever there is a high level of need for a particular function (identified in the first process), a potential ‘pinch point’ exists. The pinch point categories that have been identified are: Air Quality Pinch Culture Pinch Flooding Pinch Heat Stress Pinch Heritage Pinch Local Community Pinch Mental Health Pinch Nature Pinch Physical Activity Pinch Recreation Pinch Sustainable Travel Pinch The second dataset, ‘GIBC 02 – Pinch Points OS’, takes the analysis from the first stage process and using the Ordnance Survey data as a base layer, displays the ‘pinch points’ analysis results. The third dataset, ‘GIBC 03 – Pinch Points Consortium Housing’, takes the analysis from the first stage process and rather than using the OS as a base uses the Consortium Housing Site data instead to display ‘pinch points’. The fourth dataset, ‘GIBC 04 – Pinch Points Housing Land Availability’, takes the analysis from the first stage process and rather than using the OS as a base used the Strategic Housing Land Availability data instead to display ‘pinch points’. Conclusion The ‘pinch point’ mapping can help identify particular areas of stress, which when used in conjunction with the green infrastructure and function mapping from the first stage process can be used to help alleviate those stresses.

This layer explores the spatial relationship between accessibility of green spaces (measured as % LSOA covered by the respective green spaces and their ANGSt buffer) across the range of ANGSt Benchmarks and compares with one other variable.

          Attribute information in this layer can be found on
            Deprivation – as measured by the Index of Multiple Deprivation (MHCLG 2019)
            Population Density – Derived from ONS Census 2011In this system L, M and H refer to low, medium and high for the 

percentage of the LSOA that is covered by the green spaces and their respective buffers. The thresholds used are:

            L = Less than 5% coverage
            M = 5% to under 50%
            H = 50 % and over


            Codes 1, 2 and 3 are the relative bands for the other assessment variable.

          For IMD the thresholds are:

            1 = IMD decile 1 and 2 (Most deprived)
            2 = IMD deciles 3 to 8
            3 = IMD deciles 9 and 10 (least deprived)

          For population density the thresholds are:

            1 = Population 10,000 people per square kilometre and above
            2 – Population between 2500 and 10,000 people per square kilometre
            3 = Population under 2500 people per square kilometre


            The "Access to Natural Green Space 

Inequalities" maps only look at those green spaces that were used to run the England ANGSt analysis and were done only at LSOA level.

          LSOA may contain other green spaces whose presence will not be picked up

in this assessment. Refer to Natural England's user guide for more information on how this layer has been constructed https://designatedsites.naturalengland.org.uk/GreenInfrastructure/UserGuide/Section03.aspx#inequalities-angs

SUMMARYTo be viewed on combination with the dataset ‘Area of accessible green and blue space per 1000 population (England)’ and its associated metadata.This dataset identifies administrative areas for which Public Right of Way (PRoW) data was not available. While some gaps in the PRoW data will have been partially filled in by the OS MasterMap Highways Network Paths dataset, due to overlap between the two, some gaps will still remain. The area of accessible green/blue space in the areas highlighted by this dataset could be slightly under represented in the ‘Area of accessible green and blue space per 1000 population (England)’ dataset.COPYRIGHT NOTICEProduced by Ribble Rivers Trust. Contains Ordnance Survey data © Crown copyright and database right 2020. Contains public sector information licensed under the Open Government Licence v3.0.CaBA HEALTH & WELLBEING EVIDENCE BASEThis dataset forms part of the wider CaBA Health and Wellbeing Evidence Base.

Overview

An updated spatial data set for existing green roofs has been produced for London's Central Activities Zone (CAZ) using 2015 aerial imagery. The CAZ makes up around two per cent of London's total area.

Method

ArcMap GIS software was used to map green roofs installations. The aerial imagery was loaded into the software in true colour (RGB) and infrared (IR) composites, along with the CAZ boundary and London 500x500m Ordnance Survey grid to aid locating.

RGB images are useful for both roof types with IR being very good for identifying vegetation. IR allows for easy identification of vegetation due to it reflecting strongly in the near infrared (NIR) and appearing deep red in colour (healthy vegetation).

Challenges and solutions

The problem of judging elevation from aerial imagery, particularly of buildings with only a few stories can be partially overcome by comparing the location with Google Maps Earth view. This includes a digital elevation model that makes it easier to judge whether a green area is raised or at street level.

A number of small roof terraces in the CAZ have very dense vegetation along the edge of the roof. Where this kind of greening is spatially significant, the vegetation itself has been mapped rather than the full extent of the roof, in order to produce a more appropriate and accurate green area value.

Building shadows can mask the texture and colour of the roof. The use of NIR helps with green roof identification, as the contrast of the red of the vegetation with the surrounding area is far higher than in RGB, making the shadow less impactful.

Some roofs that appear very uniformly green in RGB may be Astroturf as opposed to a living green roof. This can usually be identified by inspecting the roof in IR, as it will not give the distinctive deep/bright red colours of living vegetation, displaying instead as blue-purple.

Even analysing a small area of London, such as the CAZ, takes a long time. This is the main reason why this study methodology has not been extended beyond the CAZ.

The Millennium Greens initiative set out to provide new areas of public open space close to people's homes that could be enjoyed permanently by the local community, in time to mark the start of the third millennium. They were to be breathing spaces - places for relaxation, play and enjoyment of nature and pleasant surroundings. They could be small or large, and in urban or rural locations. Full metadata can be viewed on data.gov.uk.

The habitat network maps seek to apply the best evidence and principles and to use the best available nationally consistent spatial data. The habitat network maps are developed around 4 distinct habitat components sets and include 4 distinct network zones where action may be undertaken to build greater ecological resilience. The different elements of the maps are described below.Habitat Components:The location of existing patches of a specific habitat for which the network is developed. This is termed the 'Primary habitat' e.g. lowland heathland. The main baseline data used for this is the Priority Habitat Inventories (PHI).The location of additional habitat that naturally form mosaics with the primary habitat e.g. habitats that are most likely to form ecological mosaics possibly used by species associated with the primary habitat. This is termed the 'Associated habitat'. The main baseline data used for this is the PHI.The locations where habitat creation or restoration is known to occur, this is primarily sites under relevant agri-environment options. This is termed the 'Habitat creation'.Sites where data suggests small fragments of the primary habitat or degraded habitat exists and where restoration may be possible, this is primarily developed from information held within the current PHI. This is termed the 'Restorable habitat'.Network Zones:Land within close proximity to the existing habitat components that are more likely to be suitable for habitat re-creation for the particular habitat. These areas are primarily based on soils but in many cases has been refined by also using other data such as hydrology, altitude and proximity to the coast. This is termed the 'Network Enhancement Zone 1'.Land within close proximity to the existing habitat components that are unlikely to be suitable for habitat re-creation but where other types of habitat may be created or land management may be enhanced including delivery of suitable Green Infrastructure. This is termed the 'Network Enhancement Zone 2'.Land immediately adjoining existing habitat patches that are small or have excessive edge to area ratio where habitat creation is likely to help reduce the effects of habitat fragmentation. This is termed the 'Fragmentation Action Zone'.Land within relatively close proximity to the Network Enhancement Zones 1 & 2 that are more likely to be suitable for habitat creation for the particular habitat and identifying possible locations for connecting and linking up networks across a landscape. This is termed the 'Network Expansion Zone'Note: For some habitat networks not all of the habitat components or all the action zones are identified either because the data does not exist or the habitat does not lend itself to identifying particular types of action. Further details are outlined in the Habitat Network Mapping Guidance document. The Network boundary is drawn around the 4 habitat components using a variable buffering process with a generalised distance of 500m although 1km was used for Blanket Bog. As the boundary for each habitat network is tightly drawn around the existing patches of habitat this means that at a national scale the habitat network is composed of a series of smaller ‘networks’ that encapsulates one or more clusters of existing habitat patches. These may be considered as ‘network segments’. The Network Expansion Zone has been drawn around these segments to identify areas where additional action may be undertaken to build greater ecological resilience across the wider landscape.Full metadata can be viewed on data.gov.uk.