At SpyShop Europe we have been close to the surveillance and counter-surveillance industries for nearly two decades. In that time we have watched governments install hundreds of millions of cameras across European capitals, transit hubs, and public squares. The build-out was sold to citizens as a fair trade: some loss of privacy in exchange for a measurable gain in safety. For years the bargain was widely accepted, and the cameras kept coming.
But did the promised safety actually arrive? And has public trust in how the state handles its citizens' data kept pace with the speed at which the cameras have been collecting it? Those are the two questions this dataset sets out to answer, jurisdiction by jurisdiction.
To carry out the study we tracked three indicators over the same reference window. For cameras we compared industry market estimates of national CCTV stock in 2015 against the most recent year available, sourced from Comparitech 2025, IHS Markit / Omdia, BSIA for the United Kingdom, and national security-industry associations elsewhere. For crime we used the most recent year of total police-recorded offences against the 2015 figure, drawn from national statistical offices or, for the European Union, from Eurostat. For trust we used the relative change in the proportion of citizens reporting that they are not concerned about how the state handles their personal data, drawn from Pew Research for the United States and Anglosphere, Special Eurobarometer 487a then 551 across the EU, and the Edelman Trust Barometer for the rest of the surveyed world.
Police-recording quality varies across countries, and where the change in recording practice itself accounts for a meaningful share of the apparent crime trend (as it does for England and Wales, where HMICFRS assessed compliance rising from 80.5% to 94.8% across the window) we flag the caveat directly. For jurisdictions whose crime and trust series are produced by state-controlled bodies without independent statistical oversight (Russia, China, much of the Gulf, and parts of Sub-Saharan Africa), we publish the camera figures but mark the crime and trust cells as not independently verifiable. Below you can compare any two cities side by side or sort the full 100-city dataset by any column.
A short guide to what the data supports, what it does not, and how to attribute every figure in this report.
“The tables below document government-operated CCTV camera density in 100 cities and direction-of-travel indicators for recorded crime and public trust over the reference window (2015 to most recent available, typically 2024 or 2024/25). All figures cited inline are the values published by the original source agency. Direction codes and scope badges follow the taxonomy defined in § 3.5 of the methodology.”
London versus Tokyo. Stockholm versus Singapore. Berlin versus Beijing.
The dataset reads differently when two jurisdictions sit next to each other.
All 100 cities are available in the pickers. The panel uses the same diverging heatmap as the full table below, so the visual contrast between any two rows reads identically across the two views.
Ten columns. All sortable. Heat-mapped.
Every value traces to a
named public source, every direction-of-travel is calculated from endpoint figures
you can verify, and every cell is built to be quoted by row.
Click any header to sort. All three Since-2015 deltas are % change vs 2015: cameras from industry market estimates (Comparitech, IHS Markit, BSIA, national associations); crime from national statistical offices or Eurostat; trust from Pew (US, Anglosphere), Special Eurobarometer 487a then 551 (EU), Edelman Trust Barometer (rest of world). Background colour encodes both direction and magnitude on a diverging scale, comparable across all three columns.
| Since 2015 | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| # | City | Country | Region | Cameras / 1K People | Cameras / km² | Cams | Crime | Trust | Privacy Law |
How the Since-2015 deltas are computed.
Cameras.
National stock estimate 2025 divided by national stock estimate 2015, less 1. Sourced from industry market reports (IHS Markit / Omdia, Comparitech 2025, BSIA for the UK, national security-industry associations elsewhere). Override with city-level estimate where one exists: London, Stockholm, Paris, Moscow, the four Chinese megacities, Dubai, Riyadh, Hyderabad, Seoul.
Crime.
Most recent year of total police-recorded offences divided by the 2015 figure, less 1. Sourced from national statistical office or Eurostat crim_off_cat. City overrides where the city-series is firm: London (MOPAC), Berlin (PKS), Stockholm (BRÅ), Paris (SSMSI), Tokyo (NPA), Singapore (SPF), Washington DC (MPD), New York (NYPD), LA, Chicago.
Trust.
Relative change in the proportion of citizens not reporting concern about state data handling. Pew Research for US / UK / Canada / Australia / NZ. Special Eurobarometer 487a (2019) vs 551 (2024) / 553 (2025) for EU. Edelman Trust Barometer for the rest of the surveyed world.
Cells showing n/a are jurisdictions with no comparable time series, overwhelmingly state-controlled crime statistics (Russia, China, much of the Gulf and Sub-Saharan Africa) where the published figures cannot be independently validated.
Confidence.
Country-level estimates carry ±20% uncertainty; city overrides are tighter (typically ±5 to 10%). Replace the camsD / crimeD / trustD fields in the cities array with project-dataset values to tighten any row.
Reading the cells.
Background colour encodes both direction and magnitude on a diverging scale: amber for positive change (deepening at +50%, +150%, +300%), red for negative (deepening at -15%, -30%), neutral for n/a. The same scale applies across all three Since-2015 columns so cells stay directly comparable.
Documented cases of facial recognition misidentification, biometric overreach, and GDPR enforcement actions, drawn from court records and named press reporting.
Each record in the 100-city index documents the following ten variables.
Variable names match the JSON fields used by the JavaScript renderer.
| Variable | Unit / type | Definition | Source class |
|---|---|---|---|
| city, country, region | text | Standard place identifiers. Region grouping follows UN M.49. | n/a |
| cams1k | cameras / 1,000 residents | Government-operated or government-accessible CCTV cameras per 1,000 residents, as defined by the source studies (Comparitech / NeoMam / Surfshark methodology). Excludes purely private commercial cameras and household systems. | Industry / NGO |
| camskm | cameras / km² | Same camera count divided by city land area. Useful when comparing dense cities (e.g. Seoul, Beijing) against sprawling ones (e.g. Sydney, Los Angeles). | Industry / NGO |
| camsD | % change vs 2015 | Percentage change in government-operated CCTV stock between 2015 and most recent available year (typically 2024 or 2024/25). Country-level estimate, with city overrides where firm city-level data exists. | Industry / NGO |
| crimeD | % change vs 2015 | Percentage change in total police-recorded offences over the same reference window. Null where no comparable time series exists (state-controlled jurisdictions). Selection rules in § 3.3. | National statistics |
| trustD | % change vs 2015 | Relative change in the proportion of citizens reporting they are not concerned about state data handling. Pew (US, Anglosphere), Special Eurobarometer 487a then 551 (EU), Edelman Trust Barometer (rest of world). Selection rules in § 3.4. | Survey houses |
| gdpr | text | Applicable national or sub-national privacy framework, as of 2026.Q1. | Regulatory |
Sections 3.1 through 3.8 below define every construction rule, indicator-selection convention, and acknowledged limitation in this dataset. Designed so a fact-checker can audit any cell on the page.
The 100 cities are inherited from the Comparitech / NeoMam global CCTV index (2025 update), which orders cities by government-operated camera density per 1,000 residents. We did not re-sample; the rank ordering is theirs. The frame favours cities for which credible enumeration is possible, which means it under-represents jurisdictions with no public CCTV statistics, parts of Central Asia, Sub-Saharan Africa, and the smaller Pacific states. Coverage by region: Asia 31, Europe 33, Americas 19, Middle East 9, Africa 11, Oceania 2.
Camera counts are sourced from Comparitech 2025 and IHS Markit / Omdia industry reports, cross-referenced with national security-industry associations (BSIA for the UK, SSAIB, ESS Industry Group for Germany).
Included: cameras operated by, or routinely accessible to, government authorities, typically municipal police, transit police, federal law-enforcement agencies, and integrated "Safe City" platforms with formal data-sharing agreements.
Excluded from the headline figure: residential doorbell cameras, private commercial CCTV with no police-access agreement, household security systems.
Chinese cities are reported using the source-study definition, which counts only formally classified state cameras. The actual penetration in Chinese cities is materially higher; including private and on-request-accessible cameras would push China's largest cities to the top of the index. We publish the lower, narrower figure because (a) it is the figure on which the source studies converge and (b) it preserves comparability with non-Chinese rows. A separate methodology note in the main report discusses the higher estimate.
For each country, the crime delta uses the highest-coverage publicly-released crime series available from the national statistical office or police:
crim_off_cat.Recording-rate caveat.
Police-recorded crime is affected by reporting rates and recording-practice changes. HMICFRS independently assessed UK police compliance with recording standards as rising from 80.5% in 2014 to 94.8% in recent reports; we cite this caveat in any single-jurisdiction analysis. Victim-survey series (CSEW, Eurostat ad-hoc modules) often tell a different and more favourable story for property crime; we treat the divergence between the two as a finding to surface, not an error to suppress.
The two backbone series for public concern about state data handling are:
Country breakdowns are available from both surveys where sample size permits; we use national readings where present, otherwise the EU or regional aggregate, badged reg. For non-democratic jurisdictions where state-controlled survey data lacks independent oversight, the cell is marked ? and no direction is published. Supplementary regional series used: Edelman Trust Barometer (28 markets, annual), Latinobarómetro (Latin America), Afrobarometer (selected African states).
Each delta cell carries a scope badge marking the geographic level at which the underlying series is available:
nat on the cameras axis, readers should not assume city-level precision.Dataset version 2026.1. The cities array, country defaults and city overrides are present in the source HTML of this report and can be extracted directly for verification. Re-runs against newer source releases are produced annually. Corrections to specific cells are welcome via [email protected] and are reflected in versioned changelogs published alongside subsequent releases.
Every figure traces to one of the publishers below.
URLs link to the primary release. Replace any figure with project-dataset
values and the citation chain is already in place.
crim_off_cat. ec.europa.eu/eurostat/web/crime