How a town gets its grade — and where the data runs out
TerraNova grades 51,317 municipalities across 4 countries from A++ to G, entirely from published official data. This page names every input, every source, and every place where a number is coarser than it looks.
Scoring model 2026.12-momentum-v1, last computed 2026-08-02.
The tables below are generated from the live model and the live database, not written by hand, so they cannot drift out of step with the grades.
The one rule How a grade is built Whose priorities Every indicator How complete each grade is What we don't measure
The one rule: nothing rather than a plausible guess
The easiest way to build this site would be to fill every gap with something reasonable. A province's average price where a town's is unpublished. A national climate figure where the local one is missing. A zero where nothing was found. Every one of those produces a page that looks complete and quietly misleads, and a wrong number is worse than a blank one because you cannot tell it is wrong.
So, three commitments, which the rest of this page exists to let you verify:
- A missing indicator scores nothing. It does not become a zero and it does not become an average. The pillar is recomputed over whatever inputs genuinely exist, and if none do, the pillar reads as “no data” instead of a middling score.
- A proxy is labelled a proxy. Where the only published figure describes a province or a district rather than the town, we use it — a coarse number honestly labelled is still useful — and we say so, on the town's page and in the table below.
- Absence is stated, not hidden. Where we have no data, the section is simply not there. A town page with fewer panels than another is telling you something true.
This is not an abstract principle. The bugs that hurt most in this project's history were all the same shape: a dead data source rendering a confident-looking score. An inland town once showed a tsunami risk bar. Half of France once carried an “attractiveness” score computed from map data that had never been imported for France — it read as a perfectly average result, which is exactly why it took so long to notice. Both are gone, and the rule above is what stops the next one.
How a grade is built
Four steps. Each indicator is normalised to 0–100. Indicators roll up into five pillars, each indicator weighted inside its pillar. The pillars combine into one 0–100 composite. The composite maps to a letter.
Normalisation is a percentile rank within the same country for most things: a price or a rental yield is scored against the rest of that country, because “expensive” only means anything relative to somewhere.
Two kinds of input are scored on an absolute scale instead, because ranking them would destroy the very thing they measure. Natural hazards carry a 30-year probability: ranking a hazard against a country where most towns have none compresses a real tenfold difference in exposure into nearly the same score. The population trend carries a percent per year: a town losing 1.2% of its people a year is doing the same thing in Galicia and in the Auvergne, and a rank would have said only “about average for its country” about both.
Pillar weights
The default (“balanced”) weighting. This is what every grade on the site means unless you changed the sliders yourself.
| Pillar | What it answers | Weight |
|---|---|---|
| Climate & risk | Is the weather actually pleasant, and what could go wrong? | 30% |
| Vitality | Is this a living town with a future, or one that is emptying out? | 25% |
| Services & access | Can you live here without a car for everything, and get home from an airport? | 20% |
| Value | How expensive is it, per square metre, compared with the rest of the country? | 10% |
| Market | What have prices, sales and rents been doing? | 15% |
The letter
Fixed thresholds on the 0–100 composite, so a grade means the same thing in every country and in every report.
| Grade | Composite from |
|---|---|
| A++ | 92 |
| A+ | 80 |
| A | 68 |
| B | 56 |
| C | 44 |
| D | 32 |
| E | 22 |
| F | 12 |
| G | 0 |
A pillar with no data at all is treated as neutral (50) when the composite is formed, so that weights stay comparable between towns — and the town's page reports how many pillars that applied to, so a grade built on three pillars is never presented as if it were built on five.
Whose priorities? Three weightings, and yours
A retiree and a landlord are not looking for the same town, so one fixed ranking would be wrong for both. The pillar weights are adjustable, and the site ships three presets. Changing them re-weights the pillars — it never changes the underlying measurements, and it cannot flip an indicator's direction.
| Profile | Climate & risk | Vitality | Services & access | Value | Market |
|---|---|---|---|---|---|
| Balanced The default, and what every grade on the site means unless you changed it. |
30% | 25% | 20% | 10% | 15% |
| Lifestyle For living there: climate and services matter more, market returns less. |
35% | 15% | 25% | 15% | 10% |
| Investment For letting or reselling: market and value dominate, climate comfort matters least. |
15% | 20% | 15% | 20% | 30% |
Every indicator, and where it comes from
Grouped by pillar. “Weight in pillar” is the indicator's share of that pillar, renormalised over whichever inputs a given town actually has. “Coverage” is the share of that country's municipalities for which the figure exists at all — the honest picture, measured from the database when this page was built.
Climate & risk
30% of the gradeIs the weather actually pleasant, and what could go wrong?
Everyday comfort
How pleasant the year actually is — sunshine and mild temperatures, penalising both cold winters and punishing summer heat — from decades of reanalysis data at the town's own location.
| Country | Source | Vintage | Figure describes | Coverage |
|---|---|---|---|---|
| ES | Copernicus Climate Change Service (C3S) — ERA5 | 2026 | the town itself | 100% |
| FR | Copernicus Climate Change Service (C3S) — ERA5 | 2026 | the town itself | 100% |
| IT | Copernicus Climate Change Service (C3S) — ERA5 | 2026 | the town itself | 100% |
| PT | Copernicus Climate Change Service (C3S) — ERA5 | 2026 | the town itself | 100% |
This is half the default climate pillar, and it is the biggest hole in the dataset: it has only been computed for a fraction of France and Italy so far. The coverage table below says exactly how much.
Beach season
A long usable warm season plus a mild winter — the Mediterranean second-home question rather than the year-round-living one.
| Country | Source | Vintage | Figure describes | Coverage |
|---|---|---|---|---|
| ES | Copernicus Climate Change Service (C3S) — ERA5 | 2026 | the town itself | 100% |
| FR | Copernicus Climate Change Service (C3S) — ERA5 | 2026 | the town itself | 100% |
| IT | Copernicus Climate Change Service (C3S) — ERA5 | 2026 | the town itself | 100% |
| PT | Copernicus Climate Change Service (C3S) — ERA5 | 2026 | the town itself | 100% |
Deliberately not the inverse of everyday comfort: a place can score well on both. It is used only by the warm/coastal profile and never enters the default grade. Coverage is currently almost nil, so that profile falls back to the standard climate pillar.
Wildfire exposure
The chance of a damaging wildfire near the town within the next 30 years, built from satellite fire detections around it.
| Country | Source | Vintage | Figure describes | Coverage |
|---|---|---|---|---|
| ES | NASA FIRMS — VIIRS active fire (fires near) | 2026 | the town itself | 100% |
| FR | NASA FIRMS — VIIRS active fire (fires near) | 2026 | the town itself | 100% |
| IT | NASA FIRMS — VIIRS active fire (fires near) | 2026 | the town itself | 100% |
| PT | NASA FIRMS — VIIRS active fire (fires near) | 2026 | the town itself | 94% |
An absolute probability, not a ranking. That matters: ranking hazards against a country where most towns have none would flatten a real tenfold difference into nearly the same score.
Earthquake exposure
The chance of a damaging earthquake within 30 years, from the recorded earthquake catalogue around the town.
| Country | Source | Vintage | Figure describes | Coverage |
|---|---|---|---|---|
| ES | USGS FDSN — earthquake catalogue | 2026 | the town itself | 100% |
| FR | USGS FDSN — earthquake catalogue | 2026 | the town itself | 100% |
| IT | USGS FDSN — earthquake catalogue | 2026 | the town itself | 100% |
| PT | USGS FDSN — earthquake catalogue | 2026 | the town itself | 94% |
Also an absolute 30-year probability. Within the climate pillar, the worst hazard governs rather than the average — averaging lets an absent hazard mask a near-certain one.
Tsunami exposure
Recorded tsunami exposure near the town, on the same absolute 30-year scale as the other hazards.
| Country | Source | Vintage | Figure describes | Coverage |
|---|---|---|---|---|
| ES | NOAA NCEI/WDS — Global Historical Tsunami Database | 2026 | the town itself | 100% |
| FR | NOAA NCEI/WDS — Global Historical Tsunami Database | 2026 | the town itself | 100% |
| IT | NOAA NCEI/WDS — Global Historical Tsunami Database | 2026 | the town itself | 100% |
| PT | NOAA NCEI/WDS — Global Historical Tsunami Database | 2026 | the town itself | 94% |
Computed and shown on the town's page, but weighted zero in the default grade — re-weighting it would move every coastal ranking, and that decision has not been taken. It is a real number when you look at it, not a placeholder.
Vitality
25% of the gradeIs this a living town with a future, or one that is emptying out?
Population trend
How fast the town is gaining or losing registered residents, as a compound annual rate — the strongest single signal here, and the one that catches rural depopulation.
| Country | Source | Vintage | Figure describes | Coverage |
|---|---|---|---|---|
| ES | Annualised from the official population register | 2025 | the town itself | 93% |
| FR | Annualised from the official population register | 2020 | the town itself | 97% |
| IT | Annualised from the official population register | 2025 | the town itself | 99% |
| PT | Annualised from the official population register | 2023 | the town itself | 99% |
Unlike almost everything else on this page, this is an absolute rate rather than a ranking against its own country: −1.2%/yr means the same thing in Galicia and in the Auvergne. It measures the register, not the people, and a municipal boundary change reads as a collapse or a surge — which is why the ranked lists refuse to publish anything beyond ±5%/yr. Each town's own page states the years its figure was measured over, because the four statistics offices publish different windows.
Density
People per square kilometre.
| Country | Source | Vintage | Figure describes | Coverage |
|---|---|---|---|---|
| ES | Derived from population ÷ surface area | 2025 | the town itself | 99% |
| FR | Derived from population ÷ surface area | 2020 | the town itself | 100% |
| IT | Derived from population ÷ surface area | 2025 | the town itself | 100% |
| PT | Derived from population ÷ surface area | 2023 | the town itself | 99% |
Derived from population and surface area rather than published as such. Municipal boundaries vary enormously in size between these four countries, so this reads as a rough town-versus-countryside signal, not a precise one.
Things to do
Density of places worth going to — food, culture, leisure, tourism, nature — per square kilometre, counted from OpenStreetMap.
| Country | Source | Vintage | Figure describes | Coverage |
|---|---|---|---|---|
| ES | OpenStreetMap — points of interest | 2026 | the town itself | 100% |
| FR | OpenStreetMap — points of interest | 2026 | the town itself | 100% |
| IT | OpenStreetMap — points of interest | 2026 | the town itself | 100% |
| PT | OpenStreetMap — points of interest | 2026 | the town itself | 100% |
Only scored where the country's map data has actually been imported. Where it has not, this contributes nothing to the grade rather than counting as zero: a town is not empty just because we have not looked.
Foreign residents
The share of residents who are foreign nationals — a proxy for how easy the landing is for an incoming foreign buyer.
| Country | Source | Vintage | Figure describes | Coverage |
|---|---|---|---|---|
| ES | INE — Padrón (población por nacionalidad, tabla 33571) | 2026 | the town itself | 99% |
| FR | INSEE — recensement, population par nationalité (étrangers) | 2021 | the town itself | 100% |
| IT | ISTAT — Popolazione straniera residente (STRASA) ÷ popolazione residente (POSAS) | 2025 | the town itself | 100% |
| PT | INE Portugal — população estrangeira com estatuto legal de residente (0013220) ÷ população residente (0008273) | 2023 | the town itself | 99% |
Not measured identically everywhere: Spain, France and Italy count residents by nationality, while Portugal counts holders of a residence permit, which is a narrower group. Compare within a country more confidently than across them.
Services & access
20% of the gradeCan you live here without a car for everything, and get home from an airport?
Air connectivity
How reachable international airports are, weighted by distance, so a town near one big hub and a town near three small ones score differently.
| Country | Source | Vintage | Figure describes | Coverage |
|---|---|---|---|---|
| ES | TerraNova — air connectivity (curated airports) | 2026 | the town itself | 100% |
| FR | TerraNova — air connectivity (curated airports) | 2026 | the town itself | 100% |
| IT | TerraNova — air connectivity (curated airports) | 2026 | the town itself | 100% |
| PT | TerraNova — air connectivity (curated airports) | 2026 | the town itself | 100% |
Everyday essentials
How many of pharmacy, supermarket, school and doctor exist inside the town's own boundary, out of four.
| Country | Source | Vintage | Figure describes | Coverage |
|---|---|---|---|---|
| ES | OpenStreetMap — everyday essential services | 2026 | the town itself | 100% |
| FR | OpenStreetMap — everyday essential services | 2026 | the town itself | 100% |
| IT | OpenStreetMap — everyday essential services | 2026 | the town itself | 100% |
| PT | OpenStreetMap — everyday essential services | 2026 | the town itself | 100% |
Containment, not distance to the nearest one. Distance from a municipal centre is meaningless when the centre is an arbitrary point in a large rural boundary; "is there a pharmacy in this town at all" is a question with an answer.
Value
10% of the gradeHow expensive is it, per square metre, compared with the rest of the country?
Price per m²
The published price per square metre. Cheaper scores better — this pillar is affordability, not desirability.
| Country | Source | Vintage | Figure describes | Coverage |
|---|---|---|---|---|
| ES | MITMA — valor tasado de la vivienda libre (€/m²) | 2026 | 3% the town itself, rest a wider-area average | 99% |
| FR | DVF — Demandes de valeurs foncières (Etalab) | 2020 | the town itself | 95% |
| IT | Agenzia Entrate — OMI, Quotazioni Immobiliari | 2018 | wider-area average (proxy) | 92% |
| PT | INE Portugal — valor mediano de venda €/m² (proxy distrital, interim) | 2025 | wider-area average (proxy) | 100% |
The single coarsest number on the site. For most of Spain and all of Portugal the only published figure is a provincial or district one, which is labelled as a proxy wherever it appears and is why no report compares your asking price against a local median in those countries.
Market
15% of the gradeWhat have prices, sales and rents been doing?
Price appreciation
How fast prices have risen, annualised, over roughly the last five years.
| Country | Source | Vintage | Figure describes | Coverage |
|---|---|---|---|---|
| ES | INE — Índice de Precios de Vivienda (IPV, CAGR 5 ans par communauté autonome) | 2025–2026 | 3% the town itself, rest a wider-area average | 100% |
| FR | DVF — Demandes de valeurs foncières (Etalab) | 2023 | the town itself | 92% |
| PT | INE Portugal — mercado imobiliário (proxy distrital, interim) | 2025 | wider-area average (proxy) | 100% |
Past movement, not a forecast. The window is not the same everywhere, so the town's own page states the years the figure was measured over rather than leaving "5y" in a label to imply it.
Market liquidity
Sales per 1,000 dwellings — how readily property here actually changes hands, which is what determines whether you can sell again.
| Country | Source | Vintage | Figure describes | Coverage |
|---|---|---|---|---|
| ES | MITMA — transacciones inmobiliarias por municipios ÷ viviendas familiares (INE, Censo 2021) | 2025 | the town itself | 98% |
| FR | DVF — Demandes de valeurs foncières (Etalab) | 2023 | the town itself | 93% |
| IT | Agenzia delle Entrate — OMI, NTN compravendite residenziali (provincia, capoluogo/non capoluogo) ÷ abitazioni ISTAT | 2024 | 1% the town itself, rest a wider-area average | 93% |
| PT | INE Portugal — mercado imobiliário (proxy distrital, interim) | 2025 | wider-area average (proxy) | 100% |
Gross rental yield
A year of rent as a percentage of the purchase price.
| Country | Source | Vintage | Figure describes | Coverage |
|---|---|---|---|---|
| ES | SERPAVI (MIVAU) — precio de referencia del alquiler ÷ precio de compra (rendimiento bruto estimado) | 2024 | 41% the town itself, rest a wider-area average | 99% |
| FR | ANIL "Carte des loyers" (loyers d’annonce) ÷ DVF (prix) — rendement locatif brut | 2025 | the town itself | 94% |
| IT | Agenzia Entrate — OMI, Quotazioni Immobiliari | 2018 | wider-area average (proxy) | 87% |
| PT | INE Portugal — mercado imobiliário (proxy distrital, interim) | 2025 | wider-area average (proxy) | 100% |
Gross, not net: no tax, no management, no vacancy, no maintenance. And it is one published figure divided by another, so it inherits the coarseness of both — where either side is a zone or province average, the page says so.
Tourism intensity
Tourist bed places per 1,000 inhabitants — short-let demand, and equally a warning about summer crowding.
| Country | Source | Vintage | Figure describes | Coverage |
|---|---|---|---|---|
| ES | INE — Viviendas turísticas en España (estadística experimental, municipal) | 2026 | the town itself | 99% |
| FR | INSEE — capacité des communes en hébergement touristique (+ résidences secondaires, RP) | 2026 | the town itself | 100% |
| IT | ISTAT — Capacità degli esercizi ricettivi (posti letto) ÷ popolazione residente (POSAS) | 2025 | the town itself | 94% |
| PT | INE Portugal — mercado imobiliário (proxy distrital, interim) | 2025 | 6% the town itself, rest a wider-area average | 100% |
Counted differently in each country: registered tourist dwellings in Spain, measured bed places in Italy, and an equivalence that includes second homes in France, without which French resorts read as empty. Read it within a country.
Each source is linked to the body that publishes it, and the data remains theirs under their own licences — see the terms. Every town's own page repeats the source and date for each figure shown on it, so you can check a specific number rather than trusting this table.
How complete is each grade, really?
The uncomfortable table. For each country, the share of the pillar's intended indicator weight that has a real measurement behind it. 100% means every input the model wants exists; 50% means the pillar was computed from half of what it is supposed to weigh, and the letter is correspondingly less informative.
| Country | Climate & risk | Vitality | Services & access | Value | Market | Whole grade | In the dataset |
|---|---|---|---|---|---|---|---|
| Spain | 100% | 97% | 100% | 99% | 99% | 99% | 8,217 |
| France | 100% | 99% | 100% | 95% | 94% | 98% | 34,888 |
| Italy | 100% | 100% | 100% | 92% | 64% | 94% | 7,904 |
| Portugal | 97% | 99% | 100% | 100% | 100% | 99% | 308 |
Read this before comparing a town in one country with a town in another. Right now Spain is the best-evidenced country in the dataset (99%) and Italy the least (94%), so the same letter is a stronger statement in one than the other. Where you see a figure below 50%, the pillar is running on a minority of its intended evidence and should be read as a hint rather than a finding.
This is deliberately a harsher measure than the completeness percentage shown next to a grade. That one counts how many of the five pillars have any data; this one counts how much of the evidence each pillar wanted actually arrived. A pillar surviving on a third of its intended weight counts as fully present in the first measure and as a third in this one.
What we measure but never score
Some figures are shown on a town's page and deliberately kept out of the grade, because scoring them would produce a ranking that is not valid. Showing them is useful; ranking on them is not.
| Shown, not scored | Why |
|---|---|
| Population | A raw headcount is context, not quality — a big town is not a better town. It feeds density and the population trend, both of which are scored. |
| Published population change | The raw percentage each statistics office publishes, shown on a town's page with the years it covers. Not scored directly: the four offices publish windows of 10, 5, 6 and 10 years under this one label, so the raw percentages are not the same quantity. It is annualised first, and the annual rate is what enters the grade. |
| Recorded burglary (France) | Residential burglary per 1,000 dwellings. Not scored: crime statistics are published for large municipalities and withheld for small ones, so scoring them would systematically penalise exactly the small towns this product is for — and a withheld figure is not a zero. |
| Recorded crime (Portugal) | All recorded crime per 1,000 inhabitants. Kept separate from the French figure on purpose: different offences, different denominator, different country. Collapsing them into one "safety" score would invite a comparison that is not valid. |
What is not in a grade at all
The part you cannot infer from what is on the page — so it is written down.
| Not measured | Why not |
|---|---|
| Flood exposure | We have no usable municipal flood dataset covering these four countries. Flood risk is therefore absent from the climate pillar entirely rather than approximated from something adjacent. It would refine that pillar, not unlock it — the pillar already scores on comfort and two other hazards. |
| Air and water quality | Published at station level, not municipal level, across all four countries. Interpolating a station reading to a town would produce a number that looks municipal and is not. |
| Schools, hospitals and transport quality | We count whether a school or a doctor is present, not how good it is. Comparable quality measures do not exist across four countries, and inventing a composite from what does exist would be exactly the plausible guess this site refuses to make. |
| Anything about a specific property | Every grade describes a municipality. No building, no street, no view, no state of repair, no legal status. Two houses 200 metres apart get the same grade and can be worth very different money. |
Grades move. That is the model improving, not the town changing
Official sources are revised and republished, new indicators land, and the scoring model changes when the data
gets better. All three can move a town's letter without anything about the town having changed. Every score
carries the model version that produced it (currently 2026.12-momentum-v1) and the date
it was computed, and every paid report states both, so a document you downloaded last month can be read as the
snapshot it is.
None of this is advice. It is a way to narrow tens of thousands of municipalities down to a shortlist worth visiting — see the terms for what that does and does not mean.
If a number looks wrong, tell us. Every town page carries a “something wrong on this page?” form. Corrections from residents and town halls are the one input we cannot get from an official dataset, and they are welcome.
Browse the data: the interactive map, the guides, or any town's page.