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Exploration Models
and GIS for
Mineral Potential Mapping
167
tion w as carried out to produce a digital elevation
model (DEM)
of the
study area (Fig.
4).
In addit ion, a subset of
m i nu s
80-mesh stream
sediment geochemical data
for Ni
(JICA-MMAJ,
1987)
w as
used
to
determine
which
portions
of the
ultramafic
terrane
ar e
enriched
in
nickel.
A
subset
of
260 an alytical results were tabulated in a spreadsheet,
one row per
sample,
with
c olumn s
conta in ing
spatial
an d nonspatial attributes. The spatial locations were
recorded
as (x, y) UTM coordinates; Ni content (in
ppm) were
recorded as
attributes. Each sample
w as
treated as representative of the local catchm ent basin
in
which
it
occurs,
so the
table
w as
applied
to
sample
catchment
basins instead
to the
sampling points (Fig.
5). Thesample catchmen t basins were generated auto-
matically inILWIS usingthe DEM and rastermap of
digitized d rainage lines labeled according to the sample
numbers
(Carranza and Hale, 1997).
Figure 2.
Location and simplified
geologic
map of study
area.
M ap coordinatesare in meters (UTM, zone 51). Inset represents
map of Philippines.
CLASSIFICATION OF NICKELIFEROUS-
LATERITE POTENTIAL
Figure 3 shows the m ethodology u sed in the clas-
sification
of nickeliferous-laterite potential. This was
implemented in ILWIS (Integrated Land and Water
Information System), a GIS software developed by
ITC (International Institute for Aerospace Survey and
Earth
Sciences)
in the Netherlands.
Spatial Data Input
Thesourcesofsp atial dataare the
1:250,000
scale
geologic map
(JICA-MMAJ, 1987)
and
1:250,000
scale topographic maps (NAMRIA, 1992a, 1992b).
The boundaries of the lithologic units were digitized
and conv erted
from
vector (polyg on) to raster
format.
The
100-m interv al elevation contours w ere digitiz ed
an d
conv erted from vector (segment) to raster form at.
From the raster map of elevation contours, interpola-
Spatial Data
Processing
The second step invo lves processing of the spatial
data
inputs to
extract
th e
indicator var iables
for the
classification of nickeliferous-laterite potential. The
geologic map (Fig. 2) was reclassified into two map
unitsperidot i tes and
nonperidotites (Fig. 6A).
Because
only
areas u nd erlain by the peridotites are
important to this study, the reclassified map of the
geology is
used
to
mask nonperidotite areas prior
to
the extraction of areas withfavo rable topographic and
geochemical indicators.
There are two topographic indicators,
slope
an d
plateau edges. In order extract
areas with
favorable
slopes
(i.e., 20 and areas with slopes
< 20
(Fig. 6B).
In
order
to
extract areas favorable
for
nickeliferous-laterite formation(i.e., areas where
plateau edges occur), detailed analysis
of the DEM
was carried out. Ranges of elevations where plateaus
an dplateau edges occur were estimated by graphically
analyzingthe histogram of DEM pixels in the
perido-
tite terrane. For areas
underlain
by a single rock unit,
the intercontour distances are m ore or less uniform so
that
th e
steps
in the
histogram
of
elevation ranges
also
ar e
more
or
less
uniform.
Variation
in the
widths
of
the
steps indicates
the
presence
of
erosional sur-
faces, s uch as plateau s or slope breaks in the landscape.
The edges of plateaus are k nick poin ts that represent
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168
Carranza M angaoang and Hale
Figure
3.
Flowchart
of
CIS-based
classification
of
nickeliferous-laterite potential (modified
after
Bonham-Carter, 1994).
interruptions in the
peneplanation history
of the
land.
From the histogram of the DEM of the peridotite ter-
rane (Fig.7), it is possible to defin e the ranges o f
elevations where plateau edges occur
by
drawing
a
line that connects
th e
steps
of the
histogram.
A
long
straight segment indicates th e ranges of elevations
resulting
from a
long peneplanation history (i.e.,
pla-
teaus are present). Short segments indicate the ranges
of
elevations that result from interruptions
in the
pen-
eplanation events (i.e., plateau edges are present). It
is
clear there are three long segments that represent
elevation ranges of plateaus
(0-100, 200-700,
and
800-1100 m) and there are two short segments that
represent elevation ranges where plateau
edges
ar e
present (100-200and700-800 m). Theareas within
the
peridotite terrane with elevation ranges of 100 to
200 and 700 to 800 m are
extracted from
the DEM
and
are shown in Figure 6C.
The
stream sediment sample catchmen t basin
m ap
of Ni content was classified into two map units
sample
catchment basins with high
N i
(>1000 ppm)
content an d sample catchment basins with low Ni
(
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Exploration Models and GIS for Mineral Potential Mapping 169
Figure 5. Stream sediment sample catchment basins and Ni
content (ppm).
Figure 8. If afavorablegeologicindicator(i.e., perido-
tite)
is
absent, then there
is no
nickeliferous-laterite
potential (0). If peridotites are present, bu t favorable
topographic
an d
geochemical indicators
ar e
absent,
then there is low potential (1). If any one of the three
favorable indicators are present
within
the peridotite
terrane, then there
is
moderate potential (2).
If any
two of the
three favorable indicators
are
present within
th e
peridotite terrane, then there
is
high potential (3).
If
all three favorable indicators are present
within
th e
peridotite, then there
is
very high potential (4). This
simple classification scheme was implem ented by first
creating binary maps that indicate
presence (score =
1)
or
absence
(score = 0) of
each
of the
indicator
variables (Fig. 6). Final ly, these binary maps are
added together.
RESULTS
The
nu m b er
of
pixels represented
by the
peridotite
terrane
is 61,841,
which
is
equivalent
to
about
618
km 2 (a pixel size of 100 X 100 m was used in the
GIS
operations). Abo ut
15 of the
peridotite terrane
has low
potential
for
nickeliferous-laterites, abou t
4 8
Figure
6.
Input
data layers for classification of nickeliferous-later-
ite potential: A, peridotite terrane; B,areas withslopes of < 20
in
peridotite terrane; C,
areas
of plateau
edges
in peridotite terrane;
an d D, stream sediment sample catchment basins with > 1000
ppm Ni.
hasmoderatepotential, about 34 hav e high potential,
and about
3 has
very high potential (Fig.
9).
Because of the importance of mineral potential
classification to land-use p olicy-m aking it is importan t
that the
re l iabi l i ty
of the
classification
is
validated.
In
this example, the contribution and significance of the
Ni
data to the classification of nickeliferous-laterite
potential also needs examination because
Ni
data
ar e
not among the exploration criteria provided by the
model of Golightly (1979).
The r eliab ility of the nic kelifero us-late rite poten-
tial
classification
i s
validated
by
comparing
th e
poten-
tial m ap with
known occurrences
of
nickel iferous-
laterite in the study area.
There
is, however, only one
kn own
nickeliferous-laterite occurrence
in the
study
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Exploration Models and GIS for Mineral Potential Mapping
171
Figure 9. Nickeliferous-laterite potential classification map.
Figure
10.
Nickeliferous-laterite potential classification when
data are excluded.
of
indicator variables based
on the
mineral deposit
model was augmented by the geochemical indicator
thatis
able
to
indicate zones
in the
secondary environ-
ment
enriched
in
nickel.
The
mineral property with known nickeliferous-laterite
deposits is located immediately south of the pro-
tected area.
PRESENT
LAND-USE POLICY
The present land-use classification of the study
area is shown in Figure 11 (Mangaoang,
1997).
About
88% of the
land
is
classified
as
woodlands
or
forests,
about
10 is
agricultural lands, planted mainly
with
rice,and
about
2% is
grasslands.
The
areas classified
to
have high to very high nickeliferous-laterite potential
occupy only about
6%;
almost
all of
this
iswith in the
forests.
These
areas of high to very high nickeliferous-
laterite potential represent an aggregate of about 7%
of the
total forest areas.
The existing land-use policy within the area is
presented in Figure 12 (Mangaoang, 1997). About 68%
oftheareaisprohibitedtomineral resources develop-
ment. In these protected areas, about 87% are forests
an d the
remainder
are
agricultural lands.
These
pro-
tected areas encompass
93% of the
zones classified
to
have high to very high nickeliferous-laterite potential.
DISCUSSION
The prohibition on mineral resources develop-
ment in the study area was imposed before the
nickelif-
erous-laterite potential
was assessed
through
the
methodology presented in this paper. It is not the inten-
tion
of this study to contest this prohibition, but to
stress the importance of mineral potential information
to theland-use policy-making
process.
Wehave shown
here an instance in which areas that are
protected from
mineral resources development later may be recog-
nized to have potential for a particular mineral deposit.
The classification of mineral potential at a national
scale therefore isessential fo rensuring thata ll poten-
tially
mineralized zones
willbe
considered
inplanning
theoptimumuse of theNation's public lands.
The scheme presented here for classifying poten-
tialfor nickeliferous-laterite is a rapid, cheap and sim-
ple methodology. However, the classification scheme
is sensitive to the type of indicator variables that are
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Exploration Models and GIS for Mineral Potential Mapping
173
correctly as high to very high potential by the
methodology.
Almost
all the
zones
o f
high
to
very hi gh potential
fo r nickeliferous-laterite
occursin an
area that
is
pro-
hibited for
min eral resources development. T his indi-
cates that undiscovered nickeliferous-laterites and
other m ineral deposits therein will not be readily avail-
able
to
provide mineral supplies that
ca n
contribute
to
future
economic growth of the country. Min eral
potential information therefore, is , highly critical fo r
opt imum land-use policy-making.
Where m ineral potential
information
an d
important exploration data are lacking,exceptfor basic
geological data, a simple scheme of classifying mineral
potential may be carried out based on the criteria pro-
vided by conceptual mineral exploration models. The
exploration criteria of interest should have a spatial
context so th at the classification scheme can be im ple-
mented using
a
GIS. However, using
only
th e
spatial
indicators required by the conceptual mineral deposit
model mayprove inadequate for a reliable classifica-
t ion.Other spatial indicator variables, w hen available,
have to be
integrated
b ut
their contr ibution
and
signifi-
cance
to the classification have to be validated. The
scheme presented
fo r
classifying potential
fo r
nickelif-
erous-laterite is a rapid,cheap,simple, and yet reliable
methodology. Mineral potential information resulting
from
th e
proposed
methodology is subjective rather
than based on statistical prediction, but provides a
realistic basis
fo r
land-use policy-making.
REFERENCES
Bonham-Carter,
G. F.,
1994, G eographic Inform ation Systems
for
geoscientists: Modellingwith GIS: Pergamon, Ontario,398 p.
Carranza, E. J. M ., andHale,M ., 1997,Acatchment basin approach
tothe
analysis
ofreconnaissance
geochemical-geological data
from
Albay Province, Philippines: Jour.
Geochem.
Explora-
tion,v. 60, no. 2, p.
157-171.
Golightly,J. P.,1979, Nicke liferous laterites: ageneral description,
Evans, D. J. I.,
Shoemaker,
R. S., and
Veltman,
H.,
eds.,
in
International
Laterite Symposium : Soc. M in. Engrs.,
Am .
Inst.
Min .
Met. Petr., Inc.,
New
York.
p.
3-23.
J I C A - M M A J ,
1987, Report
on the
mineral exploration: mineral
deposits an d
tectonics
of two
contrasting geologic environ-
ments in the Republic of the Philippines,Phase HI (Part 1),
Northern Sierra Madre: Japan Intl.
Coop.
Agency, Metal Min-
in g Agency Japan, Tokyo,
403 p.
Mangaoang, J. C., 1997, GIS for management an d development
of
mineral
resources,
Isabela province, Philippines:
unpubl.
masters thesis, Intern. Inst. Aerospace Survey
an d
Earth Sci-
ences, Delft,
The Netherlands, 86 p.
N A M R I A , 1992a,
Ilagan
1:250,000scale
topographic map
sheet
S-2506:
National Mapping
a nd
Resource Information Auth or-
ity,
Philippines.
N A M R I A ,1992b,
Solano
1:250,000
scale
topographic map sheet
S-2508:National Mappinga nd Resource Information Author-
ity, Philippines.
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