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UPDATED 18.07.2018

A master list of the best Ortho4XP sources for each country

THIS LIST IS COMPLETELY DEPENDENT ON YOUR FEEDBACK

 


THIS IS NOT A SUPPORT THREAD FOR ORTHO - PLEAS ONLY GIVE FEEDBACK ON COVERAGE AND READ THIS INTRO BEFORE COMMENTING

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 O
NLY. 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

Daikan from x-plane.org has some great advice:

Just a remark: Before embarking on the creation of orthophoto scenery for large areas (and potentially wasting a lot of time, bandwidth and disk space in the process) it is highly suggested to go check out the imagery online interactively before doing so.
Arc: 
https://server.arcgisonline.com/arcgis/rest/services/World_Imagery/MapServer?f=jsapi
GO2: https://maps.google.com
Bing: https://www.bing.com/maps/aerial
etc. (see carnet_d_adresses.py for more URL's)
Sampling different areas at your desired zoom level(s) should give you a good idea of the overall quality pretty quickly.

First lesson with Ortho4XP: Hold off from downloading terabytes of data at once before you haven't done some sampling - either through the provider's website or using the custom zoomlevel function...

 

About this list:
.
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%

All the parameters are made with the thought of having 100% as the most positive. That is why cloud coverage might seem somewhat counter intuitive. See it as 100% gone 

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 

 

Check out ZonePhoto! It has good quality and covers most of Europe and some other areas (All ZL 16)
 

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: 90%
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%

Chile
BI
Clouds: 100%
ColorMatch: 100%
ZL: 17


D

Denmark
DN
Clouds: N/A
ColorMatch: N/A
ZL: N/A

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

Domonican Republic
BI
Clouds: N/A
ColorMatch: N/A
ZL: N/A
(No data - but has been said to give satisfynig results)


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
(Scroll near the end of this post for how to get this working)

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: 90%
Color match: 70%
ZL: 16-19 100%

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

ARC
Clouds: 99%
Color Match: 98%
ZL17: 100%


J

Japan
JP
Clouds: 90%
ColorMatch: 100%
ZL: 17/ 18


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 (needs tweaking to get into ortho - see further down for how)
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/ (Spanish website)

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

Taiwan
ARC / USA2
Clouds: 98%
ColorMatch: 98%
ZL: 17=100% ZL18=10%

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

DE
You will need to go "fish" for the session cookie and replace the value in 
line 338 of Carnet_d_adresses.py.
You can do that by opening the network tab of your browser debugger (i.e. press "CTRL+Shift+E" in Firefox) and got to 
this URL.
Then select any request and look for the "Cookie" header. Copy&Paste the value into Carnet_d_adresses.py as mentioned above.
Credit: Daikan from x-plane.org

GO2

https://github.com/d41k4n/Ortho4XP/commit/dbaa04b8c4f15e1fc144d3ea3411ee300ea9af32

Replaces the current GO/GO2 source definition with one that does not suffer from having to manually update the map version (which I think is the root cause for the problem described).

You can also download the whole file which contains some other fixes from my GitHub repo here:

https://github.com/d41k4n/Ortho4XP/raw/dbaa04b8c4f15e1fc144d3ea3411ee300ea9af32/Carnet_d_adresses.py

Credit: Daikan from x-plane.org
OP disclaimer: My changes available on Github are still a work in progress and might not always work as they're only marginally tested, especially when used out of context (i.e. without cloning the repository and syncing to a branch)


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)



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! ?

  • Like 2

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i have been tested with Spain and its more than perfect but at night there is no lights the scenery its too dark. is there any solution ? 

Edited by cobra66

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The best source for Canada is GO2.

I believe it is better than the ARC source that was tested in Yellowknife.

GO2 has a few clouds scattered in remote locations, but they are unlikely to be noticeable when flying enroute.

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Hong Kong
[GO2]
Clouds: 100%
Color Match: 90%
ZL: Tested 17 100%

Don't even bother to try other sources, Google is the only good source for Hong Kong. 
I wasted 2 hours downloading from Bing just to realize all images are covered with white clouds ?

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Sweden
Hitta
Clouds: 100% (As far as I'm aware, have done most of central Sweden and along the coast up north to Kiruna)
Color Match: 95% (Mostly it's excellent, but this is prone to happen somewhat more often up north).
ZL: 15-18=100%

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