Page 165 - Geochemical Anomaly and Mineral Prospectivity Mapping in GIS

166 Chapter 6

c. Determine Ô(X) by dividing values of npixpd with the value of npixtd. As
shown in Fig. 6-8 the values of Ô(X) are stored in the column propd (which
stands for cumulative proportion of deposits) of the attribute table.
d. Calculate D (diff) by subtracting values of propr from values of propd (i.e.,
according to equation (6.4)).
e. Calculate an upper confidence (uc) value for each value of D according to
equation (6.5). The values in column uc shown in Fig. 6-8 were obtained using a
2
critical χ value of 9.21 (i.e., at α=0.01). Note that to calculate uc, M=npixt
and N=npixtd.
f. Calculate β (beta) according to equation (6.6). Note also that M=npixt and
N=npixtd.
After the calculations in the attribute table of the map of classified distances to a set of
geological features, the values in columns buffer, propr, propd, diff, uc and
beta (as shown in Fig. 6-8) can then be illustrated as graphs. For example, in Figs. 6-9
to 6-11, buffer (distance to a set of geological features) is used as variable for the x-
axis in both types of graphs whilst propr (buffer pixels), propd (deposit pixels),
diff (D) and uc (confidence band) are used as variables for the y-axis in one type of
graph and beta is used for the y-axis in the other type of graph.
Fig. 6-9 shows the results of analyses of the spatial association of the epithermal Au
deposits in the Aroroy district (Philippines) with north-northwest (NNW) trending
faults/fractures and with northwest (NW) trending faults/fractures (see also Fig. 5-13).
The epithermal Au deposit occurrences have statistically significant (at α=0.01) positive
spatial association with NNW-trending faults/fractures and the positive spatial
association is optimal within 0.45 km from NNW-trending faults/fractures (Figs. 6-9A
and 6-9B). Within this distance from NNW-trending faults/fractures, all the epithermal
Au deposit occurrences in the study area are present and, according to the curve for D,
there is about 50% higher occurrence of epithermal Au deposits than would be expected
due to chance (Fig. 6-9A).
The epithermal Au deposit occurrences have statistically significant (at α=0.10)
positive spatial association with NW-trending faults/fractures and the positive spatial
association is optimal within about 1 km from NW-trending faults/fractures (Figs. 6-9C
and 6-9D). Within this distance from NW-trending faults/fractures, 85% of the
epithermal Au deposit occurrences in the study area are present and, according to the
curve for D, there is 35% higher occurrence of epithermal Au deposits than would be
expected due to chance (Fig. 6-9C). Thus, the epithermal Au deposit occurrences have
stronger spatial association with NNW-trending faults/fractures than with NW-trending
faults/fractures. These results, which are consistent with the results of the Fry analyses
(Fig. 6-6), further support the fault-fracture mesh model (Fig. 6-7) and the hypothesis
that NNW- and NW-trending faults/fractures are plausible spatial evidence of
prospectivity for epithermal Au deposits in the case study area.
Because intersections of NNW- and NW-trending faults/fractures are possibly
whereabouts extension faults/fractures are situated (Fig. 6-7B), their spatial association
with the epithermal Au deposit occurrences is also analysed. The epithermal Au deposit