Hello, It is my experience that, for a given data set, the impact of secondary information is usually more pronounced when using KED (kriging with external drift) or SKLM (simple kriging with local means) instead of cokriging. Several factors will control the relative influence of secondary information in cokriging, namely the correlation coefficient, sampling intensity, and relative nugget effect of primary versus secondary variables. As I showed in my book, if the primary variable has a much larger nugget effect than the secondary variable and the two are well correlated, the secondary data may screen the influence of primary data. Try to play with these parameters and see what would be the impact on the final map. Although a detailed map might appear more desirable or "better" at first glance, beware that the impact of your DEM can be overestimated by some techniques and you might end up getting better re-estimation results for the smooth map.
KED could be performed using the program kt3d in Gslib. Hope it helps, Pierre <><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><> Dr. Pierre Goovaerts Consultant in (Geo)statistics President of PGeostat, LLC and Senior Chief Scientist with Biomedware Inc. 710 Ridgemont Lane Ann Arbor, Michigan, 48103-1535, U.S.A. E-mail: [EMAIL PROTECTED] Phone: (734) 668-9900 Fax: (734) 668-7788 http://alumni.engin.umich.edu/~goovaert/ <><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><> On Thu, 16 Jan 2003, Alvaro Silva wrote: > Hello > > Thanks to all that give me some help on the cokriging (Tom, Donald, Susan > and Tomislav). By reading Goovaerts (hello thanks for your course in Lisbon > last November) paper on precipitation estimation including elevation, I > notice that cokriging presents smooth surfaces, but I think this isn't > always true. I have tested it for the temperature estimation on Madeira > Island, and the maps show clearly a relation with altitude although for > Portugal mainland, i could not achieve yet this detail. I have tested the > Neural Networks with the same purpose and the resulting map for the annual > mean air temperature is very good, it captures fine details and presents > variability very well, also the r between observed and estimated values > with an independent dataset was very good (0.98). When I decided to test > also the cokriging to compare the results I was disapointed, because NN > presents a much better map. Now i try to understand why the CK doesn't give > results as good as I thought it could give. > I also would like to test kriging with external drift, does anyone know > where can I find a friendly and free software to do so, preferencially with > a tutorial. > > Thanks once again and with my best regards, > > �lvaro > > > > ---------- > Jos� �lvaro Mendes Pimp�o Alves Silva > Ge�grafo - T�cnico de SIG Geographer - GIS Technician > Departamento de Clima e Ambiente Atmosf�rico Climate Department > Instituto de Meteorologia Portuguese Meteorological Institute > > Rua C do Aeroporto > 1749 - 047 Lisboa > Portugal > > Tel: (+351) 218483961 > Fax: (+351) 218402370 > Email: [EMAIL PROTECTED] > > > > ---------- > > > -- * 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
