Lithologic, Hydrothermal Alteration and Structural Mapping of Okemesi Folds and Environs Using ...

19 Pages·2017·1.78 MB·English

Journal of Geography, Environment and Earth Science
International

12(3): 1-19, 2017; Article no.JGEESI.36143
ISSN: 2454-7352

Lithologic, Hydrothermal Alteration and Structural
Mapping of Okemesi Folds and Environs Using

LandSat 8 OLI and ASTER DEM

Ayo A. Omitogun1 and John O. Ogbole2*

1University of Ibadan, Nigeria.
2National Center for Remote Sensing, Jos, Nigeria.

Authors’ contributions

This work was carried out in collaboration between both authors. Author JOO designed the study,
sourced and analyzed the statistics. The interpolation and rasterization was carried out by authors
JOO and AAO. Supervision was done by author AAO. The paper was coordinated by author AAO.
The manuscript was done and edited by author JOO. Both authors read and approved the final
manuscript.

Article Information

DOI: 10.9734/JGEESI/2017/36143
Editor(s):
(1) Wen-Cheng Liu, Department of Civil and Disaster Prevention Engineering, National United University, Taiwan, and Taiwan
Typhoon and Flood Research Institute, National United University, Taipei, Taiwan.
Reviewers:
(1) Nnamdi E. Ekeocha, University of Port Harcourt, Nigeria.
(2) S. A. Samson, Obafemi Awolowo University, Nigeria.
(3) Prince Suka Momta, University of Port Harcourt, Nigeria.
Complete Peer review History: http://www.sciencedomain.org/review-history/21684

Received 14th August 2017
Accepted 19th October 2017
Original Research Article
Published 1st November 2017

ABSTRACT

Structural and tectonic studies of an area, help in the understanding of the magmatism, metallogeny,
groundwater, seismicity, geothermal and hydrothermal resources of the region. The Precambrian
rocks of Okemesi folds and its environs exhibit multiple deformations, repetitive folding, fracturing
and metamorphism. LandSat data have been used widely in mapping lithological and altered rocks
in geology. Several Red–Green–Blue colour combination images and specialized band ratios,
prepared from Landsat-8 bands coupled with Band ratios derived from image spectra, helped in
delineation of altered rocks, lithological units and vegetation. Aerial photographs have limitations
because of their dependence on natural east-west solar illumination paths which highlight north-
south linear features, perpendicular to the solar illumination; therefore hillshade generated from
_____________________________________________________________________________________________________

*Corresponding author: E-mail: [email protected], [email protected];
Omitogun and Ogbole; JGEESI, 12(3): 1-19, 2017; Article no.JGEESI.36143

digital elevation models (DEMs) are an alternative source for identification of lineaments. In this
research, a procedure for extracting lineaments from hillshaded ASTER DEM was applied; the
results of this study illustrate the effectiveness of extracting lineaments from hillshaded DEMs. The
final interpreted lineament map was then produced with a total of about 178 lineaments extracted
from the ASTER DEM. The azimuthal distribution indicated that most of the lineaments are trending
to NE-SW and NNE-SSW with a few E-W and NNW-SSE directions. These directions are distributed
throughout the Okemesi fold axis and on most of the rock complexes.

Keywords: Lithologic; hydrothermal alteration and structural mapping; LandSat 8 OLI and ASTER
DEM.

1. INTRODUCTION referred to as lineaments and may extend from a
few meters to tens of kilometres in length.
Major shear zones occur in different tectonic Certainly not all lineaments relate to faulting.
settings and are associated with varying tectonic They could also be attributed to lithological
displacements in various orogenies. Regional boundaries, boundaries between different land
scale, steep and generally north-south trending uses, drainage lines or even man-made
shear zones have been recognized in the constructions such as roads. Therefore, it is not
western part of the Nigerian basement complex easy to interpret the potential structural origin of
[1,2,3,4,5]. These shear zones have been traced lineaments based on satellite images only. In
north wards to and correlated with those of the addition, groundwater transferred through faults
Central Hoggar [3,6]. These zones are marked increases the moisture content of soil in relation
by mylonites and cataclasites produced by the to the surrounding area and promotes
shearing of the rocks at different crustal levels preferential alignments of vegetation; abrupt
(temperatures and confining pressures) and fluid changes in vegetation canopy and sudden
phase activities. disappearance of a certain plant species could
also signify fault structures. Fault lines may form
Detection of faults in geological exploration is an specific drainage patterns easily detected on
important parameter in the field of structural, satellite images. More particularly, streams have
economic and environmental geology; a natural tendency to meander. Thus some
conventional mapping methods used in the frequently-found types of stream anomalies, such
mapping of faults require fieldwork investigations. as straight segments, sudden bends observed
In most cases, fieldwork could be very tasking along stream courses, displacement or even
and time consuming; this usually depends local disappearance of drainage system into lines
primarily on the area extent and accessibility of of sinkholes could mark a fault line on an image.
the study Physical features such as topography,
erosion, over-growth of vegetation, scale, and Hydrothermal fluid processes alter the
other factors, control fault determination in the mineralogy and chemistry of the host rocks that
field. can produce distinctive mineral assemblages
which vary according to the location, degree and
Remote Sensing is an important technology that duration of the alteration processes. When these
has the advantage of providing synoptic view of alteration products are exposed at the surface,
the region; this makes it easier to identify some they can be mapped as a zonal pattern. They
of the characteristics of structural geological appear concentrically around a core which has
features that extend over regional areas. As the highest grade alteration and greatest
opposed to fieldwork investigations, remote economic interest. The importance of the
sensing along with image processing techniques recognition of such spatial patterns of alteration
accounts for a less time-consuming and a more makes the ‘remote sensing technique’ one of the
cost-effective method for fault detection. standard procedures in exploration geology, due
Nonetheless, such techniques in no way replace to its high efficiency and low cost [7]. The
field investigations, but on the contrary they application of remote sensing in mineral
complement each other. exploration was derived from use of aerial photo
in reconnaissance survey. Remote sensing and
Faults and fractures are often revealed as linear GIS technique are used to update existing maps,
or curvilinear traces on satellite images. These to produce geologic maps, locate fractures
image lines of different contrast are commonly (lineaments) and also to identify rock alteration

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zones. Different stages of image-processing Ekiti, and Osun States respectively, while a little
techniques were applied to LandSat 8 OLI image portion falls in Ondo State, Southwestern
of the study area to discriminate the different Nigeria, with a total surface area of 1665.5 km2.
major lithologies in the area. The major towns in the area include: Ilesa, Oke-
Ila, Okemesi, Ilupeju, Soso, Oba-Sinkin,
In this study, ASTER (Advanced Spaceborne Ayegunle, Kajola, Ijero, Ibokun, Ikogosi, Igbara
Thermal Emission and Reflection Radiometer) Ado and Ajindo (Fig. 1).
DEM, multi spectral LandSat 8 Operational Land
Imager (OLI) satellite images were processed, to The Okemesi fold belt and its environment have
enhance lineaments which are potential faults, a closely developed drainage system (Fig. 2).
fractures, geological structures, etc. The The drainage pattern is generally related to the
combination of different processing techniques geology of the area. It is roughly trellis indicating
(Principal Component Analysis, the creation of the influence of the structures of the underlying
False Colour Composite images and the rocks. The major streams namely the river
intensity-hue-saturation transformation and Band Shasha, Obabu and Mokuro commonly flow
ratio), also contributed to lithologic and through the low lying portions between the
hydrothermal alteration mapping. topographic highs. Northwest and southwest
parts are drained by the tributaries of these
2. THE STUDY AREA rivers. The northeast and southeast areas are
drained by the tributaries of Rivers Ora and
The study area lies within latitudes 07°27’1.24”N Osun. These streams which are mainly sandy
and 07°54’18.67’’N and longitudes along their upper courses are often composed of
004°43’41.96”E and 05°07’47.14’’E respectively. mudflats rich in organic matter derived from
It covers parts of the topographic map sheet bamboo, palm trees and shrubs occurring in the
numbers 243 Ilesha, 244 Ado Ekiti, 264 Akure, stream valleys.
and 263 Ondo. The study area covers part of

Fig. 1. Map of study area

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The area of study consists of an undulating Precambrian Basement Complex of
terrain with elevations ranging from 221 m in the Southwestern Nigeria, which is also part of the
western portion underlain by muscovite-quartz Basement Complex rocks of Nigeria
schist and pegmatites, through 799 m in the (Precambrian-Paleozoic). The study area is also
middle to the eastern portion underlain by part of the regional Dahomeyide fold belt defined
amphibolites and undifferentiated migmatite by [8], and so it is not an exception to the
gneiss complex and schist (Fig. 2). structural and deformational episodes that
pervaded Nigeria’s Precambrian Basement
The study area lies within the Ilesha schist belt; it Complex.
is underlain by crystalline rocks of the

Fig. 2. Drainage and topographic map of the study area (from DEM)

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For many years, the Ilesha district within the elluvial and alluvial deposits, covering much of
Precambrian basement complex of southwestern the western and northern parts of Ilesha. Here,
Nigeria (Fig. 3) has been widely known for the the underlying and possible source rocks are
substantial production of gold [9,10]. Gold mafic-ultramafic units and metasediments [11]. In
workings are concentrated in two major the other zone which is to the southeast of the
geologica1 zones; these include the district area, primary gold mineralization occurs in felsic
characterized by occurrences of essentially veins hosted in granite gneiss.

Fig. 3. Geologic map of study area, modified after geological survey (1972)

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The major rock associations of the Ilesha area district may be broadly grouped into gneiss-
generally belong to the Proterozoic schist belts of migmatite complex, mafic-ultramafic suite
Nigeria, which are prominently developed in the complex, metasedimentary assemblages and
western half of the country. Apart from gold, intrusive suite of granitic rocks. A variety of minor
other mineral resources of the schist be1ts rock types are also related to these units. The
include nickel and chrome ores, talc, magnesite, gneiss–migmatite complex comprises migmatitic
asbestos and iron ores. In terms of structural and granitic gneiss, calcareous, and granulitic
features, lithologies and mineralization, the schist rocks. The mafic–ultramafic suite is composed
belts of Nigeria show considerable similarities mostly of amphibolite, oolitic schist and minor
with Achaean greenstone belts. However, the meta–ultramafics. The metasedimentary
latter usually contain much larger quantities of assemblages, chiefly metapelite and psammitic
mafic and ultra mafic bodies and assemblages of units are found as quartzite and quartz schist.
lower metamorphic grade [11]. The intrusive suite consists essentially of Pan-
African (ca. 600 Ma) granitic units. The minor
The Ifewara fracture zone separates the rocks of
rocks include garnet-quartz-chlorite bodies,
the Ilesha schist belt into two structural units of
biotite-garnet rock, syenitic bodies, diorite and
contrasting lithologies namely the eastern and
dolerite. The association of volcanic and clastic
western segments [12,13,14,4]. The western
rocks suggests a eu-geosynclinal environment of
segment is underlain by amphibolite, amphibolite
deposition [20,9,21]. However, the quartzites are
schist, quartz schist, associated with pegmatite
oolitic, metamorphosed from sandstone and tend
and gneisse: the eastern segment of the schist
to form good topographic features with bands of
belt (in which the study area lies) is referred to as
long-hogback ridges around Okemesi through
the “Effon Psammite Formation”, made up of
Itawure and extending to Aramoko, with an
quartzite, quartz schist and quartzo-feldsparthic
elevation of approximately 100m above the
gneisses with minor iron rich schist and granulite.
surrounding terrains (Fig. 3).
The formation has a general NNE-SSW direction

showing thickness of quartzite due to
3. MATERIALS AND METHODS
overthrusting of the Effon Psammites. Other

authors ([15,16,17,18]) have provided evidences
The following data sets were employed in the
in support of the existence of the structure as
present research work: LandSat 8 OLI, ASTER
well as its significance in terms of tectonic
DEM, existing geological maps covering the area
movements [19].
of study and other ancillary data. Please see

On the basis of field relationships and table below for summary of materials used.
petrological features, the rocks of the llesha

Table 1. Summary of data source and material

1. Satellite Image Data
Image type Source Date of acquisition Resolution(meter)
LandSat 8 OLI, USGS 17/12/2015 30
VNIR, SWIR,
TIR
ASTER DEM USGS 15/12/2010 30
2. Materials
Type Description
Instrument Handheld GPS, Camera, Geologic Hammer, Compass
clinometers, Hand lens, Sample bags, Tapes, Marker.
Software ArcGIS 10.4, Erdas Imagine 2014, Envi 5.3,
Georient, Hyppy, Geomatica.
3. Other Data
Data type/Scale Area Sheet Source
Topographic Ilesha-Okemesi Ilesha NE/SE, Ondo NE Federal Survey
map, 1:50,000 Ado-Ekiti NW/SW and Akure NW Topographical
Sheets
Geological Map, Ilesha-Okemesi Iwo and Akure Sheets Nigerian
1:250,000 Geological Survey
Agency

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LandSat 8 Operational Land Imager (OLI) lineaments were compared to each other
images consist of nine spectral bands with a visually. These lineaments were cleaned visually,
spatial resolution of 30 meters for Bands 1 to 7 by overlaying roads present in the area, and
and 9, the resolution for Band 8 (panchromatic) automatically by removing all straight edges
is 15 meters; LandSat 8 (OLI) was chosen coinciding with boundary of the subset image.
because of its spectral discrimination of a variety
of characteristics that are required for the study. The manual extraction was a two-fold process
One full scene of LandSat 8, of path 187 row 65 involving digitizing lineaments from existing
having a swath width of 185 km, covers the study geological maps and from visible lineaments and
area. Band 7 (2.11 - 2.29 micrometers); faults in the image composite of LandSat 8 and
shortwave infrared, is useful in the extraction of ASTER DEM in the four principal directions. The
geological formations and rock features. second step involved passing four directional
Although previous lineament extraction studies filters through the LandSat 8 Band 6 covering the
using LandSat had made use of Thematic area.
Mapper (TM), Enhanced Thematic Mapper
(ETM) and ETM+ sensors; the corresponding The DEM technique for structural interpretation is
short wave infrared band in OLI was used in this based on the shaded relief image with various
research. elevations. In addition, enhanced techniques
such as different vertical exaggeration with
LandSat-8 data was converted to surface varying sun azimuths and angles can improve
reflectance using the FLAASH in ENVI. During elevation image for interpretation. In order to
the atmospheric correction, raw radiance and DN achieve the objectives, the following steps were
data from imaging spectrometer is re-scaled to undertaken: (1) image enhancement techniques,
reflectance data. Therefore, all spectra are with different vertical exaggeration and shading,
shifted to nearly the same albedo. The resultant were first applied to raw data of the DEM image;
spectra can be compared with the reflectance (2) the enhanced image data were interpreted
spectra of the laboratory or field spectra, directly. using visual justification to produce a lineament
The panchromatic and cirrus cloud (band 9) map; (3) the information obtained from
bands have not been used in this study. interpreted lineaments were plotted in rose a
Remotely-sensed spectral information was diagram; (4) the major trends were obtained
obtained from LandSat 8 OLI image, and the interpreted from interpretation of the geological
area of study was subset from a full scene structures; in addition, some of the linear
covering parts of Southwest Nigeria. The scene features observed from the DEM image were
was corrected for atmospheric, geometric and considered to be faults and fractures.
radiometric effects. Image enhancement was
performed to extract lineaments that would not 4. RESULTS
have been apparent from the images. The
lineaments were digitized and the rose plot for The geological maps, including lineaments,
the lengths of and directions of the lineaments lithology and landforms for Okemesi folds and its
plotted. Shear zones were digitized. environs, were produced from the image
processing techniques implemented on LandSat
Digital spatial operations were carried out on the 8 OLI image and ASTER DEM data. Integrated
LandSat 8 OLI image covering the area. Contrast field ground truthing and remote sensing
and edge enhancement filters were applied to techniques proved to be useful for lithologic and
the image to enhance the visual quality, and structural analysis of the study area. False-
principal component analysis (PCA) operations Colour Composite (FCC), band ratios, principal
were also carried out on the image; Band ratio component analysis (PCA) are some of the
operations were also carried out. Lithology important imagery techniques used for the
variations were established, areas determination of lithologies, structures and areas
hydrothermally altered were also mapped out. hydrothermally altered.
The lineaments seen on the image were digitized
to produce a lineament map based on lineament 4.1 Colour Composite
density.
This is a spectral process that creates a raster
Lineaments were extracted using the automated dataset containing subset of the original raster
extraction process. Different sets of parameters dataset bands. This is used to create a new
were used in the processing: the extracted raster dataset with a specific band combination

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and order. The order that the bands are listed in Various false colour composite models were
the Multi-value Input control box will determine proposed in this study for LandSat 8 OLI
the order of the bands in the output raster covering the area under study (Fig. 4A, B and C).
dataset. Generally, the output raster dataset These models were considered based on their
takes the extent and the spatial reference of the correlation coefficient, where the most
first raster band with a spatial reference in the uncorrelated bands are combined in RGB.
list.

Fig. 4. LandSat 8 OLI false colour composites with band combinations; (A) 5 4 2 (B) 6 5 2 and
(C) 7 6 2

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An automated technique was applied using interpreted linear features. The manually
Geomatica software to extract lineaments from extracted lineaments were also plotted into a
the 6 5 2 OLI band composite (Fig. 6). The rose diagram, both lineaments extracted through
lineaments were checked and edited, artefacts automated and the manual processes were laid
were removed from the back ground, the over each other and compared. A good
resulting lineaments were plotted into a rose correlation between the results derived from both
diagram. The major trends observed are NE–SW processes of extraction was observed;
and a few NNE–SSW and NEE–SWW (Fig. 7Dii). consequently, a resulting lineament density map
Lineaments were also extracted manually from was produced (Fig. 8B) from the combined layer
the OLI 652 composite, by manually tracing the (Fig. 8A).

Fig. 5. Images of (A) LandSat OLI Band ratio combination 4/3, 6/2, 7/4, (B) LandSat OLI Band
ratio combination 4/2, 6/7, 5, (C) LandSat OLI PCA 4,3,2, and (D) LandSat OLI PCA 6, 5, 4

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4.2 Band Ratio individual PC image or any three of the resulting
components were then enhanced linearly and
Band ratioing is a very effective technique. displayed as single or composite images for
Although may seem simple, it combines different further interpretation of lithology, structures and
wavelengths in different representative bands hydrothermal alteration. Statistics were
simultaneously to reveal useful information. For computed for the individual images and
identification and classification of lithology and percentages of data variations were produced.
structures, ratio images were prepared for the The OLI PCAs of PC bands 432 and 654 were
study area. The ratio images were created by generated as seen in Fig. 5(C) and (D). The OLI
dividing the Digital Number (DN) in one band by PCs 432 and 654 were compared, they both
the corresponding DN in another band for each discriminated lithology, the lithologic
pixel, stretching the result value and plotting the discrimination in OLI PC 432 gave a more broad
new values as an image. Band ratios of LandSat category of lithology grouping, while the OLI PC
OLI b4/b3, b6/b2, b7/b4 (Fig. 5A) and b4/b2, 654 gave a more detailed lithology variation and
b6/b7, b5 (Fig. 5B) in RGB were also prepared. structural enhancement (Fig. 5D). The PC 658
Structures, lithology and regions of hydrothermal was further reclassified and filtered:
alteration were enhanced: the band ratio b4/b2, consequently, a resulting image showing a better
b6/b7, b5 in Fig. 5B shows the hydrothermally defined lithology was derived (Fig. 6A), and five
altered region as yellow to the yellowish region of major rock types could be identified from the
the image (Fig. 9D). resulting image; i.e porphyritic granite, coarse
porphyritic biotite-granite, schist and amphibolite
The band ratios of LandSat OLI b4/b3, b6/b2, region, quartzite and quartz schist, and gneiss
b7/b4 in RGB and the OLI 762 composite (Fig. and migmatite undifferentiated. Compared to the
4C) are similar in texture and tone, and seem to geologic map of the area, the above image
have equal ability to enhance structures. Here, shows very strong correlation as seen in Fig. 6A
the major trending structures are strongly & B.
discriminated, and lineaments were extracted
from ratio of OLI b4/b3, b6/b2, b7/b4 as seen in 4.4 Dem Interpretation
Fig. 9(A) and (B). A rose diagram was plotted for
these structures, the major trend observed is Elevation data provides the topographic
ENE–WSW and a few NE–SW and E–W expressions of an area. They have been applied
trending structures (Fig. 9C). Subsequently, for structural interpretation by various
lineament density analysis which is a spatial investigators in the past [24,25,26]. Elevation
statistical analysis that calculates the intensity data can be represented in different forms:
per unit area from lineament features that fall among them, the grid forms (DEMs) are
within a radius around each pixel was carried out preferably useful for interpreting linear geologic
and a lineament density map was produced. structures which have topographic expressions
due to offset of the surface. The ability of
4.3 Principal Component Analysis producing different shaded relief images because
of the freedom to select illumination from any
PCA is a statistical method that allows for the angle [24], makes DEM selectively useful over
transformation of intercorrelated variable data set Arial photographs [27,25,28,26]. According to the
that are multivariate in nature into a data set authors, solar elevation and azimuth are
consisting of new uncorrelated variables [22,23]. important elements to examine topographically-
The first principal component largely, accounts related and dependent features. DEMs could
for as much of the variability in the new data as also be fused with other multispectral images to
possible while each of the succeeding increase interpretability and obtain more
components accounts for the remaining information than can be derived from each of the
variability. PCA is then a widely used single image alone [26]. The various image
enhancement technique in which the information enhancement techniques including directional,
content of the different bands become edge and sobel filters can be applied to DEM to
compressed and confined within the first few enhance different linear structures [24].
bands. The LandSat OLI was normalized in order Therefore, this technique was also considered for
to reduce errors usually encountered as a result extraction of surface lineament, to assess their
of various effects such as sensor quality and general pattern and density to decipher structural
difference of dynamic range [23]. The PCs were information of the area.
calculated for the normalized 7 OLI bands. The

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