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AI-GEOSTATS: interpolation question - chicken or the egg?

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  • RICK GRAY
    Hello Geostats list. I m a newcomer here - I was just referred to this list from someone on the GISList. They suggested someone here might be able to help me
    Message 1 of 3 , May 12, 2003
      Hello Geostats list. I'm a newcomer here - I was just referred to this list from someone on the GISList. They suggested someone here might be able to help me with the following (copied from my original post to that list).

      We collect weather data at a number of locations, run the data through computer models to predict a Disease Severity Value (DSV) for various crops based on temperature and hours that the leaves are wet (dew, rain, etc.), then interpolate the DSVs to generate a map that farmers can use to ascertain the best time to spray their crop. Farmers who subscribe to our service are given the DSV for their farm, as it is extracted from the interpolated map.

      We have long pondered, but not had the time to experiment, as to whether interpolating DSV's is actually better than interpolating the weather data, THEN finding the DSV.

      In other words, which way should generate the more reliable results? In the first instance, all the modelling is done with known values, so on first glance it would seem to provide truest values. On the other hand, interpolating the weather parameters, then running the model at the farmer's location, might be just as good - and offers some advantages as we attempt to automate the process. We just don't know.

      Has anybody looked into this? Know of any papers, etc. on the topic? Or even have some strong intuitions? I'd love to hear your feedback.

      Thanks,


      Rick Gray
      GIS Specialist, Ontario Weather Network
      http://www.ownweb.ca
      Ridgetown College, University of Guelph
      http://www.ridgetowncollege.com/

      Tel. 519-674-1554
      E-mail: rgray@...

      Ridgetown: -81.883 W, 42.450 N


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    • Pierre Goovaerts
      Hi Rick, There are several reasons why I would first run the model, then interpolate the results: 1. you don t have to propagate the uncertainty attached to
      Message 2 of 3 , May 14, 2003
        Hi Rick,

        There are several reasons why I would first run the
        model, then interpolate the results:
        1. you don't have to propagate the uncertainty attached
        to your input parameters since you work with actual
        observations.
        2. you have to model the semivariograms of only the
        output variable and perform a single kriging.


        Regards,

        Pierre Goovaerts
        <><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><>

        Dr. Pierre Goovaerts
        President of PGeostat, LLC
        Chief Scientist with Biomedware Inc.
        710 Ridgemont Lane
        Ann Arbor, Michigan, 48103-1535, U.S.A.

        E-mail: goovaert@...
        Phone: (734) 668-9900
        Fax: (734) 668-7788
        http://alumni.engin.umich.edu/~goovaert/

        <><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><>

        On Mon, 12 May 2003, RICK GRAY wrote:

        > Hello Geostats list. I'm a newcomer here - I was just referred to this list from someone on the GISList. They suggested someone here might be able to help me with the following (copied from my original post to that list).
        >
        > We collect weather data at a number of locations, run the data through computer models to predict a Disease Severity Value (DSV) for various crops based on temperature and hours that the leaves are wet (dew, rain, etc.), then interpolate the DSVs to generate a map that farmers can use to ascertain the best time to spray their crop. Farmers who subscribe to our service are given the DSV for their farm, as it is extracted from the interpolated map.
        >
        > We have long pondered, but not had the time to experiment, as to whether interpolating DSV's is actually better than interpolating the weather data, THEN finding the DSV.
        >
        > In other words, which way should generate the more reliable results? In the first instance, all the modelling is done with known values, so on first glance it would seem to provide truest values. On the other hand, interpolating the weather parameters, then running the model at the farmer's location, might be just as good - and offers some advantages as we attempt to automate the process. We just don't know.
        >
        > Has anybody looked into this? Know of any papers, etc. on the topic? Or even have some strong intuitions? I'd love to hear your feedback.
        >
        > Thanks,
        >
        >
        > Rick Gray
        > GIS Specialist, Ontario Weather Network
        > http://www.ownweb.ca
        > Ridgetown College, University of Guelph
        > http://www.ridgetowncollege.com/
        >
        > Tel. 519-674-1554
        > E-mail: rgray@...
        >
        > Ridgetown: -81.883 W, 42.450 N
        >
        >
        > --
        > * To post a message to the list, send it to ai-geostats@...
        > * 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 majordomo@... 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
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        >
        >



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      • Edzer J. Pebesma
        Rick, there are also several arguments to interpolate first, and model later. See the paper Gerard Heuvelink and I wrote: Spatial aggregation and soil process
        Message 3 of 3 , May 15, 2003
          Rick,

          there are also several arguments to interpolate first, and
          model later. See the paper Gerard Heuvelink and I wrote:
          "Spatial aggregation and soil process modelling", Geoderma
          89(1999),pp 47-65 for further information; PDF available from
          http://www.geog.uu.nl/~pebesma/

          Best regards,
          --
          Edzer

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