Page 183 - Modern Spatiotemporal Geostatistics
P. 183

164      Modern  Spatiotemporal  Geostatistics  —  Chapter 8

         Doing    Progressive Guesswork

         Unlike  Arthur  Golden's novel,  Memoirs  of  a  Geisha, which  describes a world
        in which  appearances are paramount (Golden,  1997),  in the geostatistical world
        one  seeks  to  go  beyond  appearances,  adding  scientific  substance to  the maps
        obtained.  This  can  happen if  not  only  the  physical  knowledge  bases  are  in-
        tegrated  into space/time  analysis,  but  the  uncertainties  associated with these
        bases  are adequately  assessed  and  visualized, as well.
            The  preceding  measures of  mapping  accuracy  (or,  if you  prefer,  measures
        of  mapping  uncertainty)  are most valuable  in the vast majority  of applications
        in  geostatistical  practice  in  which  the  phenomenon being  studied  cannot  be
        isolated  from  a  host  of  confounding  influences that  introduce  a  chance  com-
        ponent  of  considerable size  into  the  quantitative  analysis.  In  many  situations,
        while the  amount  of  uncertainty  estimated  solely on the  basis of the  hard data
        may  initially  be substantial,  there  is  usually a  significant  amount  of  physical
        knowledge currently  being ignored that could improve considerably the mapping
        accuracy  of the  phenomenon.
             BME  analysis establishes a  progressive  process, during  which  the  maps
        produced  using  the  new  knowledge  show a  substantial  improvement  in accu-
        racy  over  the  maps  previously  obtained.  As  the  process tends  towards  the
         "ultimate"  map, the  application-specific goals of  map making allow a specified
        level  of  uncertainty  relative to  the  actual  (but  unknown)  map.  Assessing this
        uncertainty  is the  important task of the quantitative  measures discussed in this
        chapter.
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