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8/11/2019 Application of Mineral Exploration Models & GIS to Generate Mineral Potential Maps as Input for Optimum Land-Use Planning in The Philippines.PDF

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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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