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Re: AI-GEOSTATS: forests on slopes

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  • Patrick van Laake
    ... Remco, I suggest you browse to the website of the EROS Data Center of the USGS. There you can pick up GTOPO30, a 30 arc-second DEM from which you can
    Message 1 of 4 , Dec 4, 2000
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      remko duursma wrote:

      > Dear listmembers,
      >
      > I have a question:
      >
      > "How much of the world's forests are located on slopes greater than 10%?"

      > Ideally, an answer would consist of a frequency distribution of forests by slope class.
      >

      Remco,

      I suggest you browse to the website of the EROS Data Center of the USGS. There you can pick up GTOPO30, a 30 arc-second DEM from which you can extract slope. While you are there, you can pick up the SLCR (for
      Seasonal Land Cover Region) data set which indicates different forest types a.o. land use classes. Both data sets are global and have a cell size of about 1km.

      With this data (and the right GIS software) you can yourself derive statistics for any slope class, slice, correlate with other data sets, differentiate by continent, ecoregion, forest type, and many more things.

      Much more fun doing it yourself than just getting a frequency distribution.

      Enjoy,
      Patrick van Laake

      >
      > Thanks,
      >
      > Remko Duursma
      >
      > Ph.D. student
      > Department of Forest Resources
      > University of Idaho


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    • Chuck Ehlschlaeger
      ... Before you spend time downloading files, you should ask yourself the following questions: 1) What is MY definition of slope? Do you want to use slope
      Message 2 of 4 , Dec 4, 2000
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        >> "How much of the world's forests are located on slopes greater than 10%?"
        >
        >
        >> Ideally, an answer would consist of a frequency distribution of forests by slope class.
        >>
        >
        > I suggest you browse to the website of the EROS Data Center of the USGS. There you can pick up GTOPO30, a 30 arc-second DEM from which you can extract slope. While you are there, you can pick up the SLCR (for
        > Seasonal Land Cover Region) data set which indicates different forest types a.o. land use classes. Both data sets are global and have a cell size of about 1km.
        >
        > With this data (and the right GIS software) you can yourself derive statistics for any slope class, slice, correlate with other data sets, differentiate by continent, ecoregion, forest type, and many more things.
        >

        Before you spend time downloading files, you should ask yourself the
        following questions:

        1) What is MY definition of slope?

        Do you want to use slope values of land that has been aggregrated to 30
        arc seconds? At the equator, 30 arc seconds is about

        111km 1deg 1min 30sec 2
        ----- * ----- * ----- * ----- = .925km
        1deg 60min 60sec


        The slope values of 30 arc second data will be vastly different than 3
        arc second data, which is different than the slope values at 30m data.
        One of my cartography exercises is to have my students download a 7.5'
        DEM and do a slope analysis (at 30m resolution). They then do a slope
        analysis with the same data aggregated to 60m. There is always a difference.

        2) What is MY definition of forest?

        The Modifiable Areal Unit Problem (which I provided an example of
        earlier in this email) also exists for question 2. A 30 arc second
        square cell called forest is likely not to be the same thing as a 3 arc
        second cell called forest.

        In summary, find or build the data that will answer the question. Don't
        use whatever data is available.

        sincerely, chuck

        PS. If you are interested in using geostatistics to represent the
        uncertainty of overly generalized data on applications, the following
        articles might be of interest:

        "Representing Uncertainty of Area Class Maps with a Correlated Inter-Map
        Cell Swapping Heuristic," by Charles R. Ehlschlaeger. Submitted to
        Computers, Environment, and Urban Systems on May 5, 1999, accepted
        January 20, 2000. Published Vol. 24, No 5, pp 451-69. URL:
        http://geography.hunter.cuny.edu/~chuck/urban/urban.html.

        "Visualizing Spatial Data Uncertainty Using Animation," by Charles R.
        Ehlschlaeger, Ashton M. Shortridge, and Michael F. Goodchild. Submitted
        to Computers in GeoSciences in September, 1996. Accepted October, 1996.
        Published Vol. 23, No 4, 1997, and at URL:
        http://geography.hunter.cuny.edu/~chuck/CGFinal/paper.htm and
        http://www.elsevier.nl/locate/cgvis/

        --
        Chuck Ehlschlaeger 212-772-5321
        Dep. of Geography fax: 914-407-2029
        Hunter College chuckre@...
        695 Park Ave. secure: chuckre@...
        New York, NY 10021 http://geography.hunter.cuny.edu/~chuck/

        "Everybody is in favor of the First Amendment, but we'd have a hell
        of a time ratifying it today." Senator (VT) Patrick J. Leahy


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      • Patrick van Laake
        ... Chuck, I completely agree with you. Too many people already use data that is not suitable for the kind of analysis they are trying to perform, either
        Message 3 of 4 , Dec 5, 2000
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          Chuck Ehlschlaeger wrote:

          > >> "How much of the world's forests are located on slopes greater than 10%?"
          > >
          > >
          > >> Ideally, an answer would consist of a frequency distribution of forests by slope class.
          > >>
          > >
          > > I suggest you browse to the website of the EROS Data Center of the USGS. There you can pick up GTOPO30, a 30 arc-second DEM from which you can extract slope. While you are there, you can pick up the SLCR (for
          > > Seasonal Land Cover Region) data set which indicates different forest types a.o. land use classes. Both data sets are global and have a cell size of about 1km.
          > >
          > > With this data (and the right GIS software) you can yourself derive statistics for any slope class, slice, correlate with other data sets, differentiate by continent, ecoregion, forest type, and many more things.
          > >
          >
          > Before you spend time downloading files, you should ask yourself the
          > following questions:
          >
          > 1) What is MY definition of slope?
          >
          >
          > 2) What is MY definition of forest?
          >
          >
          > In summary, find or build the data that will answer the question. Don't
          > use whatever data is available.
          >

          Chuck, I completely agree with you. Too many people already use data that is not suitable for the kind of analysis they are trying to perform, either because there is no better data, but more likely so because they do
          not know how to evaluate improperly documented data and therefore know no better.

          Remco's question, however, explicitly stated global coverage. Apart from the computational limitations in choosing a finer granularity of the data, there are two reasons why I so casually mentioned these two data
          sets:

          * They are the best data sets available with "uniform" global characteristics (GTOPO30 is actually constructed from many different sources with varying degrees of fidelity). For instance, both data sets are being used
          by the Food and Agriculture Organization of the UN to construct their Forest Resources Assessment 2000 analysis, if that is any indication.

          * At a global scale the problem generalization and data aggregation that are generally applied do not merit or even support using better data. Remco's request for a frequency distribution to me seems coincident with
          this.

          Still, the call on using this data is Remco's.

          Regards,
          Patrick


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