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    The AINT.app urban source desk

    Read the urban fabric.
    Greenness. Roads. Scale.

    How much of a source footprint’s population is modelled as exposed to high greenness? How much mapped road fits inside its area? Two different signals help describe urban form. They do not decide which city is best.

    Nominal 2025 · modelled exposure

    Vegetation exposure, not park access.

    The model estimates the share of population living in areas classified as having high greenness. Its method combines satellite vegetation data, built-up cells and projected population. A high percentage does not tell you whether a park is public, open or within walking distance.

    NDVI uses a three-year average, but the exact calendar window is not supplied. Thresholds vary by agro-ecological zone.

    2024 mapped roads · 2025 footprint

    Road intensity, not transport quality.

    Mapped road density expresses road length relative to source footprint area. We convert the publisher’s m/m² to km/km² by multiplying by 1,000. More mapped road is not automatically better: this does not establish walking conditions, public transport service, congestion or safety.

    Road source: Overture Maps, accessed by the publisher on 24 July 2024. Network completeness is not quantified.

    The footprint explorer

    Compare one quantity at a time.

    Download CSV

    Choose a quantity, then search destinations or filter a country. The default is alphabetical. Optional indicator ordering compares the same source epoch within that quantity; it does not create ordinal ranks, statistical significance or an overall livability score.

    250 of 250 destinations shown · 246 distinct source footprints in this view. Alphabetical order. Choosing another quantity resets the order to A–Z.

    High-greenness population exposure, Nominal 2025 model. Native 2025 morphological urban footprints; no overall city ranks.
    Destination / countryHigh-greenness exposure% · Nominal 2025 modelSource urban centreFootprint areakm² · 2025
    Abu DhabiUnited Arab Emirates0.5%Abu DhabiUC 325107
    AbujaNigeria0.2%AbujaUC 7471319
    AccraGhana0.6%AccraUC 31751,121
    Addis AbabaEthiopia1.7%Addis AbabaUC 5862465
    AdelaideAustralia3.5%AdelaideUC 1029493
    AhmedabadIndia0.1%AhmedabadUC 6143365
    AlicanteSpain0.3%AlicanteUC 448574
    AmmanJordan0.0%AmmanUC 992520
    AmsterdamNetherlands6.1%AmsterdamUC 1590308
    AnkaraTürkiye0.3%AnkaraUC 4921357
    AntwerpBelgium6.4%AntwerpUC 1069327
    AsunciónParaguay20.3%AsuncionUC 217383
    AthensGreece0.1%AthensUC 854412
    AtlantaUnited States25.9%AtlantaUC 7219292
    AucklandNew Zealand28.3%AucklandUC 1147638
    AustinUnited States64.2%AustinUC 5951628
    BaltimoreUnited States34.6%BaltimoreUC 7959449
    BangaloreIndia2.1%BengaluruUC 95581,008
    BangkokThailand5.4%BangkokUC 23152,697
    BarcelonaSpain1.1%BarcelonaUC 5071438
    BaselSwitzerland12.3%BaselUC 107368
    BeijingChina2.3%BeijingUC 87452,179
    BeirutLebanon1.2%BeirutUC 458199
    BelfastUnited Kingdom9.9%BelfastUC 235149
    BelgradeSerbia6.7%BelgradeUC 573191
    BergenNorway100.0%BergenUC 6650
    BerlinGermany32.0%BerlinUC 5483681
    BilbaoSpain2.3%BilbaoUC 3974106
    BirminghamUnited Kingdom10.2%BirminghamUC 3888685
    BogotáColombia2.2%BogotaUC 3881534
    BolognaItaly1.4%BolognaUC 3065114
    BordeauxFrance2.5%BordeauxUC 1285208
    BostonUnited States22.0%BostonUC 8255508
    BragaPortugal0.6%BragaUC 117219
    BrasíliaBrazil1.4%BrasiliaUC 5855283
    BratislavaSlovakia4.0%BratislavaUC 8984
    BrisbaneAustralia10.8%BrisbaneUC 2734701
    BristolUnited Kingdom4.9%BristolUC 3058173
    BrusselsBelgium8.4%BrusselsUC 1290235
    BucharestRomania4.3%BucharestUC 2359260
    BudapestHungary10.9%BudapestUC 964368
    Buenos AiresArgentina4.7%Buenos AiresUC 44432,186
    BusanSouth Korea3.5%BusanUC 3920355
    CairoEgypt3.1%CairoUC 46051,680
    CalgaryCanada2.1%CalgaryUC 1262533
    CanberraAustralia42.7%North Canberra [Canberra]UC 192221
    Cape TownSouth Africa1.8%Cape TownUC 431695
    CardiffUnited Kingdom4.2%CardiffUC 1943113
    CartagenaColombia1.8%CartagenaUC 3275114
    CasablancaMorocco0.1%CasablancaUC 2102415
    Cebu CityPhilippines9.3%Cebu CityUC 5065416
    CharlotteUnited States52.1%CharlotteUC 7707131
    ChengduChina3.2%ChengduUC 6378867
    ChennaiIndia4.8%ChennaiUC 103001,052
    Chiang MaiThailand9.0%Chiang MaiUC 173225
    ChicagoUnited States16.1%ChicagoUC 75322,046
    ChișinăuMoldova10.9%ChișinăuUC 442101
    ChristchurchNew Zealand2.1%ChristchurchUC 353124
    ClevelandUnited States22.4%ClevelandUC 7833413
    CologneGermany15.6%CologneUC 1186296
    ColomboSri Lanka47.8%Colombo [Sri Jayawardenepura Kotte]UC 6321,206
    ColumbusUnited States13.1%ColumbusUC 7735442
    CopenhagenDenmark3.9%CopenhagenUC 698302
    CórdobaArgentina1.6%CordobaUC 2335320
    CuencaEcuador4.2%CuencaUC 224989
    CuritibaBrazil3.6%CuritibaUC 6350566
    Da NangVietnam2.4%Đà NẵngUC 5294225
    DakarSenegal0.1%DakarUC 39277
    DallasUnited States49.2%DallasUC 63971,237
    DelhiIndia0.7%New DelhiUC 79632,139
    DenverUnited States4.5%DenverUC 59321,194
    DetroitUnited States22.2%DetroitUC 77841,170
    DohaQatar0.1%DohaUC 153392
    DubaiUnited Arab Emirates0.8%DubaiUC 1007854
    DublinIreland5.7%DublinUC 394301
    DurbanSouth Africa17.7%DurbanUC 4787807
    DüsseldorfGermany14.9%DusseldorfUC 826246
    EdinburghUnited Kingdom5.0%EdinburghUC 2186130
    EdmontonCanada6.9%EdmontonUC 1564435
    FlorenceItaly8.2%FlorenceUC 3005196
    FlorianópolisBrazil5.7%FlorianópolisUC 6961182
    FrankfurtGermany8.6%FrankfurtUC 3400193
    FukuokaJapan1.9%FukuokaUC 907450
    GdańskPoland7.8%GdanskUC 2198108
    GenevaSwitzerland5.8%GenevaUC 6974
    George TownMalaysia6.3%George TownUC 176134
    GhentBelgium6.3%GhentUC 68994
    GlasgowUnited Kingdom16.4%GlasgowUC 683309
    Gold CoastAustralia7.4%Gold CoastUC 2798168
    GothenburgSweden10.7%GothenburgUC 75191
    GrazAustria21.7%GrazUC 96176
    GuadalajaraMexico0.1%GuadalajaraUC 3105598
    GuangzhouChina3.0%GuangzhouUC 10933Shared source unit6,454
    Guatemala CityGuatemala4.0%Guatemala CityUC 2089470
    HalifaxCanada62.8%HalifaxUC 4055103
    HamburgGermany32.9%HamburgUC 4184478
    HamiltonCanada11.6%HamiltonUC 2679173
    HangzhouChina0.6%HangzhouUC 113111,517
    HanoiVietnam4.6%HanoiUC 1999925
    HelsinkiFinland1.5%HelsinkiUC 572381
    Ho Chi Minh CityVietnam2.1%Ho Chi Minh CityUC 52391,487
    HobartAustralia0.5%HobartUC 78146
    Hong KongChina5.0%Hong KongUC 11185220
    HonoluluUnited States11.8%HonoluluUC 193177
    HoustonUnited States56.5%HoustonUC 61671,859
    HyderabadIndia1.2%HyderabadUC 9524889
    IncheonSouth Korea3.4%SeoulUC 348Shared source unit2,282
    IstanbulTürkiye0.6%IstanbulUC 26371,269
    IzmirTürkiye0.3%IzmirUC 1094307
    JakartaIndonesia6.8%JakartaUC 54724,614
    JeddahSaudi Arabia0.1%JeddahUC 1112696
    JohannesburgSouth Africa2.8%JohannesburgUC 35121,756
    Johor BahruMalaysia7.4%Johor BahruUC 2979418
    KaohsiungTaiwan0.5%KaohsiungUC 1919372
    KathmanduNepal0.9%KathmanduUC 1822350
    KigaliRwanda4.8%KigaliUC 597286
    KingstonJamaica14.2%KingstonUC 795118
    Kitchener–WaterlooCanada21.2%KitchenerUC 2408147
    KrakówPoland25.5%KrakowUC 3662176
    Kuala LumpurMalaysia7.2%Kuala LumpurUC 16481,340
    KyotoJapan1.3%OsakaUC 4399Shared source unit2,212
    La PazBolivia0.1%La PazUC 212291
    LagosNigeria1.9%LagosUC 12891,199
    Las VegasUnited States0.5%Las VegasUC 4625851
    LausanneSwitzerland13.3%LausanneUC 24775
    LeedsUnited Kingdom13.4%LeedsUC 4332321
    LeipzigGermany18.6%LeipzigUC 5304180
    LilleFrance8.0%LilleUC 3449228
    LimaPeru0.7%LimaUC 2171984
    LisbonPortugal1.8%LisbonUC 231426
    LiverpoolUnited Kingdom5.2%LiverpoolUC 2264388
    LjubljanaSlovenia7.5%LjubljanaUC 8265
    LondonUnited Kingdom5.7%LondonUC 58161,649
    Los AngelesUnited States0.7%Los AngelesUC 20074,498
    LuxembourgLuxembourg11.4%LuxembourgUC 6840
    LyonFrance3.2%LyonUC 3978256
    MadridSpain2.5%MadridUC 3338680
    MálagaSpain0.1%MálagaUC 311575
    MalmöSweden1.3%MalmoUC 55884
    ManchesterUnited Kingdom7.7%ManchesterUC 3340751
    ManilaPhilippines7.3%ManilaUC 23232,555
    MarrakeshMorocco0.8%MarrakeshUC 1853124
    MarseilleFrance3.9%MarseilleUC 4182185
    MedellínColombia12.8%MedellínUC 2676233
    MelbourneAustralia1.8%MelbourneUC 17471,611
    MendozaArgentina1.6%MendozaUC 214208
    MéridaMexico0.8%MéridaUC 6875182
    Mexico CityMexico0.1%Mexico CityUC 54022,134
    MiamiUnited States9.5%MiamiUC 71682,784
    MilanItaly1.4%MilanUC 1498785
    MinneapolisUnited States37.9%Minneapolis [Saint Paul]UC 7181611
    MonterreyMexico1.2%MonterreyUC 6131685
    MontevideoUruguay2.4%MontevideoUC 804237
    MontrealCanada18.0%MontrealUC 37001,020
    MumbaiIndia0.4%MumbaiUC 7599738
    MunichGermany7.8%MunichUC 5249345
    MuscatOman0.5%MuscatUC 1124148
    NagoyaJapan0.5%NagoyaUC 52132,392
    NairobiKenya9.8%NairobiUC 1717598
    NaplesItaly2.8%NaplesUC 4490618
    NashvilleUnited States27.7%NashvilleUC 7090160
    New OrleansUnited States6.9%New OrleansUC 6607417
    New York CityUnited States10.3%New York CityUC 80993,031
    NiceFrance15.2%NiceUC 4746108
    OrlandoUnited States20.0%OrlandoUC 7243750
    OsakaJapan1.3%OsakaUC 4399Shared source unit2,212
    OsloNorway7.3%OsloUC 828244
    OttawaCanada28.5%OttawaUC 3494208
    PalermoItaly1.9%PalermoUC 4376123
    Panama CityPanama10.7%Panama CityUC 658277
    ParisFrance3.9%ParisUC 28781,421
    PerthAustralia1.8%PerthUC 498784
    PhiladelphiaUnited States12.2%PhiladelphiaUC 8029654
    PhoenixUnited States1.7%PhoenixUC 46991,304
    PhuketThailand7.6%PhuketUC 1645124
    PittsburghUnited States28.4%PittsburghUC 7847245
    Port LouisMauritius24.0%Port LouisUC 159136
    PortlandUnited States12.1%PortlandUC 4941877
    PortoPortugal1.7%PortoUC 1058324
    Porto AlegreBrazil8.7%Porto AlegreUC 5971599
    PragueCzechia8.3%PragueUC 560263
    PuneIndia2.1%PuneUC 8258580
    Québec CityCanada41.4%QuebecUC 4012275
    QuerétaroMexico0.3%QuerétaroUC 5097169
    QuitoEcuador3.7%QuitoUC 2544380
    RaleighUnited States58.3%RaleighUC 779172
    RecifeBrazil6.1%RecifeUC 8388491
    ReykjavíkIceland0.0%ReykjavikUC 4897
    RigaLatvia26.4%RigaUC 102147
    Rio de JaneiroBrazil3.5%Rio de JaneiroUC 77991,285
    RiyadhSaudi Arabia0.1%RiyadhUC 30261,108
    RomeItaly4.7%RomeUC 3938467
    RotterdamNetherlands7.0%Rotterdam [The Hague]UC 244677
    SacramentoUnited States6.1%SacramentoUC 4092759
    Salt Lake CityUnited States4.6%Salt Lake CityUC 5377527
    SalvadorBrazil7.9%SalvadorUC 8238323
    SalzburgAustria6.7%SalzburgUC 41532
    San AntonioUnited States51.9%San AntonioUC 5794640
    San DiegoUnited States1.2%San DiegoUC 2471778
    San FranciscoUnited States3.5%San FranciscoUC 14611,614
    San JoséCosta Rica6.4%San JoséUC 363491
    San JuanPuerto Rico9.1%Bayamón [San Juan]UC 213309
    San Pedro SulaHonduras10.8%San Pedro SulaUC 511211
    San SalvadorEl Salvador9.7%San SalvadorUC 916264
    SantiagoChile1.0%SantiagoUC 2334801
    Santo DomingoDominican Republic6.2%Santo DomingoUC 1667483
    São PauloBrazil1.7%São PauloUC 72772,111
    SapporoJapan1.4%SapporoUC 351353
    SarajevoBosnia and Herzegovina6.8%SarajevoUC 42661
    SeattleUnited States12.9%SeattleUC 50981,123
    SeoulSouth Korea3.4%SeoulUC 348Shared source unit2,282
    SevilleSpain0.4%SevilleUC 202480
    ShanghaiChina0.9%ShanghaiUC 113453,128
    ShenzhenChina3.0%GuangzhouUC 10933Shared source unit6,454
    SingaporeSingapore5.5%SingaporeUC 178438
    SofiaBulgaria5.4%SofiaUC 109201
    StockholmSweden22.9%StockholmUC 1693339
    StuttgartGermany9.4%StuttgartUC 4022257
    SurabayaIndonesia2.8%SurabayaUC 74591,304
    SydneyAustralia14.0%SydneyUC 23241,378
    TaichungTaiwan0.9%TaichungUC 906313
    TaipeiTaiwan8.8%TaipeiUC 1142972
    TallinnEstonia20.6%TallinnUC 99121
    TampaUnited States18.1%TampaUC 7012431
    TampereFinland6.1%TampereUC 42569
    Tel AvivIsrael3.0%Tel AvivUC 457333
    ThessalonikiGreece0.4%ThessalonikiUC 585117
    TiranaAlbania7.7%TiranaUC 714115
    TokyoJapan1.5%TokyoUC 5929Shared source unit5,165
    TorontoCanada11.9%TorontoUC 28691,620
    ToulouseFrance2.1%ToulouseUC 2268252
    TrondheimNorway1.8%TrondheimUC 55457
    TunisTunisia0.0%TunisUC 1399488
    TurinItaly0.6%TurinUC 70212
    TurkuFinland14.1%TurkuUC 9323
    UtrechtNetherlands9.3%UtrechtUC 1951115
    ValenciaSpain0.3%ValenciaUC 4522223
    VallettaMalta0.0%VallettaUC 87100
    VancouverCanada4.7%VancouverUC 358649
    VictoriaCanada12.3%VictoriaUC 6112
    ViennaAustria7.9%ViennaUC 1081325
    VilniusLithuania17.5%VilniusUC 57889
    WarsawPoland15.8%WarsawUC 3712415
    Washington DCUnited States51.4%WashingtonUC 79101,301
    WellingtonNew Zealand35.7%WellingtonUC 50564
    WinnipegCanada12.1%WinnipegUC 2013287
    WrocławPoland16.5%WrocławUC 1599118
    YokohamaJapan1.5%TokyoUC 5929Shared source unit5,165
    ZagrebCroatia10.6%ZagrebUC 419151
    ZurichSwitzerland12.0%ZurichUC 1689187

    The table scrolls. Search checks the complete cohort. Display values are rounded; original numeric values and source literals remain in the downloads. A shared source unit is one physical measurement repeated for named destinations.

    Inspect the source record

    The two signals for Abu Dhabi.

    Open destination profile

    The urban fabric

    Two signals for Abu Dhabi.

    Source footprint: Abu Dhabi · urban centre 325.

    Explore the source desk

    High-greenness exposure

    0.5%

    Nominal 2025 · modelled population exposure

    Population exposure to high greenness in the source model. This does not measure public park access or walking distance.

    NDVI calendar window: not supplied.

    Mapped road density

    20.4km/km²

    2024 mapped roads · 2025 footprint

    Mapped road length relative to footprint area. A higher value does not establish better transport, walkability or road safety.

    Network completeness: unknown.

    2025 footprint · 107 km²Projected footprint population · 508,976Source context · outside the index
    Methods, units & the source boundary

    The source geography is a fixed 2025 morphological urban-centre footprint, not a municipality or functional metropolitan area. Destinations sharing a footprint repeat the same contextual measurements; they are not independent city estimates. These records are not approved inputs to Civometra V1 or V2 and produce no ranking or quarterly results.

    Modelled greenness. The publisher estimates the share of population living in areas classified as having high greenness. Its method combines a 300-metre buffer of built-up cells, three-year average satellite NDVI, population grids and thresholds that vary by agro-ecological zone. Source field SD_POP_HGR_2025; original value 0.510646737 percent. Population denominator: Projected population within the fixed 2025 urban-centre footprint, GHS-POP R2023A. Not a current census count. The nominal model epoch does not identify an exact NDVI image date or calendar window.

    Road conversion. Source density 0.020433723 m/m² × 1,000 = 20.433723 km/km². Source mapped road length: 2,186,408 m (IN_ROA_LEN_2024), referenced to the source footprint area (GC_UCA_KM2_2025). We convert the published density rather than replacing it with a ratio of rounded display values.

    Comparison limits. The two quantities have different source epochs and are not a trend. The footprint describes settlement form, not municipal boundaries or a commuting region. Model uncertainty and road-network completeness are not quantified here; displayed decimals do not establish measurement accuracy.

    Source edition: GHS-UCDB R2024A V1.2. Source review: 2026-10-30. The review date does not update either source epoch.

    Read the source citation

    European Commission, Joint Research Centre, GHS Urban Centre Database 2025, GHS-UCDB R2024A V1.2; doi:10.2905/1a338be6-7eaf-480c-9664-3a8ade88cbcd. Abu Dhabi refers here to source urban centre 325, Abu Dhabi, a 2025 morphological footprint of 107.00 km². Nominal-2025 modelled high-greenness population exposure: 0.5% (SD_POP_HGR_2025); the NDVI observation calendar window is not supplied, and this is not park access. Mapped 2024 road density: 20.4 km/km², converted from 0.020433723 m/m² by multiplying by 1,000; network completeness is unknown. Shared destination references: none in this catalog. These are source context, not independent municipal measurements or a livability score. Reviewed 2026-10-30. Original dataset: https://data.jrc.ec.europa.eu/dataset/1a338be6-7eaf-480c-9664-3a8ade88cbcd Source records: https://bestcitytolive.com/data/urban-fabric-context.json.

    Keep the source unit and the two different epochs when quoting.

    Start with scale. Then investigate the street.

    A 2025 morphological urban centre follows settlement form. It does not represent a city hall’s territory, a commuting region or every neighbourhood equally. Read the native source name and area before comparing two destination names.

    Use modelled exposure to frame questions about vegetation, heat and public space. To plan an actual outing, check local park ownership, routes, opening times and accessibility separately.

    A comparison needs its source attached.

    The source has no universal “higher is better” rule for these two features. Climate, urban form, mapping coverage and model thresholds affect interpretation. No source confidence interval is provided here, and these point values do not establish statistically distinguishable city conditions.

    The 2025 model and 2024 mapped network are different quantities and epochs. They do not form a change-over-time series or new Civometra results.

    Methods & source material

    An edition you can inspect.

    European Commission, Joint Research Centre · GHS-UCDB R2024A V1.2. Evidence review: 2026-10-30. That review does not refresh either source epoch.

    Mapped roads · infrastructure source archive

    Retrieved 2026-10-30T01:17:19.864226+00:00. The archive contains the publisher’s thematic table, factsheet, manual and readme.

    Archive SHA-256c4424aff23a443ec6136f29985df7dcd4abdf2b712607c35204f1273f9682cca

    Original CSV memberGHS_UCDB_THEME_INFRASTRUCTURES_GLOBE_R2024A.csv

    Original member SHA-256ded414728840585d0d412d8fc73a6e03f5d5e5c65651c1d79bdc60365e2dbe37

    Greenness model · SDG source archive

    Retrieved 2026-10-30T01:17:22.796964+00:00. The archive contains the publisher’s thematic table, factsheet, manual and readme.

    Archive SHA-256967d7b048a69ca5a2d72779eb3bb5b451407badf1304cfcf90ff748704d46f94

    Original CSV memberGHS_UCDB_THEME_SDG_GLOBE_R2024A.csv

    Original member SHA-25637cf7b7a5e26a53606b79d376f8482cc7f782c030500af7f283d2a1bc2a04ab0

    Read the complete definitions, version notes & credits

    Modeled greenness exposure

    The publisher estimates the share of population living in areas classified as having high greenness. Its method combines a 300-metre buffer of built-up cells, three-year average satellite NDVI, population grids and thresholds that vary by agro-ecological zone.

    This measures modeled exposure to vegetation. It does not measure access to public parks, public ownership, tree-canopy cover, walking routes or how green every neighborhood feels. The source factsheet does not specify the exact three-year NDVI calendar window. The 2025 population is projected; the footprint is the 2025 morphological urban centre.

    No source confidence interval is provided in this thematic table. Model, mapping and threshold uncertainty remains.

    V1.2. The publisher reports an algorithm bug fix relative to V1.0; earlier edition values should not be mixed.

    Upstream credits: UN-Habitat Global Urban Indicators Database 2024; USGS Landsat NDVI; JRC GHS-POP and GHS-BUILT-S R2023A.

    Mapped road density

    Mapped road length inside the urban-centre footprint, divided by that footprint’s area. The road source is Overture Maps, accessed by the publisher on 24 July 2024. Source units are m/m2; the displayed unit conversion multiplies by 1000.

    This describes the intensity of the mapped road network. It does not measure walkability, transit frequency, congestion, road quality or road safety. More road density is not automatically better. The mapped roads refer to 2024 and the common urban-centre boundary to 2025.

    No source confidence interval or mapping-completeness estimate is provided for these city records.

    Upstream credits: Overture Maps Foundation; European Commission, Joint Research Centre.

    The archive filename, Version field and update log identify V1.2. The unchanged publisher readme also retains older V1.1 alternative-name and document-version strings.

    Mari Rivero, I., et al. (2024). GHS-UCDB R2024A — GHS Urban Centre Database 2025. European Commission, Joint Research Centre (JRC). Version 1.2. doi:10.2905/1a338be6-7eaf-480c-9664-3a8ade88cbcd.

    European Commission, Joint Research Centre, GHS-UCDB R2024A V1.2. Original feature-provider credits are retained in the definitions and unchanged source archives.

    Creative Commons Attribution 4.0 International ↗