<p>When talking about low-pass filtering spatial data, then the low frequency contributions are the large structures (the lower the frequency, the larger the structure), and the higher the smaller the structure.</p>
<p>For instance think of approximating the cross-section of a mountain with a sinoidal function (just one wavelength): then a small mountain would mean a higher frequency than a large mountain. Using this (de)composition of the topography allows to recreate any surface profile up to whatever detail level necessary. Technically you apply the <a href="https://en.wikipedia.org/wiki/Fourier_transform" rel="noreferrer">Fourier transform</a> to your data. For a low-pass filter you then throw away the higher frequencies, and subsequently apply the inverse Fourier transform to get back the smoothed data.</p>
<p>Of course you can apply this to any kind of data, not just topography, so for instance also to a 2D map of the gravity anomaly.</p>

CC BY-SA 4.0
2024-11-17T16:11:23.367Z
As a general rule, when I answer a good question (and this is a good question), I **always** upvote the question. We need more good questions at this site. There's only one upvote on the question right now, and it is mine. I suggest you add your upvote to my upvote.
David Hammen
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2024-11-17T17:03:31.593Z
You have a point.
planetmaker
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2024-11-17T19:46:45.873Z
thanks so much!
antonio
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2024-11-18T08:23:16.750Z
I agree with @DavidHammen, vote early and vote often! https://earthscience.meta.stackexchange.com/questions/27/vote-early-and-vote-often
Jean-Marie Prival
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2024-11-17T15:44:50.647Z
2024-11-17T15:44:50.647Z
planetmaker
<p>I'm a master's student in geology, I wanted to ask a little more about gravimetric anomalies and low-pass filters. The question is this: If I want to isolate a local gravimetric anomaly from the regional gravimetric contribution, can I use a low-pass filter or vice versa? I know that low-pass filters cancel out high frequencies, but does a localized gravimetric anomaly have higher or lower frequencies than a more extended gravimetric anomaly?</p>

<geology><geophysics>
low-pass filters and gravimetric anomalies
antonio
# low-pass filters and gravimetric anomalies

(Asked by: username_0 on 2024-11-17)

I'm a master's student in geology, I wanted to ask a little more about gravimetric anomalies and low-pass filters. The question is this: If I want to isolate a local gravimetric anomaly from the regional gravimetric contribution, can I use a low-pass filter or vice versa? I know that low-pass filters cancel out high frequencies, but does a localized gravimetric anomaly have higher or lower frequencies than a more extended gravimetric anomaly?

**Tags:** geology, geophysics


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## 1 answers

### Answer by username_1 on 2024-11-17. Score: 6

When talking about low-pass filtering spatial data, then the low frequency contributions are the large structures (the lower the frequency, the larger the structure), and the higher the smaller the structure.

For instance think of approximating the cross-section of a mountain with a sinoidal function (just one wavelength): then a small mountain would mean a higher frequency than a large mountain. Using this (de)composition of the topography allows to recreate any surface profile up to whatever detail level necessary. Technically you apply the [Fourier transform](https://en.wikipedia.org/wiki/Fourier_transform) to your data. For a low-pass filter you then throw away the higher frequencies, and subsequently apply the inverse Fourier transform to get back the smoothed data.

Of course you can apply this to any kind of data, not just topography, so for instance also to a 2D map of the gravity anomaly.

> **Comments:**
> **username_2**: As a general rule, when I answer a good question (and this is a good question), I **always** upvote the question. We need more good questions at this site. There's only one upvote on the question right now, and it is mine. I suggest you add your upvote to my upvote.  
> **username_1**: You have a point.  
> **username_0**: thanks so much!  
> **username_3**: I agree with @username_2, vote early and vote often! https://earthscience.meta.stackexchange.com/questions/27/vote-early-and-vote-often  

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