Maybe, in order to have a quick and "safe" interpolation, the natural neighbor method of Dave Watson could perfom better than TIN. Sebastiano Trevisani
Quoting Gregoire Dubois <[EMAIL PROTECTED]>: > Dear list, > > I would appreciate feedback on an issue that is closely related to > SIC2004 > > Let us consider a variable (air pollutants, radioactivity) that is > measured at regular time intervals by an automatic monitoring network > that is structured like a regular grid. In the case one needs maps to be > generated on a regular basis, I was wondering what arguments would be > against the use of Triangulated Irregular Networks (or any simple linear > interpolation algorithm)? As a matter of fact, if TIN cannot be used to > assess uncertainties, it can be easily automated and it is an exact > interpolator (no risk to smooth out critical values). I thus understand > TIN is the most reasonable approach in the case one has a network that > is dense enough. Obviously, the "dense enough" obviously needs to be > defined properly as I expect it to be the main parameter that will > define the need for more advanced interpolation techniques. But with the > exception of density, are there any non obvious issues I am missing > here? > > Thank you in advance for any feedback. > > Best regards, > > Gregoire > > ------------------------------------------------- This mail sent through IMP: webmail.unipd.it
* By using the ai-geostats mailing list you agree to follow its rules ( see http://www.ai-geostats.org/help_ai-geostats.htm ) * To unsubscribe to ai-geostats, send the following in the subject or in the body (plain text format) of an email message to [EMAIL PROTECTED] Signoff ai-geostats
