1. science
2. geology

Ministry of
Minerals
Geological
Researches
Authority of Sudan
By:
Roaa A.Azeem
Projects planning Dep., The Geological Researches Authority of Sudan, Sudan
Out lines
•Introduction
•Study area
•Objective
•Methodology
•Lithology investigation
•Processing Techniques
•Result
•Conclusion
SUDAN
General:
Area: 1.882.000 square kilometers
Population: 33,419,000 persons
It is neighbored by sevencountries
Economy
The back bone of Sudan
economy is Minerals, Agriculture
supported by huge animals wealth.
 Cement production have also
begun to be important to the
Sudanese economy.
•Introduction
Limestone is one of the most important economic
industrial materials in cement manufacturing and other
industries.
Objective
The main objective of this paper is to give an idea of the
applications of the remote sensing technology in detection of
limestone.
The challenge
is to find way for identify limestone in a regional scale.
SAVE..time, money.
Improving and updating of geological mapping.
Increasing of the national income.
Study area
Atbara area is located in the River Nile State
of the Sudan
APPLICATION
Kadabas
TEST
Atbara
Marble Quarry
Atbara
•Methodology
1- Remotely sensed data (ETM+, TM)
2- Lithology Investigation
3- using of principal component and bands combination for investigating limestone
Using software ENVI4.5 (The Environment for Visualizing Images)
1. PCA
principal Component Analysis
2. Choosing uncorrelated data
Lithology Investigation
GEOLOGY
Marble in this area belongs to the meta-sedimentary part of
Kurmut Series.

Kurmut Series consists of meta-sediments such as
marbles, calc-silicate rocks, quartzites, paragneisses,
mica schists and graphitic schist with intercalations of
metavolcanic rocks and basic dykes.
 The marble bands are well foliated and folded with
fold axes plunging in different directions with N and NE
axial planes

Processing Techniques
1. PCA
principal Component Analysis
Row data
PC data
Uncorrelated,
Wide range
Highly Correlated, narrow
range
Using software ENVI4.5 (The Environment for Visualizing Images)
 Our methodology is based on the Principal Component Analysis (PCA)
 PCA is used to convert raw remote sensing data of multi-spectral
imageries into a new principal component image, which is more easily
interpretable.
 PCA is a statistical technique widely used in RS to choose the suitable
bands and to show spectral differences which helps to display clearly
the correlation of the spectral values between the different channels.
Processing Techniques
2. Choosing uncorrelated data
• PC analysis shows spectral differences which helps to display
clearly the correlation of the spectral values between the
different channels.
• After Principal Component transformation, visual inspection
of the PC color composites indicates that the composite
containing the PC1,PC2, PC3, PC4 were the most informative
mainly for the limestone formation.
Processing Techniques
3. Bands combination
1
1. Color Composite of bands 7,4,1 in (RGB) express
more geological information and provide higher
contrast between units than the conventional
color Images Fig.1.
2. PC A ratio of PC1,PC2,PC3,PC4 gives sharp
spectral response of the limestone, so the
combination of PC2/PC4/PC1 for TM image Fig.2
and PC4/PC3/PC2 for ETM+ Fig.1 gives a very
distinctive results.
2
3
PC2
PC3
1- PC2, PC4 and PC1
indicating high and good contrast
for limestone (TM).
PC4
PC4/3/2
2- PC4, PC3 and PC2
Best bands combination of ETM+ in RGB
3- Accurate map
Has been established
1. Sudan had seven cement plants with a combined capacity of 10.1
million metric tons per year (Mt/yr).
2. National cement production increased to nearly 3.48 Mt in 2012 from 3
Mt in 2011 and 246,500 metric tons (t) in 2008. Output increased
because of the expansion of Al-Rajhi Group’s Atbara plant and the
opening of six new plants from 2008 to 2011 (International Cement
Review, 2011; Bank of Sudan, 2013a, p. 142).
3. New plants
• Al-Rajhi Group produced about 1.12 Mt of cement
• ASEC Cement Co. of Egypt (690,800 t.)
• Berber Cement Co., 605,700 t.
• Al-Shamal Cement Factory, 551,600 t.
• Al-Salam Cement Production Company Ltd. 288,300 t
• Nile Cement Company Ltd., 149,100 t.
• Aslan Cement Co., 68,700 t.
The increase in production was broadly based in 2012, with output
increasing at all plants except for ASEC and Aslan
(Bank of Sudan, 2013a, p. 142).
Remote Sensing techniques are an efficient tool for geological mapping.
 This study showed that the Principal Component analysis processing
technique is more efficient in discrimination and delineation of limestone
units and their regional extension.
The data obtained by this study were applied for the extension of Atbara
cement factory and will be very useful forfuture new cement manufacturing.
Strongly recommended, as indicated by this
study, to integrate processed remotely sensed
data and available geologic information to
locate and determine the limestone rocks in
other areas of similar conditions.