I forgot to Cc: to the list.. GD
From: Gregoire Dubois [mailto:[EMAIL PROTECTED] Sent: 01 July 2005 13:04 To: 'Els Verfaillie' Subject: RE: [ai-geostats] modelling trend and kriging type At first sight, I would say in all fields where you have a dominating physical/sociologigical phenomenon - that is obviously influencing the values of the variable of interest, - that is relatively stable in space and time, - that has generally a larger scale than the sampled area. In other words, one could expect to see applications of KED in all fields in which the spatio-temporal scale of observation is large. This mans in Geology (Mining & Petroleum engineering) rather than in mineralogy, in Meterology (only if you work one averaged values representing long periods of time) rather than micro-meteorology, Remote Sensing rather than photography , Epidemiology rather than Health Science, Soil sciences rather than ??? In other words, I expect a less frequent use of KED in fields where the phenomena are described for short period of times/for very small surfaces, that is simply said in situations where the trend may be more difficult to detect/understand...if you have any trend at all ! (e.g, daily rainfall, hourly atmospheric pollution levels , pollution levels measured far from the sources, the same variables observed over very small areas). An illustration may be useful: relief and elevation are known to have an impact on rainfall. These links are usually clear when analysing years of measurements, not if you analyse a few days of observations. The same is valid for spatial scales (rainfall measurements made at 100 locations over a small area on a hill will probably not show any trend). These are the first thoughts I have in mind. Thinking about possible use of KED in sociology and epidemiology, one can probably easily use trend detection as indicators for democracy and equality among people. Have a nice w-e ! Gregoire -----Original Message----- From: Els Verfaillie [mailto:[EMAIL PROTECTED] Sent: 01 July 2005 10:55 To: Pierre Goovaerts; Recep kantarci; ai-geostats@unil.ch Subject: RE: [ai-geostats] modelling trend and kriging type Dear AI-list, in which context KED is mostly used? I have found examples of this methodology in the context of soil science and climatology: Bourennane, H., King, D. and Couturier, A., 2000. Comparison of kriging with external drift and simple linear regression for predicting soil horizon thickness with different sample densities: Geoderma, v. 97, p. 255-271. Bourennane, H. and King, D., 2003. Using multiple external drifts to estimate a soil variable: Geoderma, v. 114, p. 1-18. Goovaerts, P., 1999. Using elevation to aid the geostatistical mapping of rainfall erosivity: Catena, v. 34, p. 227-242. Hudson, G. and Wackernagel, H., 1994. Mapping temperature using kriging with external drift: theory and an example from Scotland: International Journal of Climatology, v. 14, p. 77-91. Martinez-Cob, A. and Cuenca, R.H., 1992. Influence of elevation on regional evapotranspiration using multivariate geostatistics for various climatic regimes in Oregon. Journal of Hydrology 136, 353-380. Are there other interesting references for this methodology in the same or other application fields? Best wishes, ___________________________________________________ Els Verfaillie, PhD student Renard Centre of Marine Geology - Ghent University Krijgslaan 281-S8 B-9000 Gent - Belgium tel: +32-9-2644573 fax: +32-9-2644967 e-mail: [EMAIL PROTECTED] http://www.rcmg.ugent.be/ ___________________________________________________
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