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Re: [ai-geostats] Frightened of Spatial Autocorrelation

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  • Koen Hufkens
    Some random remarks that went through my single braincell: I would focus on the physical environment to predict the locations, but it depends on what you call
    Message 1 of 10 , Sep 2, 2004
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      Some random remarks that went through my single braincell:

      I would focus on the physical environment to predict the locations, but
      it depends on what you call an archeological site.

      A part of the place where a settlement would be created, could be
      explained by the distance from the surrounding sites. But I would think
      of it as a marginal effect until pretty recent times.

      Why do I think this:

      - If you go way back, people where selfsubstaining living communities.
      So, if commerce wasn't that big a part of their life the distance to
      other villages wouldn't matter and the choices for starting a village
      would only be dominated by physical factors.

      - In recent times the distances could become more important because of
      trade and the fact that their were more people around, that would spread
      across the land to claim their part of a living community where there
      would be some "breathing" space. That "breathing" space could be your
      clue to finding more sites. But again only if the combination of the
      social factors (preventing overcrowding and the urge to claim your patch
      of land) and the biophysical ones were in favour of the people.

      No social pressure on a community = no need to resettle, bad land = no
      way someone is going to settle there (until recent times with better
      agricultural techniques).

      A case where your technique would work is a uniform type of soil and
      topography, where the (re-)settlement of people would only be dominated
      by social factors and not so much by biophysical ones. Look at maps of
      the champagne area in France (sorry, only example I could think of).

      So, depending on the timeframe your looking at my strategy would differ.
      On old settlements I wouldn't include the distance and focus more on
      detailed biophysical data like pollen data. For recent times the SA
      approach could be interesting, because of the social aspect, but I
      wouldn't let it dominate a prediction model. You could cross check it
      with a model without the distances and known sites with a leave one out
      methode to see how good it behaves. Anyway... have fun with it...

      Cheers,
      Koen.



      On Thu, 2004-09-02 at 21:43, Kevin M. Curtin wrote:
      > Hello All,
      >
      > I’m not sure if this is the correct forum for this…but a colleague has
      > asked a question I’d like to address.
      >
      >
      >
      > This fellow wants to predict the location of archaeological sites
      > based on factors such as soil type, proximity to a water source,
      > slope, AND proximity to other archaeological sites.
      >
      >
      >
      > On proposing such a predictive model he has been challenged with, “How
      > are you going to deal with Spatial Autocorrelation”. We’re not sure
      > why SA should be a problem since we are suggesting that spatial
      > proximity is a factor in settlement location.
      >
      >
      >
      > So, do we need to test for SA and why?
      >
      >
      >
      > Thanks in advance,
      >
      > Kevin
      >
      >
      >
      >
      >
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    • Isobel Clark
      Kevin Sounds like an ideal case for Geographically Weighted Regression. You could use semi-variograms or spatial auto-correlation to determine exactly how
      Message 2 of 10 , Sep 2, 2004
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        Kevin

        Sounds like an ideal case for Geographically Weighted
        Regression.

        You could use semi-variograms or spatial
        auto-correlation to determine exactly how proximity
        defines relationship. My only current beef with GWR is
        the seemingly pre-defined distance weighting
        functions. Not had much time to get into this yet, so
        don't dump on me all you experts out there.

        I would be interested in any published results on this
        as one of my business partners is doing similar work
        on bronze age denmark.

        Isobel
        http://uk.geocities.com/drisobelclark





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      • Steven Citron-Pousty
        You might look at the following series of papers: http://www.nceas.ucsb.edu/~liebhold/ecography/ While the papers are written with an ecological focus,
        Message 3 of 10 , Sep 2, 2004
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          You might look at the following series of papers:
          http://www.nceas.ucsb.edu/~liebhold/ecography/
          While the papers are written with an ecological focus, settling is
          settling is settling.
          Hope they help...
          Steve

          Isobel Clark wrote:

          >Kevin
          >
          >Sounds like an ideal case for Geographically Weighted
          >Regression.
          >
          >You could use semi-variograms or spatial
          >auto-correlation to determine exactly how proximity
          >defines relationship. My only current beef with GWR is
          >the seemingly pre-defined distance weighting
          >functions. Not had much time to get into this yet, so
          >don't dump on me all you experts out there.
          >
          >I would be interested in any published results on this
          >as one of my business partners is doing similar work
          >on bronze age denmark.
          >
          >Isobel
          >http://uk.geocities.com/drisobelclark
          >
          >
          >
          >
          >
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        • Beatrice Mare-Jones
          Hello Kevin You may like to speak to David Hansen a GIS Specialist/ Soil Scientist at the USGS in Sacramento - dhansen@mp.usbr.gov He has a good paper
          Message 4 of 10 , Sep 2, 2004
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            Hello Kevin

            You may like to speak to David Hansen a GIS Specialist/ Soil Scientist at
            the USGS in Sacramento - dhansen@...

            He has a good paper "Describing GIS Applications: Spatial Statistics and
            Weights of Evidence Extension to ArcView in the Analysis of the
            distribution of Archaeological Sites in Landscape. You may know this one -
            if not you can view it at www.goscafe.com?technical_papers/Papers/paper054

            Kind regards


            Beatrice





            "Kevin M. Curtin" <curtin@...>
            03/09/2004 07:43


            To: <ai-geostats@...>
            cc:
            Subject: [ai-geostats] Frightened of Spatial Autocorrelation


            Hello All,
            I'm not sure if this is the correct forum for this?but a colleague has
            asked a question I'd like to address.

            This fellow wants to predict the location of archaeological sites based on
            factors such as soil type, proximity to a water source, slope, AND
            proximity to other archaeological sites.

            On proposing such a predictive model he has been challenged with, "How are
            you going to deal with Spatial Autocorrelation". We're not sure why SA
            should be a problem since we are suggesting that spatial proximity is a
            factor in settlement location.

            So, do we need to test for SA and why?

            Thanks in advance,
            Kevin
            * By using the ai-geostats mailing list you agree to follow its rules
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          • sebastiano
            I think that a fuzzy logic system approach is well suited for you task Some book where you can find something Principle of Geographical information Systems
            Message 5 of 10 , Sep 3, 2004
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              I think that a fuzzy logic system approach is well suited for you task
              Some book where you can find something "Principle of Geographical information Systems" Burrough and MCdonnel
              and "Fuzzy Logic in Geology", Demicco (2004)
              Bye
              Sebastiano trevisani
               At 21.43 02/09/2004, you wrote:
              Hello All,
              I’m not sure if this is the correct forum for this…but a colleague has asked a question I’d like to address.
               
              This fellow wants to predict the location of archaeological sites based on factors such as soil type, proximity to a water source, slope, AND proximity to other archaeological sites.
               
              On proposing such a predictive model he has been challenged with, “How are you going to deal with Spatial Autocorrelation”. We’re not sure why SA should be a problem since we are suggesting that spatial proximity is a factor in settlement location.
               
              So, do we need to test for SA and why?
               
              Thanks in advance,
              Kevin
               
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            • Viktoras Didziulis
              Hello, Kevin ! Predictive interpolation is a very interesting field. You may be interested in GIS applications based on Dempster-Shafer Theory. There are some
              Message 6 of 10 , Sep 3, 2004
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                Hello, Kevin !

                Predictive interpolation is a very interesting field.

                You may be interested in GIS applications based on Dempster-Shafer Theory.
                There are some online material also linked to archeology and prediction of
                archaeological sites at http://gis.esri
                com/library/userconf/proc99/proceed/papers/pap295/p295.htm
                and http://websrv5.sdu.dk/ejstrud/forskning.html

                Also IDRISI GIS has a collection of useful modeling tools for multicriteria
                analysis. It is described in manual which can be downloaded from IDRISI web
                site...

                Another subject of interest might be various AI techniques. I personally am
                experimenting with Case Based Reasoning (spatial predictions of community
                structure). There are some references and an experimental module online at
                http://www.alleco.fi/allmaps
                Currently I am rewriting the code (for the third time already :)). Still, at
                least for me it looks promising. Although currently I came to a decision
                that these 'explicit' GIS modeling techniques must be suplemented with the
                implicit' ones based on cellular automation, nearest neighbourhood or
                variograms and krigging. The reason to think so is that those 'inteligent'
                methods predict ecological niches. But in real world those niches may remain
                unoccupied. So we need an interaction of explicit top-down influence in form
                of 'niches' and implicit bottom-up influence in the form of 'growth from a
                seed'.

                Best regards
                Viktoras

                -------Original Message-------

                From: Kevin M. Curtin
                Date: 2004 m. rugs�jis 02 d. 12:44:03
                To: ai-geostats@...
                Subject: [ai-geostats] Frightened of Spatial Autocorrelation

                Hello All,
                I�m not sure if this is the correct forum for this�but a colleague has asked
                a question I�d like to address.

                This fellow wants to predict the location of archaeological sites based on
                factors such as soil type, proximity to a water source, slope, AND proximity
                to other archaeological sites.

                On proposing such a predictive model he has been challenged with, �How are
                you going to deal with Spatial Autocorrelation�. We�re not sure why SA
                should be a problem since we are suggesting that spatial proximity is a
                factor in settlement location.

                So, do we need to test for SA and why?

                Thanks in advance,
                Kevin
              • Niels Chr. Nielsen
                Isobel, Kevin and others I would be very interested as well, since my collegue (an archaeologist) and myself (geographer) are doing work on Bronze Age Denmark,
                Message 7 of 10 , Sep 3, 2004
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                  Isobel, Kevin and others

                  I would be very interested as well, since my collegue (an archaeologist) and myself (geographer) are doing work on Bronze Age Denmark, in the landscape of Vendsyssel. See web site http://websrv5.sdu.dk/ejstrud/forskning.html
                  with paper http://websrv5.sdu.dk/ejstrud/forskning/GIS/ejstrud_wunsdorf_2001.pdf
                  and http://www.humaniora.sdu.dk/kulturmiljoe (mostly in Danish)

                  Niels


                  Isobel Clark wrote:
                  Kevin
                  
                  Sounds like an ideal case for Geographically Weighted
                  Regression. 
                  
                  You could use semi-variograms or spatial
                  auto-correlation to determine exactly how proximity
                  defines relationship. My only current beef with GWR is
                  the seemingly pre-defined distance weighting
                  functions. Not had much time to get into this yet, so
                  don't dump on me all you experts out there.
                  
                  I would be interested in any published results on this
                  as one of my business partners is doing similar work
                  on bronze age denmark.
                  
                  Isobel
                  http://uk.geocities.com/drisobelclark
                  
                  
                  	
                  	
                  		
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                  -- 
                  Niels Chr. Nielsen, M.Sc.
                  Skolevej 18, Nordby
                  DK-6720 Fanø
                  Tlf. (+45)76121216(evening),(+45)65504152(during day)
                  mobile (+45)20878568
                  e-mail: niels_c_nielsen@...
                  
                • Rajive Ganguli
                  With ref. to the posting below (AI techniques and predictive work), we have recently done a lot of work comparing kriging and neural network performance. As
                  Message 8 of 10 , Sep 3, 2004
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                    With ref. to the posting below (AI techniques and predictive work), we
                    have recently done a lot of work comparing kriging and neural network
                    performance. As an example, one of those papers (soon to show up in
                    Jo. Exp. Geol) is posted at
                    http://www.faculty.uaf.edu/ffrg/papers/nomepap_modi_revise.zip.

                    To summarize our findings, I would say there hasn't been much
                    difference in prediction performance. One or the other is marginally
                    better on any given case. An indication of the absolute performance
                    of either methods can be easily obtained from the semi-variogram:
                    lower the nugget, better both methods perform, while higher the nugget
                    the worse they both perform.

                    In the paper that is posted, both methods performed very well with NN
                    having a prediction performance (R_sq) upwards of 0.98 with very low
                    bias and kriging being 0.95.

                    Thanks,


                    Rajive Ganguli, Ph.D., P.E., C.O.I
                    Associate Professor of Mining Engineering
                    University of Alaska Fairbanks
                    ================================
                    Office: 317 Duckering Building
                    Mailing Add: Box 755800, Fairbanks, AK 99775
                    ph: 907-474-7631, fax: 907-474-6635
                    web: http://www.faculty.uaf.edu/ffrg/
                    -------------------------------------------
                    "He uses statistics as a drunken man uses lamp-posts... for support rather
                    than illumination." - Andrew Lang (1844-1912)




                    -----Original Message-----
                    From: Viktoras Didziulis [mailto:viktoras.didziulis@...]
                    Sent: Friday, September 03, 2004 12:12 AM
                    To: ai-geostats@...
                    Subject: Re: [ai-geostats] Frightened of Spatial Autocorrelation

                    Hello, Kevin ! Predictive interpolation is a very interesting field. You
                    may be interested in GIS applications based on Dempster-Shafer Theory.
                    There are some online material also linked to archeology and prediction of
                    archaeological sites at http://gis.esri
                    com/library/userconf/proc99/proceed/papers/pap295/p295.htm and
                    http://websrv5.sdu.dk/ejstrud/forskning.html Also IDRISI GIS has a
                    collection of useful modeling tools for multicriteria
                    analysis. It is described in manual which can be downloaded from IDRISI web
                    site... Another subject of interest might be various AI techniques. I
                    personally am
                    experimenting with Case Based Reasoning (spatial predictions of community
                    structure). There are some references and an experimental module online at
                    http://www.alleco.fi/allmaps Currently I am rewriting the code (for the
                    third time already :)). Still, at
                    least for me it looks promising. Although currently I came to a decision
                    that these 'explicit' GIS modeling techniques must be suplemented with the
                    implicit' ones based on cellular automation, nearest neighbourhood or
                    variograms and krigging. The reason to think so is that those 'inteligent'
                    methods predict ecological niches. But in real world those niches may remain
                    unoccupied. So we need an interaction of explicit top-down influence in form
                    of 'niches' and implicit bottom-up influence in the form of 'growth from a
                    seed'. Best regards Viktoras -------Original Message------- From:
                    Kevin M. Curtin Date: 2004 m. rugsëjis 02 d. 12:44:03 To:
                    ai-geostats@... Subject: [ai-geostats] Frightened of Spatial
                    Autocorrelation Hello All, I'm not sure if this is the correct forum for
                    this…but a colleague has asked
                    a question I'd like to address. This fellow wants to predict the location
                    of archaeological sites based on
                    factors such as soil type, proximity to a water source, slope, AND proximity
                    to other archaeological sites. On proposing such a predictive model he has
                    been challenged with, "How are
                    you going to deal with Spatial Autocorrelation". We're not sure why SA
                    should be a problem since we are suggesting that spatial proximity is a
                    factor in settlement location. So, do we need to test for SA and why?
                    Thanks in advance, Kevin
                  • Volker Bahn
                    Hi Kevin, I work in the field of distribution modeling of birds and somewhat come from the other direction than most geostatistics people here on the list. In
                    Message 9 of 10 , Sep 7, 2004
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                      Hi Kevin,

                      I work in the field of distribution modeling of birds and somewhat come from
                      the other direction than most geostatistics people here on the list. In
                      ecology, we first only predicted by local conditions and habitat, then were
                      pointed to the problems of spatial autocorrelation in such an approach, then
                      tried to compensate for autocorrelation problems in statistics and only
                      lately recognized that autocorrelation is actually additional information
                      that could improve prediction. Steve already posted the most current papers
                      regarding this issue in Ecography, which helped me much
                      (http://www.nceas.ucsb.edu/~liebhold/ecography/). I would add the following
                      paper to the list:

                      Lichstein J. W., T. R. Simons, S. A. Shriner, and K. E. Franzreb. 2002.
                      Spatial autocorrelation and autoregressive models in ecology. Ecological
                      Monographs 72(3):445-463.

                      For birds it has been well documented that autocorrelation in distributions
                      are caused by autocorrelation in underlying resources. Thus, in theory, if
                      you cover ALL important predictors in your model (let's say a regular
                      regression or any other "non-spatial" method), the spatial structure in the
                      distribution is modeled implicitly by being contained in the predictors.
                      However, if you miss a predictor (which in practice will always be the
                      case), you will miss its spatial structure and the residuals of your
                      analysis will reflect this structure rendering these approaches ineffective
                      and statistically flawed. In addition, I'm trying to show in my research
                      that dispersal of individuals (meaning leaving either the birthplace or the
                      last breeding place permanently to breed elsewhere) also leads to
                      autocorrelation in distributions. This could also be the case for
                      archeological sites as there was undoubtedly some contact and exchange among
                      neighbors and this contact would have been more intense with close neighbors
                      as travel comes at a cost. Thus I would expect autocorrelation in the
                      spatial distribution of archeological sites above and beyond the
                      autocorrelation in the underlying conditions predicting archeological sites.
                      I use conditional autoregressive regression models (CAR) in Splus to model
                      bird distributions.

                      I hope this helps

                      Volker
                      _______________________________
                      Volker Bahn
                      Dept. of Wildlife Ecology - Rm. 210
                      University of Maine
                      5755 Nutting Hall
                      Orono, Maine
                      04469-5755, USA
                      Tel. (207) 581 2799
                      Fax: (207) 581 2858
                      volker.bahn@...
                      http://www.wle.umaine.edu/used_text%20files/Volker%20Bahn/home.htm


                      ----- Original Message -----
                      From: Kevin M. Curtin
                      To: ai-geostats@...
                      Sent: Thursday, September 02, 2004 15:43
                      Subject: [ai-geostats] Frightened of Spatial Autocorrelation


                      Hello All,
                      I'm not sure if this is the correct forum for this.but a colleague has asked
                      a question I'd like to address.

                      This fellow wants to predict the location of archaeological sites based on
                      factors such as soil type, proximity to a water source, slope, AND proximity
                      to other archaeological sites.

                      On proposing such a predictive model he has been challenged with, "How are
                      you going to deal with Spatial Autocorrelation". We're not sure why SA
                      should be a problem since we are suggesting that spatial proximity is a
                      factor in settlement location.

                      So, do we need to test for SA and why?

                      Thanks in advance,
                      Kevin




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