HOUSING AND SPATIAL DATA From sites to insights: the case for a geospatial approach to understand London’s housing future
- Katharine Rowland
- 2 days ago
- 10 min read
 | Kat joined Knight Frank in April 2025 as a Senior Analyst, specialising in geospatial analysis to identify, interpret and present key insights into the UK property market. She holds a BSc in Geography from Durham University and a Master’s in Climate Change from the University of Leeds. Prior to Knight Frank, Kat worked at Esri UK in Technical Support, as a GIS analyst for the Ribble Rivers Trust, and as an environmental consultant at Eunomia. Her interests include leveraging spatial data and GIS techniques to address environmental challenges and presenting environmental and social data in clear, engaging ways that communicate issues and solutions to a wider audience. |
Kat explains how she built a spatial dataset of site allocations and developed a methodology to analyse the distribution and characteristics of future housing in London, in advance of the release of the 2026 London Plan. Kat suggests a mechanism to improve housing delivery: “If local plan adoption were accompanied by the release of highquality spatial data, it could play a transformative role in guiding land agents and developers in realising the local authority’s vision.” |
Challenging housing targets
I recently joined Knight Frank’s Research Analytics team. Recent projects include visualising how student populations move between neighbourhoods over time and how this varies across demographic groups; modelling travel times and amenity provision around a proposed Build to Rent asset; and identifying suitable land parcels for ground-mounted solar installations close to major energy off takers.
It’s been an exciting time to join a leading research team in the real estate sector. It is widely acknowledged that there is a chronic shortage of affordable housing in the UK. Consequently, there is currently an intense political and media spotlight on housing delivery and the viability and locations of new developments. This has led to heightened demand for clear, data-driven evidence on the feasibility of housing schemes and the likely trajectory of housing supply.
This is especially pressing in London. The next iteration of the London Plan – produced by the Mayor of London and the Greater London Authority – is expected in summer 2026. This highly anticipated development strategy will define the capital’s planning and housing ambitions, along with the policy mechanisms required to achieve them, making it a pivotal document for London’s future.
The publication of the ‘Towards a new London Plan’ (1) consultation document in May 2025 outlined the key themes that are likely to form the foundation of the new plan and invited stakeholders to respond. One of the most significant proposals was the ambitious requirement for London boroughs to deliver 880,000 new homes over the next decade. This prompted Knight Frank to assess the feasibility of meeting this target by examining the existing pipeline of planned housing.
Research geodata
The best available data on future homes in London is the housing site allocations in the local plans provided by individual boroughs. Site allocations in local plans set out where housing development could occur. Although they are indicative – reflecting potential for housing, rather than developer intention or planning permission – they remain the best available proxy for estimating how many homes may realistically be developed over the next 10 years.
The first steps were to establish how many homes each London borough has identified potential sites for and where, as set out in their local plans. This comprehensive dataset would be hugely valuable in addressing a range of key questions, such as: are future housing sites sufficiently well-connected to appeal to new residents? Who owns the land earmarked for development? Are boroughs primarily focusing on infill opportunities in existing neighbourhoods, or on larger-scale growth in new areas? How do these trends differ between boroughs?
However, these seemingly straightforward questions quickly proved challenging to answer. The London Datastore’s ‘Planning Local Plan Data’ (2) dataset includes a bundle of spatial data from all 35 London local planning authorities (LPAs) – the 32 boroughs, the City of London, the Old Oak and Park Royal Development Corporation, and the London Legacy Development Corporation (3). Yet only 21 of these authorities had provided geospatial data for their site allocations, and of these, 11 related to allocations from outdated local plans, meaning these sites are likely to have already been developed. As a result, the official London datastore provided usable, up-to-date site allocations data for fewer than a third of authorities.
There is a statutory requirement for planning authorities to publish a Policies Map alongside their local plan documentation (4). These maps are accessible online for most boroughs, though they are typically provided as interactive web maps rather than as downloadable spatial data. The existence of these implied that LPAs already hold spatial data for site allocations, which suggested that submitting Freedom of Information (FOI) requests to the remaining boroughs for the underlying site allocation GIS data would not create an unreasonable burden. This process was successful and increased the total number of available site allocation datasets to 22 boroughs. I’d like to thank the council officers from the additional 12 planning authorities who responded and shared their boroughs’ geodata.
Our research demonstrated that there were eight authorities where data is not available. The City of Westminster and City of London do not publish housing site allocations. There are six boroughs that have not published any forward-looking site allocations; the only available site allocations for these come from older local plans (e.g., from 2008). Additionally, none are currently reviewing or preparing a new local plan, so no new site allocations are publicly available for these.
The FOI requests to the remaining five boroughs were either declined or went unanswered. I therefore went back to basics and manually digitised these site allocations in ArcGIS Pro using the online Policy Maps and/or the detailed illustrations within the boroughs’ local plans. While these boundaries are not perfect – and should be treated as indicative in any detailed analysis – they provide a sufficiently reliable representation for inclusion.
Putting numbers and delivery times to site allocations
The outcome of this process was a single dataset covering all housing site allocations across 27 London LPAs. The next step was to enhance the spatial data with consistent attribution, most importantly the expected number of housing units for each allocation and the projected delivery timeframe. This stage took longer than anticipated (for reasons discussed later), but the outcome is a rich and standardised dataset that enables robust geospatial analysis of housing sites across London.
One of the most valuable analyses we have conducted was examining whether the planned new homes are in areas with sufficient public transport connectivity. This theme is particularly important because connectivity is a critical factor influencing the attractiveness and viability of new housing and advancing policy goals to reduce car use and dependence. The recent government announcement that housebuilding around train stations will be given automatic approval (5) emphasises the importance of public transport connections for new homes.
To assess this, we intersected the site allocation dataset with Transport for London’s (TfL’s) 2031 Projected Public Transport Access Level (PTAL) Index (6,7) to identify future accessibility for each proposed residential site, and plotted trends in connectivity.
Connectivity of housing sites
There is a significant variety between boroughs – for example, in Lambeth (Figure 1a) the proportion of residential units with ‘good’ connectivity is 88% (exceeding the current London average of 30%), with none of the proposed allocations having ‘poor’ connectivity. This is in stark contrast with Richmond-upon-Thames (Figure 1b), where less than 10% of proposed residential units have ‘good’ connectivity, and 25% have ‘poor’ connectivity to public transport, exceeding the London average of 19%. We also compared the PTAL scores of proposed sites with existing homes, and analysed the difference in PTAL scores between 2023 (the most recently published dataset) and 2031 (TFL’s projected scores) to assess the impact of future upgrades.
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Figure 1: Public Transport Access Levels of proposed housing allocations across London boroughs, highlighting Lambeth (left) and Richmond-upon-Thames (right)
Green Belt land and housing sites
Another contemporary issue we have explored is whether London boroughs intend to use protected Green Belt land and Metropolitan Open Land to meet their housing targets. The 2025 London Plan consultation states a clear preference for prioritising housing development on brownfield sites within London’s existing urban footprint, but also acknowledges that brownfield land alone will not be sufficient to meet the government’s housing targets.
We concluded that only 4% of site allocations have a significant overlap (>5%) with protected land. Of these ~50 proposed site allocations, the majority are on land that already hosts pre-existing development and therefore is suitable for de-designation and/or development. The main exception to this is the borough of Enfield (around 33% of which is Green Belt), which has proposed to de-designate ~500 ha of Green Belt across 14 site allocations (see Figure 2) totalling 8,080 housing units, on the basis that that exceptional circumstances are met, as the need for new homes cannot be met on brownfield sites and underutilised land. This analysis helped to shed light on the current and projected use of protected land, providing evidence on a prevalent, and oftentimes contentious, topic.
Figure 2: one of the fourteen sites on Green Belt land that Enfield is intending to de-designate and develop
The ‘big picture’ for housebuilding
This geospatial dataset is immensely valuable for helping us to understand the ‘big picture’ of the future of housing in London. We are using it to explore questions such as who owns the land that is earmarked for development (categorised into private companies, publicly entities, local councils, housing associations and individuals) and the implications that this could have for the likelihood and viability of development; if or how redevelopment is complicated by the legacy of right to buy ex-council homes and how this further fragments ownership of sites that may be primarily council-owned; and whether new homes are planned in areas that have safe air quality levels.
Data comparison challenges and reforms
It is interesting to reflect on the challenges faced during this data collation process. One of the most significant difficulties was the wide variation in the recency of local plans, which made cross-borough comparisons problematic. There is also inconsistency in timescales: boroughs are operating independently with no common alignment to the London Plan or to each other. Some authorities are not currently progressing a local plan, while others are at different stages of adoption. Collectively, this means that establishing a standardised dataset is more complex than it initially appears, as site allocations included in the research vary from borough to borough, in terms of certainty and planned delivery horizons.
There is also substantial variation in how local plans are structured and the level of detail they provide. Site allocations are presented in different formats, and the information included differs considerably between boroughs. In several cases, neither the expected number of housing units nor the delivery timeline was supplied. Moreover, data is expressed inconsistently: some plans used phases from the plan date (e.g., 1–5 years), others used calendar year bands (e.g., 2025–2030), while others provided descriptors such as “medium term”, adding further ambiguity and complexity.
Another challenge is that key information is difficult to locate. It is not always clear whether a local plan is adopted or under review, and details such as the number of housing units may be buried in appendices or supplementary documents, rather than in the main plan. All these factors contributed to the process of building a standardised shapefile taking longer than anticipated.
These challenges led us to consider the substantial value that could arise from introducing a standardised geospatial format for site allocations (or local plans more broadly). Geospatial data is fundamental for evidence-based decision-making, yet there is no requirement for local plan spatial datasets to be published beyond the plan boundary and online policy maps. Standardising format and content of data within local plans would reduce analytical complexity. If local plan adoption were accompanied by the release of highquality spatial data, it could play a transformative role in guiding land agents and developers in realising the local authority’s vision. The absence of such data represents a missed opportunity to support economic activity and accelerate the delivery of muchneeded homes.
The UK government has announced that reforms to the local plan system will be introduced in early 2026, including requirements for standardised data formats and dedicated guidance to support plan makers. A valuable existing resource is MHCLG’s Local Plan tracking tool (8), which allows users to monitor the status and progress of local plans across the country.
A government geospatial data standard for local plans is in development (9), and our findings suggest that extending this standard to cover site specific information – such as location, size and projected delivery timeline of housing allocations – would greatly improve accessibility and analytical value. Ireland’s National Planning Geospatial Data Hub (10) is a striking and successful example of when high-quality geospatial data is treated as essential planning infrastructure rather than an optional addon. A similar coordinated national approach in the UK could lead to the collation and open sharing of geospatial planning data to support a wide range of stakeholders to make more informed decisions.
Knight Frank’s Research and Analytics teams is continuing to use this dataset to explore London’s future housing trajectory, identifying patterns and insights to inform where new homes should be delivered. We hope this article demonstrates the significant value of applying geospatial analysis to housing data and underscores the importance of improving the consistency with which this information is published.
Notes:
This research was conducted in summer 2025 and subsequent updates or developments may not be captured
This research has been conducted for London, given the upcoming publication of the 2026 London Plan, but all the data used are publicly available from local plans, hence the method is replicable to other regions.
References
https://data.london.gov.uk/dataset/planning-local-plan-data-2zjmn/
The London Legacy Development Corporation (LLDC) and the Old Oak Park Royal Development Corporation (OPDC) are designated development corporations responsible for overseeing planning and development within specific opportunity areas in London. Each acts as the local planning authority for its respective area, and has published a Local Plan for the current period. As a result, site allocations within overlapping boroughs are not included in their local plans and hence LLDC and OPDC are analysed in this research as separate entities
Regulations 5 and 9 of the Town and Country Planning Regulations 2012 and the National Planning Policy Framework
https://www.gov.uk/government/news/housebuilding-around-train-stations-will-be-given-default-yes
The 2023 PTAL dataset is available online at https://gis-tfl.opendata.arcgis.com/datasets/0646faf45243463aa04ca685e598f471; the 2031 dataset was accessed via FOI
Though PTAL scores are only calculated for London, the new MHCLG Connectivity tool could be used to replicate this analysis for the rest of the UK: https://www.gov.uk/ guidance/connectivity-tool
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