I want to create a noise map with measured point data. But I want to have a planar representation, so I need an interpolation method.

Which one is the 'best' for measured noise data?

I prefer 'IDW' interpolation, but I am not sure about that. Any ideas?

  • it´s for my master thesis too! i´m measuring noise with a gauge and with my smartphone (special noise measure app) and I want to find out, if the smartphone app is a good alternative way to measure noise, so I want to compare the measured data so the results of the interpolation must not be very exactly or correctly, it only should give an overview for the following interpretations first, will try the spline method and then the IDW, and then I think I will choose the interpolation method, which looks more realistic to me thanks for all the answers so far! – user28840 Apr 5 '14 at 17:27
  • Please use the edit link on your question to add additional information. The Post Answer button should be used only for complete answers to the question. – PolyGeo Aug 16 '14 at 3:15

Noise is much more complex than a simple IDW interpolation. Sound propagation depends on many factors and distance is just one of them. Air density, temperature, humidity, terrain, wind direction and ground attenuation should all play their part in even the simplest of models. In addition to these simple factors there are issues relating to tonality of the noise source and octave spreading. Add to this the fact that noise is effected by refraction and reflection, so frequently does not travel in a straight line.

Also remember that perception of noise is highly subjective and non-linear (the latter point being why the dB scale is logarithmic and not linear - that's the way the human ear works). So perception at night and in the day are two very different things for the same sound power level. So, even having derived a number on a map, it must still be interpreted to have any meaning.

That said, you still need a pragmatic approach to noise calculation. So, I would strongly advise you to read up on noise calculations. You can start by having a look at the Institute of Acoustics Best Practice Guide to the Application of ESTSU-R-97 For the Assessment And Rating Of Wind Turbine Noise. Of course, this is noise from a wind turbine perspective but it is a starting point. I would then go on to read some more about the controversy surrounding the ESTSU-R-97 guidance. The Wind turbine noise propagation model is based on the ISO-9613-2 standard, which describes a general method for attenuation of sound during outdoor propagation. As such this is essential reading and following the ISO standard will at least give you credibility and a rationale for your calculations.

The wind industry has specialist tools for doing even simple (simplistic?) calculations of noise propagation. Some of these could take the sting out of what you are trying to do. If you are doing the noise calculation for wind turbines, then I would recommend you use one of these tools (e.g. OpenWind - which has a free version) and then, which ever side of the debate you are one, your results will be acceptable (or at least undissmissably in line with best practice, which is a different thing). If you are not calculating for wind turbines but for some other point source, then you may be able to bend the wind farm software to your will.

  • I'm not an expert, but I was playing with SPreAD a while ago and found it interesting. It's an ArcGIS 9.x python toolbox advertised as "open source". It can be requested here. Have you ever seen or used it before? – SaultDon Apr 4 '14 at 16:00
  • I must admit that I haven't used SPreAD as I usually have a wind farm package to hand and that's where most of my noise calculations are focused. However, I looked at the blurb and it seems very interesting (not least because it is free) and accounts for a lot of effects such as up and down-wind losses, terrain, etc. When time permits, I must compare the output to my usual tools. Thanks for the heads-up. – MappaGnosis Apr 4 '14 at 16:13
  • I've got time this weekend, going to be converting the scripts to GRASS equivalents. – SaultDon Apr 4 '14 at 16:41
  • Excellent - I think it would be valuable to report back what you find between the tools. – MappaGnosis Apr 4 '14 at 19:33

For my masters thesis I ran a comparison of interpolation methods for interpolating elevation maps from LiDAR clouds, and in almost all scenarios thin plate spline interpolation was the most accurate method. IDW is good in some situations but it's quite primitive. If you're dealing with continuous data types (as opposed to categorical data types), which I assume you are if you're dealing with noise data, you might also get good results with spline.

If you are using ArcGIS, I believe spline interpolation is included in the geostatistical analyst toolset.


Assuming you're measuring sound intensity, it decreases by distance squared so I think IDW with a power of 2 is the only appropriate way to do it.

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