Global Mapper v24.0

Mismatching edges in DTM

Hello,

when generating my DTM I always notice mismatched lines. To be precise, these are edges in the terrain representation. The height difference is only minimal, but they are extremely emphasized by the representation. Does anyone know what causes these?Are there any suggestions for a solution?

Greetings



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Best Answer

  • DerrickW
    Accepted Answer

    Are you creating the terrain surface yourself?


    In public layers, like USGS 3DEP, lines like this often represent the boundary between a lidar flight and something like SRTM data (the 3DEP layer is a composite/mosaic with a lot of different data sources).

    Example:

    If you go and look on USGS' lidar portal website, you can view the footprint for the lidar collections that directly match what we're seeing here (data on the top of the mountains are from an unknown, lower-resolution surface).

    This is expected in datasets like this. There's some "tricks" to try to mask the seamlines, like re-sampling your surface to an appropriate grid with binning, or separating them and trying to do a vertical adjustment on one to better match into the other, but they will all have a tradeoff.


    If this is YOUR data, generated with lidar or photogrammetry, that's a workflow problem on your end that needs to be fixed before you even get to the point of using Global Mapper. From what I can tell, this looks a little bit like you're using drone-based lidar and the misalignment is happening between data collected from different flights/battery swaps? If that's true, you need to use surveyed ground control targets (don't rely on RTK alone). The control points are even more important in areas where you have separate flights.


    If survey targets aren't an option for you for one reason or another, you can create psuedo-control/PhotoID/Manual tie points. For instance, extract XYZ coordinates from your first flight at various points around the site (that are visually identifiable) and then use those to control your adjacent flights and match them into the first dataset. (In the future, you'd want to place something visible out BEFORE your flights and then use those to match your different datasets together)


    As an example, this is how I set up large UAS flights. Blue = Mapping extents, Red=UAS Flight boundary and the circles are where we will place ground control targets, which are especially important in the overlap areas between separate flights.

    These points are then marked in the processing software (Pix4d, in this case) in all of the datasets before finishing processing and bringing into global mapper.


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