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  • A master list of the best Ortho4XP sources for each country

    THIS LIST IS COMPLETELY DEPENDENT ON YOUR FEEDBACK

     

    Some notifications
    There may be several listings for each country and not every country will have full coverage per source and combinations may be needed.
    Some sources need editing of the carnet_d_adress.py file in ortho or other modifications to work. See the bottom of this list for how to get the sources you won't find in the source list of ortho.
    WARNING: Do NOT use these for airport creation or in any way distribute the downloaded tiles in any way. Even when making freeware or sharing them for no charge.
    Doing so may violate the source providers terms of use. These are meant to be for personal use ONLY. As of why this is get approval of usage, consult the source provider in question.
    There is a list at the bottom of this page with an (somewhat limited) explanation for each source.

    For a short "how to guide" for Ortho and other x-plane related questions see the BEGINNERS GUIDE
    .
    Explenation of list parameters:
    I follow an approximate satisfaction rate in percent (higher is better on all):

    Clouds: 0-100% -there might be clouds in the ortho images. Example: 100%= NO clouds -95% Some clouds here and there but not interfering much with immersion.
    Color match: 0-100% -the color matching between and within areas of tiles. Example: 100% NO difference at all between tiles or patches within tiles. 60%=big differences between tiles and some severe patches.
    ZL coverage: 15-19 -Many sources may have less covered tiles in higher zoom levels resulting in black or white squares in the landscape (this parameter is mostly for what the info provider has tested)

    When giving info - please do so in this format:

    Country
    [short name of the source]

    Clouds: 100%

    Color Match: 95%
    ZL: all 15-17=100% 18-19=85%

    The sources with N/A on them are not tested and I have no info on them, but they are sorted under the country they belong. So feel free to test and give feedback :)

     

     

    So, let the list begin 😃

    A

    Australia
    AU_1
    Clouds: N/A
    ColorMatch: N/A
    ZL: N/A

    BI
    Clouds: 95%
    Color match: 95%
    ZL: tested 16-19 99%

    Austria
    OST

    Clouds: N/A
    ColorMatch: N/A
    ZL: N/A

    GO2
    Clouds: 90%

    Color match: 75%
    ZL: tested 16-19 100%


    B

    Belgium
    BE_Wa

    Clouds: N/A
    ColorMatch: N/A
    ZL: N/A

    BI
    Clouds: 100%
    ColorMatch: 100%
    ZL: 15-19 = 100%


    C

    Canada
    Arc NW Territories loc: Yellowknife (CYZF)
    Clouds: 100%

    Color Match: 100%
    ZL: 17 = 100% (no other ZLs tested, but ZL17 looked terrific at high and low altitudes - I do not recommend to try a higher ZL due to diminishing returns, increased size and time to convert orthos)

    China (regions tested: west of Shanghai/ZSPD to Nyingchi Mainling/ZUNZ)
    Arc

    Clouds: 95%

    Color Match: 95%
    ZL: 17 = 100% (no other ZLs tested, but ZL17 looked terrific at high and low altitudes - I do not recommend to try a higher ZL due to diminishing returns, increased size and time to convert orthos)

    Croatia
    CRO
    Clouds: N/A
    ColorMatch: N/A
    ZL: N/A


    Czech Republic
    CZ (Mapy.cz)
    Clouds: 100%
    (But has watermarks)
    ColorMatch: 100%
    ZL 100%

    BI
    Clouds: 97%
    ColorMatch: 100%
    ZL: 16-19 = 100%


    D

    Denmark
    DN

    Clouds: N/A
    ColorMatch: N/A
    ZL: N/A

    BI
    Clouds: 100%
    ColorMatch: 95%
    ZL: 15-17 = 100%


    E

    Estonia
    EST
    Clouds: N/A
    ColorMatch: N/A
    ZL: N/A

    England
    BI
    Clouds 100%
    Colormatch ~97%
    ZL: ZL16


    F

    Faroe Islands
    FO
    Clouds: N/A
    ColorMatch: N/A
    ZL: N/A

    France
    BI
    Clouds: 99%

    Color Match: 90%
    ZL: 16 to 19 = 100%

    FR
    Clouds: N/A
    ColorMatch: N/A
    ZL: 17

    FR_sat / FR_sat2 / FR_satP / Top25
    Clouds: N/A
    ColorMatch: N/A
    ZL: 17 / 17 / 18 /16

    F44
    (La Loire atlantique vue du ciel - this specific area around Nantes, France: http://vuduciel.loire-atlantique.fr/#11/47.3435/-1.6788)
    Clouds: 100%
    ColorMatch: 100% (within the area - not sure about adjunct tiles)
    ZL: 15-19 = 100%


    G

    Germany
    BI
    Clouds: 98%

    Color Match: 95%
    ZL: all 16-19 = 100%

    DE
    Clouds: N/A

    Color Match: N/A
    ZL: all 16-19 = N/A

    Greece
    BI
    Clouds: 95%

    Color Match: 90%
    ZL: 17
    = 100%

    H


    I

    Iceland
    BI
    Clouds: 95%
    Color Match:95%
    ZL: 16-17 = 100%

    India
    Northern India (Himalayas, NE India, West and east India)
    BI
    Clouds: 70-80%
    Color Match: 90-100%
    ZL 16-19 100%

    GO/GO2
    Coluds-50-60%
    Color Match: 70%
    ZL 16-19 80%

    Southern India (Peninsular Plateau and Islands)
    GO/GO2
    Clouds 70%
    Color Match 90%
    ZL 16-19 90%

    Ireland
    BI
    Clouds: <1%

    Color Match: <95%
    ZL: 16 - 19 = 100%

    Italy

    IT
    Clouds: 100%

    Color match: 100%
    ZL: 16-19 100%

    BI
    Clouds: 95%
    Color Match: 95%
    ZL17: 100%



    J

    Japan
    JP
    Clouds: N/A
    ColorMatch: N/A
    ZL: N/A


    K


    L

    Luxemburg
    BI
    Clouds: 100%

    Color Match: 100%
    ZL: 16-19
      100%


    M

    Mexico
    BI
    Clouds: 95%
    Color match: 99%
    ZL 16 100%. ZL 17 tested in a small region in the south, similar results to ZL16, with better resolution of course, but haven't done the whole country at ZL17.


    N

    Netherlands
    NE  
    not working - only white tiles ( NE2 works )

    NE2
    Clouds: 100%
    Color match: 99%
    ZL: tested 16 and 18: 100%

    ARC ( Same source as NE2, but you wont get white tiles in countries next to it as in NE2 )
    Clouds: 100%
    Color match: 99%
    ZL: tested 16 and 17: 100%

    BI (has gotten worse after last update summer/fall 2017 - make copy of old source if you have them)
    Clouds: 90%
    Colormatch: 80%
    ZL:16 and 17


    New Zealand
    NZ
    (Partial but very good in some places)
    Clouds: N/A

    ColorMatch: N/A
    ZL: N/A

    For NewZealand you might want to check out http://forums.x-plane.org/index.php?%2Ffiles%2Ffile%2F38709-lyndiman’s-new-zealand-ortho-photography-set%2F

    Norway
    NO X (needs tweaking to get into ortho)
    Clouds:100%
    Color Match:80%
    ZL coverage: 15-17 100% / 18-19 95%

    NO3 X (needs tweaking to get into ortho)
    Clouds:100%
    Color Match:80%
    ZL coverage: 15-17 99% / 18-19 90%

    ARC
    Clouds: 80%
    Color match: 85%
    ZL: 15-17 100%

    SE (map.eniro.no)
    Clouds: 90%

    Color match: 85%
    ZL: 15-17 100%


    O


    P

    Poland
    PL
    Clouds: N/A
    ColorMatch: N/A
    ZL: N/A


    Q


    R


    S

    Spain
    ARC (ArcGIS Online)
    Clouds: 95% depends on ZL

    Color Match: 90%
    ZL: 17-19 100%

    BI
    Clouds: 95% (canary islands suffer on this - try ARC here)

    Color match: 90%
    ZL: 16 to 18 tested

    SP
    Clouds: 94%

    ColorMatch: 98%
    ZL: 18 and 19 tested

    But for all these (is)lands , including the Canary , Spain main land and Portugal , you will get the best results with http://www.spainuhd.es/

    Spainuhd is a mix of ZL 17 ( inland ) , ZL 18 ( shorelines and airports ) and some ZL 19 ( El hierro and La palma )

    Slovenia
    SLO

    Clouds: N/A
    ColorMatch: N/A
    ZL: N/A

    Slovakia
    CZ (Mapy.cz)
    Clouds: 100%
    (But has watermarks)
    ColorMatch: 100%
    ZL 100%

    BI
    Clouds: 97%
    ColorMatch: 100%
    ZL: 16-19 = 100% (Some tiles might be missing at higher ZL not tested enough to be certain. Blank tiles found)

    South Africa (Johannesburg/FAOR and Maputo/FQMA regions)
    Arc

    Clouds: 100%

    Color Match: 100%
    ZL: 17 = 100% (no other ZLs tested, but ZL17 looked terrific at high and low altitudes - I do not recommend to try a higher ZL due to diminishing returns, increased size and time to convert orthos)

    Sweden
    SE
    Clouds: 90%

    Color match: 85%
    ZL: tested 15-17 100%

    SE2

    Clouds: N/A

    ColorMatch: N/A
    ZL: N/A

    Hitta (supposed to be good - not tested)
    Clouds: N/A

    Color match: N/A
    ZL: N/A


    Switzerland
    CH (Watermarked)
    Clouds: N/A
    ColorMatch: N/A
    ZL: N/A

    GE (Geneva area only)
    Clouds: 100%
    ColorMatch: 100%
    ZL: 15-19 = 100%

    BI
    Clouds: 90%

    Color match: 90%
    ZL: tested 16-19 90%


    T

    Tahiti and Moorea (French Polynesia)
    FRsatp 
    Clouds: 97%
    Color match: 99%
    ZL: tested 17: 100%


    U

    USA Alaska
    ASK_1 ASK_2 (INACTIVE / NOT AVAILABLE)
    Clouds: N/A
    ColorMatch: N/A

    ZL: N/A

    USA general
    USA_1
    Clouds: N/A
    ColorMatch: N/A

    ZL: N/A

    USA_2
    Clouds: N/A
    ColorMatch: N/A

    ZL: N/A

    USA West Coast & Midwest plains, Texas, etc
    BI
    Clouds: 100%

    Color match: 90%
    ZL: 17 100%

    St Thomas Island (Caribbean)
    BI
    Clouds: 95%

    Color Match: 98%
    ZL: 18 
    = 100%


     

    UK
    BI
    Clouds: 99%

    Color Match: 95% (scottish highlands are effected)
    ZL: 16 - 19 100%

    V


    W


    X


    Y


    Z


     

    _________________________________________________________________________________________________
     

    Some sources mentioned are not listed in the native Ortho4xp and will need a "hack" to be enabled.

    Might be worth testing:

    EOX

    Clouds: 100%
    Color Match: 99%
    ZL: 0-14=100%

    Requires the following changes to Carnet_d_adresses.py:

    https://github.com/d41k4n/Ortho4XP/commit/caac8e369bc90acb999c6ea7fdbcdd141326858a

    Alternatively you can download the modified Carnet_d_adresses.py


    NO
    Download the edited ortho version here: https://github.com/d41k4n/Ortho4XP/tree/hacks/norway-source and copy only "carnet_d_adresses.py" and "Ortho4xp.py" to your ortho4xp folder.
    Also make sure that the sources alias "NO" is listed in the list of  source codes (in the carnet_d_adresses file - open it in notepad). (Appears in the drop down list of sources in ortho)
    Ortho carnet d adresses.JPG

    NO2
    Copy the following text and paste it between other source codes in your carnet_d_adress.py file (open and edit with notepad)
    Also make sure that the sources alias "NO2" is listed in the list of  source codes

        ####################################################
        # National geographical institute of Norway
        # Unsure about copyright
        ####################################################
        elif website in ['NO2']:
            if not pyproj_loaded:
                return 'error'
            text_til_x_left=(til_x_left//16)*16
            text_til_y_top=(til_y_top//16)*16
            montx=0 if til_x_left%16==0 else 1
            monty=0 if til_y_top%16==0 else 1
            [latmax,lonmin]=gtile_to_wgs84(text_til_x_left,text_til_y_top,zoomlevel)
            [latmin,lonmax]=gtile_to_wgs84(text_til_x_left+16,text_til_y_top+16,zoomlevel)
            [ulx,uly]=pyproj.transform(epsg['4326'],epsg['32633'],lonmin,latmax)
            [urx,ury]=pyproj.transform(epsg['4326'],epsg['32633'],lonmax,latmax)
            [llx,lly]=pyproj.transform(epsg['4326'],epsg['32633'],lonmin,latmin)
            [lrx,lry]=pyproj.transform(epsg['4326'],epsg['32633'],lonmax,latmin)
            text_minx=min(ulx,llx)
            text_maxx=max(urx,lrx)
            text_miny=min(lly,lry)
            text_maxy=max(uly,ury)
            deltax=text_maxx-text_minx
            deltay=text_maxy-text_miny
            minx=text_minx+montx*deltax/2.0
            maxx=minx+deltax/2.0
            miny=text_miny+(1-monty)*deltay/2.0
            maxy=miny+deltay/2.0
            url="http://openwms.statkart.no/skwms1/wms.georef_nib?version=1.3.0&\
                 service=WMS&request=GetMap&layer=Georef-omlopsfoto_orto50&format=image/jpeg&\
                 STYLE=default&SRS=EPSG%3A32633&BBOX="+\
                 str(minx)+','+str(miny)+','+str(maxx)+','+str(maxy)+\
                 "&WIDTH=2048&HEIGHT=2048"
            fake_headers=fake_headers_generic

    NO3
    Copy the following text and paste it between other source codes in your carnet_d_adress.py file (open and edit with notepad)
    Also make sure that the sources alias "NO3" is listed in the list of  source codes

        ####################################################
        # Norway Webatlas by twitch.tv/GiantUnicorn
        # Unsure about copyright
        ####################################################
        elif website=='NO3':
            url="https://waapi.webatlas.no/maptiles/tiles/webatlas-orto-newup/wa_grid/"+\
                str(zoomlevel)+"/"+str(til_x)+"/"+str(til_y_top)+".jpeg?APITOKEN=9da664c7-e5b9-4dc7-a093-7ef0f90563c0"
            fake_headers=fake_headers_generic

     

    Some Explenations:
    OSM = Open Street map - NOT to be used for ortho tiles creations!
    BI              = bing.com
    GO / GO2 = google.com
    Here          = here.com
    ARC          = arcgisonline.com
    USA_1      = nationalmap.gov
    USA_2      = arcgisonline.com
    FR            = geoportail.fr
    FR_sat     = geosud.fr (ZL17)
    FR_sat2   = geosud.fr (ZL17)
    FR_satP   = geosud.fr (ZL18)
    TOP_25   = geosud.fr (ZL 16)
    DE            = geodatenzentrum.de
    SP            = ign.es
    IT              = minabiente.it
    SE2          = lantmateriet.se
    Hitta / SE   = eniro.no
    PL             = geoportal.gov.pl
    BE_Wa      = geoservices.wallonie.be
    NE             = gdsc.nlr.nl
    NE2           = geodata1.nationaalgeoregister.nl
    SLO          = gis.arso.gov.si
    CRO          = geoportal.dgu.hr
    OST          = wien.gov.at
    CH             = map.geo.admin.ch
    AU_1         = gov.au
    NZ             = govt.nz
    JP              = go.jp
    FO             = kortal.fo
    F44           = http://vuduciel.loire-atlantique.fr/#11/47.3435/-1.6788
    GE            = ge.ch/sitg


    Have I missed something? Something to add? Please drop me a note and I'll get right to it 😃

    Have a nice day, happy landings and blue skies! :)

    Magnus Lorvik
    aka fur0r3 & muug (muugart)

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