Where should the government be directing the billions of investment for the Warm Homes Plan? Ordnance Survey (OS) has reviewed its data to highlight the hot and cold spots.
OS analysed around 23.6 million homes across Great Britain using the OS National Geographic Database (OS NGD). With more than 600 million features, the OS NGD was used to identify trends and compare physical characteristics of homes using a heat index score to assess how easy they are to heat and which households might be more vulnerable when temperatures drop.
The analysis considered:
- connected homes – properties with shared walls, such as terraced or semi‑detached properties, retain heat better than detached houses;
- period of construction (age of building) – older properties built before 1960 are less likely to have cavity walls, insulation or double glazing; and
- construction material – homes built with insulating materials lose heat more slowly.
Initial analysis confirms real-world experience: urban areas generally have a lower heat-loss risk – likely due to the urban heat island effect, higher ambient temperatures and denser, often newer housing stock. Coastal and remote areas, meanwhile, tend to be harder to heat.
The highs and lows
Diving into some of the detail made public by OS reveals that local authority districts in northern Scotland and Wales have the highest average heat-loss scores, suggesting more homes may be harder to heat. Na h-Eileanan an Iar (Western Isles) has the highest average score of 1.30, while Stevenage in Hertfordshire has the lowest at 0.26.
The scores give an indication of how hard it might be to heat up the average home in a local authority based on the three building characteristics. Across Britain, most local authority districts fall between 0.8 and 0.95, with a handful scoring 1 or higher.
Additional factors also play a role. In Cornwall, for example, the predominance of traditional granite-built homes can make insulation more challenging, OS said. Across England, around 25% of residential properties are detached, with every wall exposed to the elements. Other coastal areas with a higher heat index are Wales and Scotland, which also have a higher number of detached properties – 29% in Wales and 32% in Scotland.
In southern England, coastal towns like Bournemouth are commonly thought to benefit from a milder micro-climate due to the protection offered by the Isle of Wight. However, OS data shows homes in the area actually have a higher heat index, with 59% being built before the 1960s and almost 50% being standalone.
London’s diversity
In London, boroughs such as Tower Hamlets rank among the easiest to heat, likely due to the high proportion of flats (21%) with shared walls, modern construction standards, and the lowest percentage of pre-1960 buildings (37%). In contrast, Harrow is among the hardest to heat, largely because of its high number of standalone properties and the fact that 84% of its buildings date before 1960, meaning they are more likely to have older insulation standards.
Additionally, urban areas like London also experience the urban heat island effect, which could mean properties require less energy to heat.
Among older cities, York is surprisingly easier to heat than Winchester and St Albans, OS noted. In contrast, new towns such as Milton Keynes are also easier to heat, as the vast majority of homes were built after 1960, giving it the second-lowest heat index of all local authorities. Stevenage, the UK’s first New Town, has the lowest heat index overall and the highest proportion of homes built from 1960 onwards (87%) among local authority districts.
The OS data can be used to identify south-facing rooftops suitable for solar panels, which could help households reduce energy costs. In south Cambridgeshire, 14% of residential properties already have solar panels installed.
Wales a key focus?
The Warm Homes Plan may need to concentrate its efforts on Wales. It has the oldest housing stock in the UK, largely due to industrial-era terraced housing built during the 19th century for coal and steel workers, which might suggest poorer insulation, OS said.
Isabelle Chatel de Brancion, land and property lead at OS, said: “Understanding which homes are hardest to heat is critical for improving energy efficiency. OS data provides detailed insights into building age, construction materials, and location, enabling us to model heat-loss risk at scale. This data-driven approach helps pinpoint areas most vulnerable to heat loss and identify where energy-efficiency improvements would have the greatest impact.
“Beyond highlighting national patterns, OS data can also shed light on viable solutions such as identifying rooftops suitable for solar panels, informing town planning, and helping utility companies optimise renewable energy plans. These insights could support local authorities and homeowners in making informed decisions to keep homes warmer this winter and reduce costs.”
