-
Notifications
You must be signed in to change notification settings - Fork 190
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Use kriging with external drift to interpolate temperature #155
Comments
I can give you a short survey:
If your DEM data is grided and you don't have the elevation data at your target points, you should use external Z drift otherwise use specified drift. Does that help? Cheers, Sebastian |
Thanks, it helps a lot. I've figured out. |
Cool! Don't forget to cite PyKrige ;-) |
Sorry for reviving this old thread but just to make sure I understand... UniversalKriging(
x,
y,
z,
drift_terms=['external_Z','specified_drift'],
external_drift=hi,
external_drift_x=lon,
external_drift_y=lat,
specified_drift=h
) right? |
Hello! I am trying to krig with external drift. I am using the following setup.
I thought this was the correct way to set up to krig with external drift, but I received the following error.
Im currently using pykrig version 1.6.1 I'm not sure what I'm doing wrong. Any help is greatly appreciated :) |
I'm trying to interpolate temperature data with DEM data and kriging with external drift is suggested. The documentation lists several drift terms (‘regional_linear’, ‘point_log’, ‘external_Z’, ‘specified’, and ‘functional’) but I don't know what's the difference and which to use since I'm new to kriging method. Most tutorials about kriging I've read just throw equations and I couldn't relate them to "drift terms". Could someone give me a clue?
The text was updated successfully, but these errors were encountered: