I have a DEM with small pixels (500x500), and a bigger grid with temperatures (7x4). What I do is that I take the value for every red point (see figure), and impose that every point of my DEM in the same big square has the value of its corresponding red point. ![enter image description here]()
However, I do not like this interpolation, and I would like to have something more diffuse.
This is what I wanted to do:
- Take a point (pink one for example)
- Use Inverse Distance Weighting to calculate the value from the 4 nearest neighbors
![enter image description here]()
The issue is that I have to do that for 250 000 points, 15000 times !! I was trying to use IDW from PyGEM (without success, https://mathlab.github.io/PyGeM/_modules/pygem/idw.html). However I read that this is not recommended for a lot of points.
Is there an alternative to IDW from PyGEM to tackle this issue ?
I read this post (Inverse Distance Weighted (IDW) Interpolation with Python) but it was written in 2010 and I wanted to see if there has been any improvements since.
