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Find my areaComparing your home shortlist
Enter your workplace to see your commute area and check nearby places — or use “+ Add home” on the Home shortlist to drop a specific home on the map.
Example: EC4N 7TW · 45 mins by public transport
Generated on demand from the Geoapify Isoline API based on your entered address and chosen commute time.
Useful as the core 'can I actually get to work/school in a reasonable time from here' boundary that every other layer sits inside.
Sourced from OpenStreetMap via the Overpass API, covering Tube stations only.
Useful for gauging real commute convenience, since proximity to a Tube station typically matters more for day-to-day journey times than straight-line distance to central London.
Station pins sourced from OpenStreetMap via the Overpass API, covering London Overground and National Rail stations separately from the Underground.
Turning this on also draws London Overground's six real branch lines — Liberty, Lioness, Mildmay, Suffragette, Weaver and Windrush (the 2024 rebrand) — traced from OpenStreetMap's railway route relations, each in its own official colour.
Useful because some areas are poorly served by Tube but well served by Overground or rail, and which specific branch serves an address changes the journey options significantly.
Sourced from OpenStreetMap via the Overpass API, covering every aerodrome in the bounding box, not just major passenger airports, plus facility-level heliports such as London Heliport. Individual hospital, rooftop and private helipads are excluded.
At the five principal London airports, a black dashed 1 km line shows each reviewed runway's location and orientation. It is a reference indicator only — not the full runway, a flight path, frequency, altitude, or wind-dependent direction. Gatwick's northern runway is labelled separately because it is not in routine use.
Useful mainly as context alongside the aircraft-noise layer, and for anyone who flies regularly and values a short airport run.
Sourced from TfL's official Cycle Routes dataset — London's recognised current cycle network, shown as one line style: numbered Cycleways plus the small number of legacy Cycle Superhighways (CS7, CS8) still carrying that branding. Tap a route to see its name.
Quietways and any in-progress or planned route are deliberately not shown — this answers "where are London's recognised current cycle routes", not "where does any cycling infrastructure exist".
One pin per reported serious or fatal pedal-cycle casualty in Greater London over the latest five final years of police-reported STATS19 collision data. Slight-injury casualties are not shown.
Each pin sits at its collision's recorded coordinate; the popup gives the date and the conditions recorded at the time. There is no cycling-exposure denominator, so this is a count of reported harm, not a safety rate — a busy, well-used route can show more pins than a quiet dangerous one.
STATS19 covers only personal-injury collisions reported to police, and injury-severity reporting methods changed across police forces over this period, so the recent-year serious counts are not perfectly comparable to the earlier years.
Sourced from data.police.uk (Metropolitan Police and City of London Police) and aggregated into a roughly 0.65 km² hex grid. Each hex is shaded by the number of reported crimes per km² over a trailing 12-month window — a raw incident count normalised by area, not a per-resident rate.
This shows where incidents are reported, not how dangerous an area is to live in. Busy commercial, retail and nightlife districts — the West End, Camden, Shoreditch — always rank high because they are dense with footfall, visitors and shops, and most of those incidents do not involve local residents. Raw counts don't separate residential from commercial crime.
Every crime location published by police is deliberately anonymised, snapped to the nearest of roughly 750,000 fixed map points (street midpoints, parks, public places), never an exact address. It also reflects only crime reported to and recorded by police, which can differ from actual crime levels by area and crime type.
Sourced from data.police.uk (Metropolitan Police and City of London Police) and aggregated into a roughly 0.65 km² hex grid. Each hex is shaded by the number of reported crimes per km² over a trailing 12-month window — a raw incident count normalised by area, not a per-resident rate.
This shows where incidents are reported, not how dangerous an area is to live in. Busy commercial, retail and nightlife districts — the West End, Camden, Shoreditch — always rank high because they are dense with footfall, visitors and shops, and most of those incidents do not involve local residents. Raw counts don't separate residential from commercial crime.
Every crime location published by police is deliberately anonymised, snapped to the nearest of roughly 750,000 fixed map points (street midpoints, parks, public places), never an exact address. It also reflects only crime reported to and recorded by police, which can differ from actual crime levels by area and crime type.
Sourced from data.police.uk (Metropolitan Police and City of London Police) and aggregated into a roughly 0.65 km² hex grid. Each hex is shaded by the number of reported crimes per km² over a trailing 12-month window — a raw incident count normalised by area, not a per-resident rate.
This shows where incidents are reported, not how dangerous an area is to live in. Busy commercial, retail and nightlife districts — the West End, Camden, Shoreditch — always rank high because they are dense with footfall, visitors and shops, and most of those incidents do not involve local residents. Raw counts don't separate residential from commercial crime.
Every crime location published by police is deliberately anonymised, snapped to the nearest of roughly 750,000 fixed map points (street midpoints, parks, public places), never an exact address. It also reflects only crime reported to and recorded by police, which can differ from actual crime levels by area and crime type.
Sourced from data.police.uk (Metropolitan Police and City of London Police) and aggregated into a roughly 0.65 km² hex grid. Each hex is shaded by the number of reported crimes per km² over a trailing 12-month window — a raw incident count normalised by area, not a per-resident rate.
This shows where incidents are reported, not how dangerous an area is to live in. Busy commercial, retail and nightlife districts — the West End, Camden, Shoreditch — always rank high because they are dense with footfall, visitors and shops, and most of those incidents do not involve local residents. Raw counts don't separate residential from commercial crime.
Every crime location published by police is deliberately anonymised, snapped to the nearest of roughly 750,000 fixed map points (street midpoints, parks, public places), never an exact address. It also reflects only crime reported to and recorded by police, which can differ from actual crime levels by area and crime type.
Sourced from data.police.uk (Metropolitan Police and City of London Police) and aggregated into a roughly 0.65 km² hex grid. Each hex is shaded by the number of reported crimes per km² over a trailing 12-month window — a raw incident count normalised by area, not a per-resident rate.
This shows where incidents are reported, not how dangerous an area is to live in. Busy commercial, retail and nightlife districts — the West End, Camden, Shoreditch — always rank high because they are dense with footfall, visitors and shops, and most of those incidents do not involve local residents. Raw counts don't separate residential from commercial crime.
Every crime location published by police is deliberately anonymised, snapped to the nearest of roughly 750,000 fixed map points (street midpoints, parks, public places), never an exact address. It also reflects only crime reported to and recorded by police, which can differ from actual crime levels by area and crime type.
Sourced from data.police.uk (Metropolitan Police and City of London Police) and aggregated into a roughly 0.65 km² hex grid. Each hex is shaded by the number of reported crimes per km² over a trailing 12-month window — a raw incident count normalised by area, not a per-resident rate.
This shows where incidents are reported, not how dangerous an area is to live in. Busy commercial, retail and nightlife districts — the West End, Camden, Shoreditch — always rank high because they are dense with footfall, visitors and shops, and most of those incidents do not involve local residents. Raw counts don't separate residential from commercial crime.
Every crime location published by police is deliberately anonymised, snapped to the nearest of roughly 750,000 fixed map points (street midpoints, parks, public places), never an exact address. It also reflects only crime reported to and recorded by police, which can differ from actual crime levels by area and crime type.
Sourced from data.police.uk (Metropolitan Police and City of London Police) and aggregated into a roughly 0.65 km² hex grid. Each hex is shaded by the number of reported crimes per km² over a trailing 12-month window — a raw incident count normalised by area, not a per-resident rate.
This shows where incidents are reported, not how dangerous an area is to live in. Busy commercial, retail and nightlife districts — the West End, Camden, Shoreditch — always rank high because they are dense with footfall, visitors and shops, and most of those incidents do not involve local residents. Raw counts don't separate residential from commercial crime.
Every crime location published by police is deliberately anonymised, snapped to the nearest of roughly 750,000 fixed map points (street midpoints, parks, public places), never an exact address. It also reflects only crime reported to and recorded by police, which can differ from actual crime levels by area and crime type.
Sourced from data.police.uk (Metropolitan Police and City of London Police) and aggregated into a roughly 0.65 km² hex grid. Each hex is shaded by the number of reported crimes per km² over a trailing 12-month window — a raw incident count normalised by area, not a per-resident rate.
This shows where incidents are reported, not how dangerous an area is to live in. Busy commercial, retail and nightlife districts — the West End, Camden, Shoreditch — always rank high because they are dense with footfall, visitors and shops, and most of those incidents do not involve local residents. Raw counts don't separate residential from commercial crime.
Every crime location published by police is deliberately anonymised, snapped to the nearest of roughly 750,000 fixed map points (street midpoints, parks, public places), never an exact address. It also reflects only crime reported to and recorded by police, which can differ from actual crime levels by area and crime type.
Sourced live from the Environment Agency's Flood Map for Planning (Zone 2 and Zone 3, rivers and sea).
Useful as an early screening signal for flood exposure, insurance cost, and potential mortgage or planning scrutiny, though it ignores existing flood defences and doesn't cover surface water flooding.
Sourced live from the Environment Agency's Flood Map for Planning (Zone 2 and Zone 3, rivers and sea).
Useful as an early screening signal for flood exposure, insurance cost, and potential mortgage or planning scrutiny, though it ignores existing flood defences and doesn't cover surface water flooding.
Sourced from DfE's Get Information about Schools, joined to Ofsted's own separate monthly inspection-outcomes data by URN. Filter by State, Grammar, Private/Independent, Faith or SEN/Special — a school can match more than one (a state-funded grammar school is both State and Grammar).
Ofsted's rating shows in whichever format that school's most recent inspection actually used — the older single-word grade (Outstanding/Good/Requires Improvement/Inadequate) or the newer report-card format introduced in November 2025 (several areas each graded separately, plus a Met/Not Met safeguarding check) — always labelled with its own system and date so the two aren't mistaken for directly comparable. Independent schools aren't covered by Ofsted's state-funded schools dataset at all, shown as such rather than as 'not yet inspected'.
Sourced from DfE's Get Information about Schools, joined to Ofsted's own separate monthly inspection-outcomes data by URN. Filter by State, Grammar, Private/Independent, Faith or SEN/Special — a school can match more than one (a state-funded grammar school is both State and Grammar).
Ofsted's rating shows in whichever format that school's most recent inspection actually used — the older single-word grade (Outstanding/Good/Requires Improvement/Inadequate) or the newer report-card format introduced in November 2025 (several areas each graded separately, plus a Met/Not Met safeguarding check) — always labelled with its own system and date so the two aren't mistaken for directly comparable. Independent schools aren't covered by Ofsted's state-funded schools dataset at all, shown as such rather than as 'not yet inspected'.
Sourced from DfE's Get Information about Schools, joined to Ofsted's own separate monthly inspection-outcomes data by URN. Filter by State, Grammar, Private/Independent, Faith or SEN/Special — a school can match more than one (a state-funded grammar school is both State and Grammar).
Ofsted's rating shows in whichever format that school's most recent inspection actually used — the older single-word grade (Outstanding/Good/Requires Improvement/Inadequate) or the newer report-card format introduced in November 2025 (several areas each graded separately, plus a Met/Not Met safeguarding check) — always labelled with its own system and date so the two aren't mistaken for directly comparable. Independent schools aren't covered by Ofsted's state-funded schools dataset at all, shown as such rather than as 'not yet inspected'.
Sourced from DfE's Get Information about Schools, joined to Ofsted's own separate monthly inspection-outcomes data by URN. Filter by State, Grammar, Private/Independent, Faith or SEN/Special — a school can match more than one (a state-funded grammar school is both State and Grammar).
Ofsted's rating shows in whichever format that school's most recent inspection actually used — the older single-word grade (Outstanding/Good/Requires Improvement/Inadequate) or the newer report-card format introduced in November 2025 (several areas each graded separately, plus a Met/Not Met safeguarding check) — always labelled with its own system and date so the two aren't mistaken for directly comparable. Independent schools aren't covered by Ofsted's state-funded schools dataset at all, shown as such rather than as 'not yet inspected'.
Sourced from DfE's Get Information about Schools, joined to Ofsted's own separate monthly inspection-outcomes data by URN. Filter by State, Grammar, Private/Independent, Faith or SEN/Special — a school can match more than one (a state-funded grammar school is both State and Grammar).
Ofsted's rating shows in whichever format that school's most recent inspection actually used — the older single-word grade (Outstanding/Good/Requires Improvement/Inadequate) or the newer report-card format introduced in November 2025 (several areas each graded separately, plus a Met/Not Met safeguarding check) — always labelled with its own system and date so the two aren't mistaken for directly comparable. Independent schools aren't covered by Ofsted's state-funded schools dataset at all, shown as such rather than as 'not yet inspected'.
Sourced from the NHS's own GP practice list (ODS), joined to the Care Quality Commission's monthly ratings directory. Markers are colour-coded by CQC rating — Outstanding, Good, Requires improvement, Inadequate, or Not Rated.
A surgery that shares its registered address with another service (e.g. an out-of-hours GP service at the same site) can show as 'Not Rated' rather than getting its own individual score — shown here plainly with a short explanation rather than hidden, since that's a real limitation of the source data, not an error.
Sourced from OpenStreetMap via the Overpass API (amenity=hospital), refreshed periodically alongside every other POI layer in this project.
Useful for judging how close you'd be to emergency care and major medical facilities, which matters more the further out from central London you look.
Sourced from OpenStreetMap via the Overpass API, tagged and filterable by religion (Christian, Muslim, Jewish).
Useful for anyone for whom proximity to their place of worship and faith community is a genuine factor in where they choose to live.
Sourced from OpenStreetMap via the Overpass API, tagged and filterable by religion (Christian, Muslim, Jewish).
Useful for anyone for whom proximity to their place of worship and faith community is a genuine factor in where they choose to live.
Sourced from OpenStreetMap via the Overpass API, tagged and filterable by religion (Christian, Muslim, Jewish).
Useful for anyone for whom proximity to their place of worship and faith community is a genuine factor in where they choose to live.
Sourced from OpenStreetMap via the Overpass API, grouped into Premium, Medium and Budget tiers by brand.
Useful for matching an area to your actual shopping habits and budget, rather than just 'is there a supermarket nearby.'
Sourced from OpenStreetMap via the Overpass API, grouped into Premium, Medium and Budget tiers by brand.
Useful for matching an area to your actual shopping habits and budget, rather than just 'is there a supermarket nearby.'
Sourced from OpenStreetMap via the Overpass API (shop=mall), represented by one centroid per mapped mall.
Useful for locating larger concentrations of shops and services rather than individual high-street stores.
Sourced from OpenStreetMap via the Overpass API (amenity=pub). Markers are clustered at wider zooms so the dense central-London pattern remains usable.
Useful for seeing whether an area has everyday social venues within walking distance; OpenStreetMap coverage and opening status can vary.
Sourced from OpenStreetMap via the Overpass API (amenity=cafe). This is one of the app's densest point layers, so markers are clustered until you zoom in.
Useful for comparing day-to-day neighbourhood convenience, while remembering that independent cafés change frequently.
Sourced from OpenStreetMap via the Overpass API (leisure=fitness_centre), with clustered markers at wider zooms.
Useful for checking access to dedicated fitness centres; small studios and facilities inside other venues may be mapped inconsistently.
OpenStreetMap physical facilities tagged sport=tennis within Greater London; private/no-access features are excluded.
Missing access tags mean access is unknown, not public. Check the operator before travelling.
OpenStreetMap physical facilities tagged sport=soccer within Greater London; private/no-access features are excluded.
Missing access tags mean access is unknown, not public. Check the operator before travelling.
OpenStreetMap clubs and facilities tagged sport=rowing or club=rowing within Greater London.
A mapped club does not by itself guarantee public membership or current access; check with the operator.
Sourced from OpenStreetMap two ways: named lido facilities (tagged as a sports centre or swimming area whose name includes “lido”) and genuinely public outdoor swimming-pool areas. Private, members-only, kids'/paddling and indoor pools are excluded, and an unnamed outdoor pool is only kept when its tags show it is a real public facility (an entry fee, a named operator, or a 20 m-plus pool).
OpenStreetMap has no single “lido” tag, so this is a small, hand-checkable list of the ones that are clearly identifiable — not a complete register. An outdoor pool that OSM tags as neither of the above (for example Hampton Pool) will not appear.
Where OpenStreetMap records them, the popup shows the pool's website, opening hours and phone number.
Sourced from OpenStreetMap via the Overpass API, using full polygon outlines (not just a central point) so parks, commons and playing fields render as their real shape rather than a dot.
Useful for judging genuine walkable access to outdoor space, not just proximity to a named park's entrance.
Sourced from OpenStreetMap via the Overpass API, using full polygon outlines (not just a central point) so parks, commons and playing fields render as their real shape rather than a dot.
Useful for judging genuine walkable access to outdoor space, not just proximity to a named park's entrance.
Sourced from OpenStreetMap via the Overpass API, using full polygon outlines (not just a central point) so parks, commons and playing fields render as their real shape rather than a dot.
Useful for judging genuine walkable access to outdoor space, not just proximity to a named park's entrance.
ONS Mid-2024 population estimate at 2021 LSOA level, shown as people per km².
This describes population concentration across an area, not housing density or crowding at a specific address.
MHCLG English Indices of Deprivation 2025, at 2021 LSOA level. Decile 1 is the most deprived 10% of neighbourhoods in England, decile 10 the least deprived — a single national ranking, not London re-ranked on its own.
IMD measures relative deprivation across income, employment, education, health, crime, housing and living-environment domains. It describes the area, not every individual living in it.
Census 2021 (TS054), at 2021 LSOA level: the share of households renting from a council/local authority or another social landlord, out of all households.
This measures household tenure, not the physical condition, ownership status or quality of any individual home.
Modelled by Defra for the 2022 strategic airport-noise mapping round, using the Heathrow and London City LAeq,16h coverages.
Useful because aircraft noise is a real and persistent quality-of-life factor under the main approach and departure paths, but these are neighbourhood-scale modelled contours rather than a measurement at an individual home.
Sourced from the London Datastore's 'Noise Pollution in London' dataset, based on DEFRA/DfT strategic noise mapping.
Useful for spotting areas with high ambient road or rail noise that a map or a single visit wouldn't reveal, particularly near major roads or rail junctions.
Sourced from the London Datastore's 'Noise Pollution in London' dataset, based on DEFRA/DfT strategic noise mapping.
Useful for spotting areas with high ambient road or rail noise that a map or a single visit wouldn't reveal, particularly near major roads or rail junctions.
Defra UK-AIR's PCM modelled annual-mean background nitrogen dioxide concentration, shown on its native 1 km grid and clipped to Greater London.
This first pollution layer shows broad background conditions, not street-level exposure, roadside peaks or regulatory compliance. A second pollutant can follow once this ships cleanly.
Sourced from the ONS Open Geography Portal, showing the outline of all 33 London boroughs. Each borough also carries its own Council Tax Band A-H figures, sourced from gov.uk's official statistics — click a borough on the map to see its own table.
Useful for seeing at a glance which local authority governs an area, and for comparing council tax directly between neighbouring boroughs, which can vary substantially even a short distance apart.
Sourced from Transport for London, showing the current Ultra Low Emission Zone boundary (expanded in August 2023 to cover the whole of Greater London).
Useful because vehicles that don't meet the zone's emissions standards are charged a daily fee to drive within it — a real running cost worth knowing about before choosing where to live if you drive an older or less efficient vehicle. Since the 2023 expansion, the zone covers almost all of Greater London, so this boundary mainly matters at the edges of the area shown on this map.
Sourced from HM Land Registry Price Paid Data, showing individual residential sales from the last few years within whichever area of the map you're currently viewing — price, sale date, property type and tenure for each one.
Useful for judging real, recent asking-vs-achieved prices for an area directly, rather than relying on an estate agent's own listing price or a borough-wide average that can hide a lot of street-by-street variation.
Contains HM Land Registry data © Crown copyright and database right 2026. This data is licensed under the Open Government Licence v3.0.
Start with your commute, then tell us what matters to you, and we'll show which parts of London match — then open an Address Report for a promising area.
Enter where you work and how long you're willing to travel by public transport. Only areas inside that travel time are shown — everything on the map will be somewhere you could actually commute from.
Only areas within this commute are shown on the map.
No specific workplace?
Closeness to a train, Tube, DLR or Elizabeth line station. This uses the app's broad rail category, which also covers London Overground and trams.
Pick what you can spend. Renting: choose a bedroom category and a monthly ceiling. Buying: choose a price ceiling. Areas whose typical figure is above your ceiling stay on the map and keep their match score — they're flagged in dark red so you can see what you'd be stretching for.
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Areas over your budget still appear on the map, clearly flagged — they aren't hidden.
Closeness to a state primary or secondary school rated Good or Outstanding at its last full Ofsted inspection.
Independent schools, and schools on Ofsted's newer report-card system or not yet inspected, can't be graded this way and don't count towards this.
Closeness to a park, nature reserve or recreation ground of at least 0.2 hectares.
Away from the loudest road, rail and aircraft noise. Uses the annual-average Lden road and rail contours and the Defra daytime (LAeq,16h) aircraft contours.
Fewer reported crimes. Based on the number of crimes reported per km² over the last 12 months, compared with the rest of London. This counts reported incidents by area, so busy commercial and nightlife districts rank high regardless of what living there is like.
Reflects crime reported to and recorded by police, and doesn't separate residential from commercial incidents — it isn't a direct measure of how safe an area is.
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In Advanced Search, open Layers to explore hospitals, schools, crime data, green spaces, transport, and more — check several at once to compare an area at a glance.
Use the full interactive map and additional layers to investigate this location.