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I'd like to densify a point layer to get a better spatial distribution. With "better" I mean homogeneous distributed. If I had to quantified my improvement, I would calculate the voronoi diagram and after the densification the areas had to be under a special threshold.

Is there an algorithms/tool to do my task. Doesn't matter of ArcGIS, QGIS or Python. I thinks thats a common problem of sensor networks.

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    Can you explain a bit more what you mean by homogenous distributed?
    – John Powell
    Apr 17 '16 at 12:04
  • Homogenious = the Areas of the single Voronoi Polygons below a max threshold, doesn't mean that it has to be in a grid order.
    – CanadaRunner
    Apr 17 '16 at 14:59
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    So you want more data to fill in the holes to improve the quality of the collected data? The only way I know is to collect more data. If you start interpolating, you'll be asserting a precision which does not exist.
    – Vince
    Apr 17 '16 at 15:26
  • I guess you can run proximity analysis on existing points, merge polygons over the limit and try to fit new points inside using something like gis.stackexchange.com/questions/185889/…
    – FelixIP
    Apr 17 '16 at 20:47
  • Please choose which of QGIS, Python and ArcGIS Desktop you wish to ask about in this question, and tell us precisely what you have tried with that product. Otherwise you are effectively asking three questions which goes against the Tour.
    – PolyGeo ♦
    Jan 25 '17 at 9:59