Posts by vogel69

    WOW !

    I have been off during the past few months and only realize today that I had missed this announcement. =O

    I am really very happy with the formalization of this new "future" scenery that Antoine had teased us a few months ago ;).

    Not only because of the beauty of these screenshots but especially because I am a fan of FranceVFR's work that I know from P3D and FSX. And I especially have an idea what is behind .... I know that their scenery are very well produced and at all levels, both the quality of the mesh, the work on the ground photo (colors, accuracy, homogeneity) , their 3D building generation engine is breathtaking and above all already very well tested and optimized because designed for very constraining simulator like fsx, without forgetting the work on vegetation placed with precision and surprisingly realistic!

    One of my only regrets since my passage to VR and therefore AFS2, it was not being able to benefit from their work on AFS2 ... Recently I had a lot of frustration to see that my region: Rhone-Alpes was out for P3D and not being able to take advantage of it in VR ;(

    But know my hope is reborn with this announcement :D


    Kind regards, Michael


    - Are Sentinal data available all over the world?

    Yes, of course have a look here:

    informations here:

    data server like USGS:

    an dedicated Imagery server:

    a special cloudless server:


    - How did you process them?

    hummmmm.... may be a bit long to explain but to summarize I proceeded in two different ways:

    1- Manual method, I take the example of Saint Lucia, I downloaded the same tile Level2A True color (copericnus server: search for Mission Sentinel 2, Product Type: S2MSI2A --> for each tiles clic on "eyes" and Download TCI) which covers the islands on 3 different dates (by choosing dates of the same season with as little cloud as possible). I converted them to Tiff and reprojected them. Then in photoshop I loaded them into a layer each. Then, I erase each cloud by hand, hoping that on the image below there was no cloud ... And after that is the usual treatment to end with geoconverter.

    2- Method nag, for the island of Cuba for example, I downloaded directly the data of EOX cloudless server + usual treatment and geoconverter.


    As far as I understand, AeroScenery does not permit them as input at present.

    Yes true :( unfortunately, the method remains complicated ... But maybe Nico's could add the EOX Cloudless server in a future version... But I'm not sure that so many people are interested to those low res data :/


    I was pleasantly surprised when I discovered the data from the European Satellite Mission: Sentinel 2. This satellite imagery is sure at low resolution compared to Google data or bing -> only 10m/pixel, but it has several advantages:

    - First, not least is that these data are clearly free to access and use (Creative Commons).

    - Second, these data are very homogeneous in color and at good quality.

    - Third, all data are represented and therefore the sea is not cut to the bottom of the odds and all the shallow waters are visible even very off the coast.

    - Finally, the last advantage that I I discovered later that thanks to their redundancy (about 1 pass every 5 days) it is possible to clean the clouds quite efficiently. The principle in summary consists in superimposing different pass as layer in photoshop, which allows to clear cloud on a layer and missing part will be replaced by the layer of the bottom, etc. in the end, if you spend a little time, except in a very cloudy region you can get an almost cloudless picture. Later, I discovered that there were also utilities with algorithm to do the work alone but most of the time it is less precise work and it feels a lot in the final rendering. so reserve it therefore only to treat very large areas.

    In order to try to the use of these sentinel 2 data, I decided to treat some of the Caribbean, the goal was to connect Florida to my scene in Martinique to allow a pleasant transit to the eye between two area ;)

    After a lot of tests and manual work I am rather satisfied with the result. I completed the Elevation part with the ALOS World 3D 30m data also in open-data (

    Attached are some animated gif with comparative in game screenshot :

    Basic Photo Cover / Base Mesh <-> Cover Photo Sentinel 2 / Mesh ALOS

    If it interests some, I would to try to pack all this and put it available on :/

    To improve all this it would be interesting to know if it is not possible to use these basic data (resolution 10m) and to couple them with higher resolution aerial data (1 or 2 meter / p) in order to be able to take advantage of the color homogeneity of sentinel2 data and the accuracy of the high-resolution aerial data ... I know that there is this type of processing for satellite data in order to couple satellite low resolution colorimetric data with a panchromatic band which stores only high resolution data this is called pansharpening but after some tests I have not yet managed to transpose this for sentinel data 2. To be continued ...

    oh shit. Now my cultivation tool is not working with your grids anymore because you changed the BoundingBox format. :/

    Need to change my code now. Well, weekend.

    sorry for inconvenience :(

    I observed that, too. I only detected it when saving to another place and then exchanging the file. Are we supposed to understand that...?

    Kind regards, Michael

    not understand... but support it until i fix it ;)

    Hi turman,

    I'm pretty sure I came across a discussion on another forum about this subject of a script to import the heights of OSM data buildings about the city of Nice. It was a few years ago and it was in French if I remember correctly. I found this discussion particularly interesting at this time because I was looking for how to add building height data to my sources for creation of a more realistic autogen building. The DTM and DSM data comparison is a very good idea and surely allows to have an accurate result but I quickly stumbled on the lack of open data enough precise to be able to launch the work. Height accuracy needed to create a scenery for a simulator is not as demanding as adding this info to the global OSM data. So I imagined other possibilities...

    First idea, in the case where we only have a DSM sufficiently precise, the idea was to take the measure of several points taken randomly into cadastral polygon from OSM or cadastral data and keep the highest point then compare with the height data taken on several randomly chosen points around the same polygon and keep the lowest. so for each building I could theoretically recover the height (difference between max and min) and the altitude of its base (min). Working directly on a DSM raster it's not so hard to write a script to do that but there is always the problem of lack of sources. To overcome this lack, I thought to exploit the data of google-earth in areas covered by photogrametrie. Exploiting data from a hight number of points in GE is theoretically possible. A hight resolution DSM raster of an area could be generated like this. put aside the complexity of implementation, slowness of measurement, view deformation at high zoom, problem is that these data are not open because processing from protected by the copyright data.

    My other idea that I finally used for Martinique is much less accurate but already help to reinforce realism and buildings variety. Idea was exploiting roofs color of buildings. With Raster's functions of scenproc It is possible to add to the average color of each polygon so of each building. Sure there is a lot of imprecision and errors linked to ground photo quality, projected shadows, imagery & vector shifting but it helps to give variety., For residential areas, when I had rather red, blue or green roofs, it derived from simple homes (1 or 2 level) and when I had gray roofs, it crowded this with other data (type: residence, commercial, building area, etc.) I could try to vary the height of buildings for a start in realism...