Page 272 - Geochemical Anomaly and Mineral Prospectivity Mapping in GIS
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Data-Driven Modeling of Mineral Prospectivity                        275

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           there are  13 locations of epithermal Au deposits in about 130  km , is likely to yield
           geologically meaningful results.
           GIS-based data-driven estimation of EBFs
              Suppose that in a study area T, comprising N(T) total number of unit cells or pixels,
           there are a number of known mineral deposits, D, of the type sought occurring in N(D)
           number of pixels (Fig. 8-10). Suppose further that X i (i=1,2,…,n) spatial evidence maps,
           each with a number of C ji (j=1,2,…,m) classes of spatial evidence, have been created to
                                                                th
                                                                               th
           represent certain prospectivity recognition criteria. Each of the j  C ji class of the i  X i
           spatial evidence map has N(C ji) number of pixels (Fig. 8-10). The sum of N(C ji) number
                         th
           of pixels in any i  X i spatial evidence map is equal to N(T). By overlaying a binary map
           of D on each multi-class evidential map, the number of C ji pixels overlapping with D
           pixels [i.e.,  N (C ∩ D ) ] is determined. From this, the number  of  C ji pixels  not
                          ji
                                             −
           overlapping with  D pixels [i.e.,  N (C iji  ) N (C ∩ D ) ] can be derived. The values of
                                                  ji
           N(T), N(D), N(C ji) and  N (C ∩ D )  are the ones used in data-driven estimations of the
                                   ji
           EBFs.
                                             th
                                                                     th
              The degree of belief ( Bel C ji  ) for the j  C ji (j=1,2,…,m) class of the i  X i (i=1,2,…,n)
           spatial evidence map with respect to D is, according to An et al. (1994b), estimated as

                   N (C ∩  D )
            Bel  =     ji     .                                                (8.4)
                     N (C  ji  )
              C ji

                                             th
                                                                     th
           The degree of disbelief ( Dis C  ji  ) for the j  C ji (j=1,2,…,m) class of the i  X i (i=1,2,…,n)
           spatial evidence map with respect to D is, according to An et al. (1994b), estimated as

                         −
                   N (C  ) N (C ∩  D )
            Dis  =     ji      ji    .                                         (8.5)
              C ji
                         N (C ji )

                                                     th
                                                                               th
           Then, the degree of uncertainty (Unc C  ji  ) for the j  C ji (j=1,2,…,m) class of the i  X i
           (i=1,2,…,n) spatial evidence map with respect to D is, according to the relationships of
           the EBFs (see Chapter 7, Fig. 7-18),  estimated as

                      N( C ∩  D)  N( C )  −  N( C ∩  D)
           Unc C ji  = 1 −  N( ji C )  −  ji  N( C ) ji  = 1 −  Bel C  ji  −  Dis C ji  .  (8.6)
                            ji
                                            ji
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