RES: AI-GEOSTATS: Dealing with Universal Kriging
Thanks you all for your contributions. Rubens -- * To post a message to the list, send it to [EMAIL PROTECTED] * As a general service to the users, please remember to post a summary of any useful responses to your questions. * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list * Support to the list is provided at http://www.ai-geostats.org
RE: AI-GEOSTATS: Dealing with Universal Kriging
Alessandro Thanks for the contribution. If Universal Kriging is applied, there is no need for simulation or multi-indicator approaches to get a standard error, it comes with the solution. Isobel __ Do You Yahoo!? Everything you'll ever need on one web page from News and Sport to Email and Music Charts http://uk.my.yahoo.com -- * To post a message to the list, send it to [EMAIL PROTECTED] * As a general service to the users, please remember to post a summary of any useful responses to your questions. * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list * Support to the list is provided at http://www.ai-geostats.org
Re: AI-GEOSTATS: Dealing with Universal Kriging
Rubens Your approach has been long used in hydrology and similar fields with much success. The problem with the standard deviation is that it does not include the the 'error' on the estimation of the true drift. To get a composite error you would either have to (a) add your kriging variance to some sort of classical regression variance to get a composite one; (b) use a Universal Kriging (or generalised covariance) approach to estimate the surface with the drift included. In our experience, your estimated surface will not change but your kriging variances will increase slightly. Isobel Clark __ Do You Yahoo!? Everything you'll ever need on one web page from News and Sport to Email and Music Charts http://uk.my.yahoo.com -- * To post a message to the list, send it to [EMAIL PROTECTED] * As a general service to the users, please remember to post a summary of any useful responses to your questions. * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list * Support to the list is provided at http://www.ai-geostats.org
AI-GEOSTATS: Dealing with Universal Kriging
Dear all, We are trying to apply Universal Kriging to “High Plains” Aquifer in Kansas (OLEA, 1999) for land surface elevation (LSE), using its 317 data points. The purpose of this application is just for didactic ends. Our first step was to filter a prominent 1st degree drift. The way we did it was using Surfer 8.0 (Golden Software) and obtaining the residuals, in such way that summing the residuals by the 1st degree trend we obtain the original data. Obviously the values of this new variable (residuals of LSE, i.e., RLSE) are much lower than the original one. Calculating the experimental variogram, modeling it and kriging the variable is possible to obtain the RLSE (residuals of land surface elevation) map. Summing this map to the drift (calculated in a deterministic way) we obtain a map that we suppose that represents a map for the original variable (LSE). But what about the standard deviation? We did a little test and it seems that the standard deviation map for the residuals (RLSE) represents the std. dev. map for the original variable (LSE). Is this a correct conclusion and procedure? If we have less data, will it work? If we use a 2nd degree drift the standard deviation could be wrong? Thanks for your attention, Rubens == Rubens Caldeira Monteiro # ICQ 106157533 São Paulo State University at Rio Claro - UNESP/Rio Claro – PhD candidate on Geosciences & Environmental Sci. São Paulo University at Piracicaba - ESALQ-USP/Piracicaba – Undergrad. on Environmental Management University of North Carolina at Chapel Hill - UNC-CH URL: http://www.unc.edu/~rubenscm/CASEhome.html
