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I have a dataset which contains location and signal strength data from a field survey for a radio project I'm working on. An example:

lat,      lon,      signal
34.123,  -89.123,  55
34.124,  -89.124,  50
34.125,  -89.125,  36

Of note: the data doesn't fully cover the region it's collected from, because the signal strength is collected at the base station. When the mobile unit can't contact the base, there's no data.

So, the visualization I'm looking for is a sort of combination heatmap and interpolation—the visualization should fade out when there are no points in a given location, like a heatmap, but its color should be determined by the value of the collected points, like an interpolation.

How can I accomplish this?

Fishbreath
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2 Answers2

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I was able to accomplish what I wanted to do, albeit imperfectly, by just using larger dots in the layer style and rendering with an additive Gaussian blur.

RF survey

To add that blur, I did the following (QGIS 3.10):

process part 1

  1. Set the symbol size to however large you want the blur footprint to be. (I chose 10mm).
  2. Expand the Layer Rendering section.
  3. Tick 'draw effects'.
  4. Use the star button to the right to open the effects dialog.

process part 2

  1. Add a Blur effect.
  2. Set the blur strength to a large proportion of the symbol size. (I went with 7.5mm, 75% of my dot size.) Play with opacity and blend mode until you obtain a visually pleasing result.
Fishbreath
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I think that you need to use a distance based interpolation method (IDW) with a strong power decay, so that the values fade quickly within your no_data regions. Then, it is a simple heatmap and the color ramp should be based on the interpolated values.

Nick Pucino
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  • I haven't been able to come up with settings in QGIS that yield decay to 0 over a wide region. Most of them don't even decay below the minimum signal in the dataset. – Fishbreath Feb 14 '20 at 02:39
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    See here: https://gis.stackexchange.com/questions/78542/picking-coefficient-in-inverse-distance-weighted-method-of-qgis , it looks like in Qgis the classical notion of power decay is inverted, so that a small coadfficient in the IDW function means stronger decay. Have you tried with the minimum coefficient values?? – Nick Pucino Feb 14 '20 at 04:35