Digital image processing and geospatial analysis of ... · PDF fileDigital image processing and geospatial analysis of landsat 7 ETM+ for mineral exploration, Abidiya area, North Sudan

INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES

Volume 3, No 3, 2013

© Copyright by the authors - Licensee IPA- Under Creative Commons license 3.0

Review article ISSN 0976 – 4380

Submitted on January 2013 published on March 2013 645

Digital image processing and geospatial analysis of landsat 7 ETM+ for

mineral exploration, Abidiya area, North Sudan Sami O. El Khidir, Ibrahim A.A.Babikir

Faculty of Petroleum & Minerals, Al Neelain University, Khartoum, Sudan

[email protected]

ABSTRACT

Digital data of Landsat Enhanced Thematic Mapper Plus (ETM+7) was used in mineral

exploration investigations for the area around Abidiya area, North Sudan. The studied area

consists of Precambrian crystalline basement rocks. The oldest geologic unit comprises basic

and ultrabasic rocks associated with metacherts overlain by island arc-related

metavolcanosedimentary sequences, these units have been overlain by supracrustal

metasediments and intruded by magmatic granitic intrusions. Regional structures manifested

by the Nakasib suture and Keraf shear zones. Several digital image processing “DIP”

techniques applied on the multispectral bands (1, 2, 3, 4, 5 & 7) were demonstrated in the

context of geological mapping and mineral exploration. Dual techniques of analyses have

been carried-out to enhance and delineate the alteration zones related to gold mineralization.

Mineralization zones can be identified by their spectral signatures of the alteration products

iron oxides, hydroxyl-bearing minerals, carbonates and quartz-feldspars minerals. Alteration

map have been produced based on the band ratio techniques produced from Sabin’s band

ratio color composite image (bands 5/7, 3/1 and 3/5 in the R G B, respectively). Another

alteration map produced by using the Feature Oriented Principal Selection technique (FPCS),

named as Crosta alteration color composite image. The Crosta image based on a selective

principal component analysis for some bands. Both alteration images have been supervised

classified and vectorized. Geospatial analysis of the vectorized layers proved to support the

demarcation of the mineralization zones. These zones are aligned with the sheared and

metamorphosed basic and ultrabasic and metacherts, and controlled by the shear fractures.

The metasomatic replacements associated with the shear activities could be responsible for

enhancing the mineralization in this area, which gave high signals in the alteration map.

Keywords: Landsat 7, Spectral enhancement, image transformation, FPCS, alteration zone,

geospatial analysis.

1. Introduction

Remote sensing has been widely used in natural sciences since the last century. It has been

used in many geological applications as geological mapping, mineral exploration,

geotechnical and hydrogeological investigations. In Sudan many researches involve the

optical and radar remote sensing data have been conducted (Abdelsalam, et al., 1995; Kenea,

1997; Mohamed, 1997, Elsayed, 2002; Ali, 2005; El Khidir, 2006 and Babikir, 2006).

Exploitation of remote sensing images in mineral exploration is well understood by

enhancing geological mapping, mapping the regional lineaments and structural trends,

mapping local fracture and faults to delineate localized ore deposits and recognize

hydrothermally altered rocks by their spectral signatures (Sabins, 1997, 1999).

The study area lies east of Abiydia town, River Nile State, North Sudan. It is bounded by

Latitudes 18º 10` and 18º 40` N and longitudes 33º 55` and 34º 10` E (Figure 1). The purpose

Digital image processing and geospatial analysis of landsat 7 ETM+ for mineral exploration, Abidiya area,

North Sudan

Sami O. El Khidir, Ibrahim A. A. Babikir

International Journal of Geomatics and Geosciences

Volume 3 Issue 3, 2013 646

of this study is to use digital image processing techniques (DIP) and geospatial analyses to

delineate various lithological units in the context of geological mapping and demarcate

alteration zone related to gold mineralization by the their spectral signatures of the associated

minerals. PCI Geomatica 9.1 and ArcGIS 9.2 software packages are both used in digital

processing, spectral enhancement, spectral classification and geospatial analysis of the

produced enhanced images to for lithological classification and identifying alteration halos of

mineralized bodies.

Figure 1: Location map of the study area.

2. Geological and structural setting

The Precambrian basement rocks in Northeast Sudan comprised two distinct geodynamic

crustal domains. The eastern domain known as the Nubian Shield is a part of the Arabian –

Nubian Shield (ANS) of Neoproterozoic age, formed during the Pan African orogeny (950-

550 Ma). The ANS comprises welded terrains of assemblages of low-grade metamorphosed

arc volcanics and associated intrusive rocks immature sediments and ophiolitic remnants of

arc- and back-arc basins. These terrains are separated by ophiolitic-decorated suture zone as

the NE-trend Nakasib suture separating the Haya terrain from Gebeit terrain (Kennedy, 1964;

Vail, 1979, 1983 & Kröner, et al., 1987) (Figure 2). The other western domain represented by

the Precambrian rocks exposed west to the Nubian Shield and contains a heterogeneous

mixture of Archean, Paleo-, Meso-, and Late Proterozoic rocks, referred to as the Saharan

Metacraton (Abdelsalam et al., 2002).


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Figure 2: Sketch map of the main tectonic domains, Precambrian structures, major shear and

suture zones of the Arabian- Nubian shield “ANS” (Modified after Ali, 2005).

The boundary between the two domains is still a matter of debate; Bailo (2000) suggested

that the N trending Keraf shear zone (KSZ) in northern Sudan defines the northern boundary

between those two Precambrian crusts. While Kuster and Liegeois (2000) based on

geochemical and geochronological data argued that the eastern boundary of the East Saharan

Craton lie below or more to the west. The NE trending Nakasib Suture Zone (NSZ) represent

the most prominent suture zone in the Red Sea Hills (Abdelsalam and Stern 1990). The study

area comprises different lithological units (Ali, 2005; El Khidir, 2006). Based on the

geological and structural situation the ophiolitic mafic-ultramafic sequences represent the

oldest rock unit. Ali (2005) reported and described in details the mafic ultramafic masses in

the intersection area between the Keraf Shear Zone and the Nakasib Suture Zone. The new

masses are located in the same trend of the Oshib ophiolitic rocks decorating the Nakasib

suture zone (Abdelrahman, 1993). The basic-ultrabasic rocks associated with layers of low


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grade metachert sediments, overlain by metavolcanosedimentary sequences, which comprise

a series of basic to intermediate island arc volcanic assemblage and supracrustal

metasediments. The above units were intruded by syn- to late- and post-orogenic intrusions.

Cretaceous sediments represented by Nubian Sandstone group is the Phanerozoic units in the

area. Quaternary and recent deposits are manifested in the alluvial wadi deposits, Nile silts

and the superficial aeolian sediments (Figure 3).

3. Digital Image Processing

Digital image processing of the multispectral remotely sensed data is carried –out in order to

improve the appearance of the images and enhance information extraction in the geological

context. In this perspective the various techniques adopted here is improve the visual

geological interpretation and automated spectral signatures extraction related to the altered

halos of the mineralized bodies.

Figure 3: Geological map of the study area

3.1 Image enhancement techniques

Image enhancement techniques adopted in this study compromised different spectral

techniques. Spectral enhancement can be carried by simple contrast stretching technique to

enhance certain spectral characteristic features in the digital images. Contrast stretching is

one of the most simple, important and widely used methods. It deals with rescaling of grey

levels to the entire digital number (DN) range so that features of interest are better shown in


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the image (Gupta, 2003). In this respect, the linear contrast stretching has been applied for

colour composite images of bands 7, 4 & 1 (Figure4). The produced false colour composite

image (bands 7, 4 and 1) has much better contrast and spectral resolution for geological

information.

3.2. Mineral exploration

Mineral deposits are usually associated with alteration zones, especially those related to

sulphide deposits. These alteration successive zones constitute one of the most important

guides for mineral exploration. They are rich in alteration minerals such as, the iron oxides,

the hydroxyl-bearing minerals, carbonates and quartz-feldspar minerals. The spectral features

of the hydroxyl-bearing and iron oxide minerals are the main indicators for prospecting and

delineating mineral deposits in multispectral remote sensing context and are widely

applicable in the prospecting projects.

Figure 4: False color composite image of bands 7, 4 and 1 in the R, G & B, after linear

stretching


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In this context, digital image processing directed towards enhancing the alteration zones

related to gold mineralization in the study area. The techniques adopted to pinpoint

mineralized zones by their spectral signatures of the alteration mineral products, can be

summarized as follows

1. Image transformation by band ratio technique; examines the results of band

ratioing image related to iron oxide and hydroxyl-bearing minerals alterations.

2. Creation of false color composite (FCC) image from ratio bands technique

{Sabin’s ratio image}. Identifying alteration zone by the spectral characteristics

of the iron oxide and hydroxyl-bearing minerals alterations.

3. Image transformation by Feature Oriented Principal Component Selection

(FPCS). This method is to map the iron oxides minerals and hydroxyl- bearing

minerals by unadjusted principal component analysis for some selected bands;

examine the results of FPCS image as set as F-image (iron oxide alteration), H-

image (hydroxyl-bearing minerals) images.

4. Creation of FCC from the FPCS products (F-images, {F + H image}, H-image

in the R, G and B, respectively).

5. Supervised classification for both FCC images to delineate alterations to

produced two thematic maps.

6. GIS-based geospatial analysis for vectorized thematic supervised classified

maps. The geo-spatial analysis used to illuminate the alteration zones.

3.2.1 Band ratioing images

A band ratio image is created by dividing brightness values, pixel by pixel, of one band by

another. The primary purpose of such ratios is to enhance the contrast between objects by

dividing brightness values at peaks and troughs in a spectral reflectance curve. This tends to

enhance spectral differences and suppress illumination (topographical) differences. Ratios

can be used to differentiate objects if those objects have characteristic spectra. A false color

composite can then be made in which each ratio band is assigned one of the three primary

colors with the lighter parts (high DN values) of the band contributing more color to the

composite.

In mineral exploration band ratioing is widely used to enhance the spectral feature of the

alteration zones depending on the absorption bands of their altered minerals. For example

iron oxides (ferrous and ferric oxides) minerals are illuminated by band ratio 3/1, 3/5 and 5/4,

while band ratio 5/7 is used for detecting high values of the hydroxyl-bearing minerals

(kaolinite, illunite, muscovite, epidotes, chlorites, amphiboles) (Gupta, 2003). In this context,

band ratioing techniques have been applied to obtain indicator in the form of iron oxides

alteration image by dividing the DN of band 3 over DN of band 1, additionally, ferrous

oxides alteration supported by another band ratio of band 3/band 5. Similar technique adopted

to acquire criteria of the altered hydroxyl-bearing minerals related to mineralization zones.

This image produced in the form of DN band 5/ DN of band 7. The results of band ratioing

have been subjected to low-pass filter, smoothing is used to eliminate small zones lesser that

90x90 m. Simple linear stretching produce a pleasant grey-scale images. These alteration

zones have evidently depicted by grey scale images of the band ratio ones. A false coloured


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image have been created by combine the results of band ratioing in the form of (R=5/7, G=

3/1, B=3/5), which is called Sabins's ratio coloured image (Figure5). The obtained image

portrays gossans and alteration zones in crimson reddish hues due to high contents of their

iron oxides and clay minerals (Sabins, 1997).

3.2.2 Principal Component Analysis (Feature Oriented Principal Component Selection

“FPCS”

Feature Oriented Principal Component Selection (FPCS) is a method to select some bands of

the image not all to run a principal component transformation. The selected bands are

believed to exhibit spectral information over an intended target (Crosta and Mc. Moore,

1989). This method developed by Loughlin (1991) to map alteration zones and it is well

known by Crosta image. Theoretically, it is known that the iron oxides minerals and

hydroxyl- bearing minerals display absorption bands in range of bands 1 and 7 in the ETM+7

data, respectively. Hence, two sets of four selected bands are transformed by unadjusted

principal component analysis. The eigenvector loadings are carefully examined to define

which Principal Components (PCs) contain information related to the target objects.

Figure 5: Band ratio transformations images (A) Iron oxides alteration map (band ratio3/1),

(B) Hydroxyl-bearing minerals alteration (band ratio 5/7) (C) Sabin’s color composite image

(bands 5/7, 3/1 and 3/5 in the R, G and B) showing alteration zones in crimson reddish hues.

Usually, in the principal component transformation the first and the second components are

excluded, since they reflect the general albedo and topography for the first PCA and the

second component differentiate between the VNIR bands against the SWIR bands. Special

smoothing techniques applied to the higher order components, displaying the desired

information, as they often contain noises. The result is grey-scale image that depicted the

target object in contrasting response.


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Following Crosta technique to map alteration zones (Crosta and Mc. Moore, 1989). The ETM

bands 1, 3, 4 and 7 are transformed to obtain the PCs, which are defining iron oxides richer

zones. The obtained PC image is called F-image, while the ETM bands 1, 4, 5 and 7 are

transformed to depict zones richer in hydroxyl-bearing minerals (H-image). These images are

produced after examining the eigenvector loading for both sets (Tables 1 and 2), which are

PC4 in both produced images.

An obtained F- and H- grey scale images are used to examine the displayed zones. A false

colour composite image "Crosta alteration image" is produced after displaying the

hydroxyl delineating image (H-image) in the red channel, the iron oxide defining image (F-

image) in the blue channel and the mathematical added image (H-image + F-image) in the

green channel after smoothing by low-pass filter: The image defines alteration zones usually

in terms of their iron oxides and clay minerals richer zones by reddish yellowish hues The

filtering operation is carried in order to remove or subdue effects of the incorporated

significant noise from the high-order PCs as it is often expected and then result in improving

the hues in the data (Figure 6).

Table 1: Eigenvectors of covariance matrix (bands 1, 3, 4 and 7), for mapping the iron oxide

minerals alteration zones in the study area

PC / bands Band 1 Band 3 Band 4 Band 7

Mean 37.14 94.68 112.82 100.73

Stand. Dev. 8.21 18.48 19.14 17.36

PC1 0.24235 0.57341 0.57824 0.52736

PC2 - 0.07327 - 0.27598 - 0.31637 0.53678

PC3 - 0.53034 0.54009 - 0.18672 - 0.62624

PC4 - 0.80910 0.55076- - 0.17127 - 0.20391

Table 2: Eigenvectors of covariance matrix (bands 1, 4, 5 and 7), for mapping the hydroxyl –

bearing minerals alteration in the study area

PC / bands Band 1 Band 4 Band 5 Band 7

Mean 37.14 112.82

107.12 100.73

Stand. Dev. 8.21 19.14 17.88 17.36

PC1 0.23723 0.58191 0.56233 0.53748

PC2 0.04131 0.78261 -0.31637 -0.53454

PC3 -0.96864 0.16672 0.17127 0.06786

PC4 0.06119 -0.14531 0.74455 -0.64848


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Figure 6: Results of the FPCS transformations, (A) F-image for iron oxides alteration map

by FPCS of bands 1, 3, 4 and 7. (B) H-image for Hydroxyl-bearing minerals

alteration by FPCS of bands 1, 4, 5 and 7. (C) Crosta’s color composite image (H-

image in red, (H-image + F-image) in green and F-image in blue) showing alteration

zones in yellowish orange-red hues.

3.2.3 Supervised classification

Supervised classified maps were produced from the Sabins's and Crosta’s colour composite

images. Maximum likelihood algorithm have adopted for both images after providing

adequate eight training areas. The separability between the training areas is good and shows

results lesser than 2 and is 1.5 in average, which indicate the presence of good spectral

signatures for each class. The resultant maps have been filtered by sieve filter to eliminate the

small noisy areas to produce pleasant maps. These maps clarify the alteration zoned class

from the unaltered fresh rocks classes and the River Nile one (Figure 7).

4. GIS Geospatial Analysis

The obtained classified maps (Figure 7) are vectorized to polygon feature class and

reclassified, whereby alterations layers from both maps are extracted to two new layers.

Geospatial overly analysis by intersect processing give new alteration map. This final GIS

layer directly depicts alteration zones from both original images (Figure 8).


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(A) (B)

Figure 7: Supervised classified maps of the Sabin’s color composite image, (A), and Crosta

colored alteration image (B).

Figure 8: Alteration map produced after the spatial analysis of the classified transformed

images, overlay on the satellite imagery and the geological map.


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5. Results and discussion

The results obtained from band transformations process in Figure (5 a), shows the band ratio

3/1 in grey-scale, the image depicts high iron oxide minerals signature on alteration areas as

well as on sedimentary rock and alluvial wadi deposits. This is attributed to the ferruginous-

capping of the sedimentary sandstones and the richness of these minerals in the alluvial wadi

deposits. On the other hand, hydroxyl-bearing minerals images (Figure5 b) exhibits high

signature in similar alteration zones. Similarly, high signals displayed over the Nile silts and

alluvial wadi deposits, which attributed to their high contents of clay minerals. It is clear that

both band ratio images are not enough in displaying the alteration zones in term of the grey-

scale image (Figure 5(a) and (b)). The produced Sabins’s ratioing colour composite image

(band ratios 5/7 in red, 3/1 in green and 3/5 in blue) displays target zones in distinguishable

crimson red hues (Figure 5 c). Some of these alterations attributed to the alteration zones and

others related to weathering products of the ferruginous sandstones and basic-ultrabasic rocks.

Statistical results of eigenvectors loading of the Principal Component transformation for the

four selected bands 1, 3, 4 and 7, show that the PC4 has good contrast in the values between

band 3 and band 1 to differentiate areas with high content of iron oxide minerals of alteration

zones (Table 1). However, the obtained F-image is unsatisfactory (Figure 6 a), high values of

iron oxide minerals in many parts, on alteration zones, in alluvial sediments, the

metasediments and parts of the sedimentary sandstones. In another hand, H-image that

defining the hydroxyl-bearing minerals have been generated after the Principal Component

analysis being applied to the selected bands 1, 4, 5 and 7. Statistics show that the PC4 has

good contrast in the values between band 5 and band 7 to differentiate areas with high content

of clay minerals of alteration zones (Table 2). The obtained H-image (Figure 6.b) displayed

high values on alluvial deposits and over many other places. The Crosta’s color image

portrays the suspected alteration zones in brighter yellowish orange and whitish hues (Figure

6. C). High signals define extended alteration zones. Undesirable similar hues resulted from

the alluvial sediments in drainage system; this attributed to their high contents of the clay

minerals.

Simple supervised classification have been carried out on both colored composite images

(Sabin’s and Crosta’s), the high separability of the training areas encourage using the

maximum likelihood algorithms. The classified maps define eight main classes. Raster to

vector conversion produced eight-class polygon layer. The geo-spatial analyses have been run

on the extracted alteration zones class layers. A new intersected alteration zones layer

expresses the correlated high signals in both images.

Figure (8) exhibits the result of the digital image enhancement of remotely sensed data and

the geospatial analysis for the study area, which portrays alteration zones related to gold

mineralization. These alterations appear as extended zone aligned parallel to Jebel Qurun –

Jebel El Kaweiyit, highly associated with the basic and ultrabasic rocks and the associated

metacherts in the area. Other small alteration spots appear in the southern area at alluvial

wadis, these related here to the weathering products of the weathered metabasites and the

carbonate rocks.

5.1 Conclusions

This work demonstrate that the utilizing of remote sensing and GIS techniques in geological

mapping and mineral exploration. It proved that digital image processing can afford

exploration criteria for quick and fast exploration projects. In this study Landsat 7 ETM +


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data was used to study the area around Abiydia town, the River Nile State, North Sudan. Dual

transformation methods were applied for mineral exploration. The band ratioing technique is

generated to enhance the mineralized areas by spectral signatures of iron oxide and clay

minerals in the alteration zones. Feature Oriented–Principle Component transformations

(Crosta’s image) have been utilized for the same purpose. Two lithological maps

demonstrating different lithological units associated alteration zone have been produced after

supervised classification. The depicting of alteration zone is carried by GIS-geospatial

analysis in both maps. The resultant map shows that these zones are associated with basic and

ultrabasic rocks and the associated metacherts.

However, these technique is should be taken with cautious because some lithologies possess

similar spectral signatures, such a drawdown can be overcome by integrating the structural

data in the geospatial analyses.

Acknowledgements

The authors highly acknowledge the Faculty of Petroleum and Minerals, Al Neelain

University to sponsor and facilitate the study. Remote Sensing group of Prof. List at FU-

Berlin are acknowledged for providing satellite data and facilities of digital image processing.

Rida Mining Company is thanks for hosting during fieldwork.

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Digital image processing and geospatial analysis of ... · PDF fileDigital image processing and geospatial analysis of landsat 7 ETM+ for mineral exploration, Abidiya area, North Sudan