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FW: [ai-geostats] modelling trend and kriging type

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  • Gregoire Dubois
    I forgot to Cc: to the list.. GD From: Gregoire Dubois [mailto:gregoire.dubois@jrc.it] Sent: 01 July 2005 13:04 To: Els Verfaillie Subject: RE: [ai-geostats]
    Message 1 of 1 , Jul 1, 2005
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      I forgot to Cc: to the list..


      From: Gregoire Dubois [mailto:gregoire.dubois@...]
      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 !


      -----Original Message-----
      From: Els Verfaillie [mailto:els.verfaillie@...]
      Sent: 01 July 2005 10:55
      To: Pierre Goovaerts; Recep kantarci; ai-geostats@...
      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.

      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: Els.Verfaillie@...
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