ARTICLE IN PRESS

0969-8043/$ - se

doi:10.1016/j.ap

�Correspond963 11 6112289.

E-mail addr1Unit of radi

Applied Radiation and Isotopes 62 (2005) 649–661

www.elsevier.com/locate/apradiso

Statistical factor analysis of aerial spectrometric data,Al-Awabed area, Syria: a useful guide for phosphate and

uranium exploration

J. Asfahani�, M. Aissa, R. Al-Hent

Geology Department, Atomic Energy Commission, P.O. Box 6091, Damascus, Syria

Received 26 June 2004; accepted 20 August 2004

Abstract

Factor analysis provides a quantitative interpretation for synthesizing and correlating data from airborne

spectrometric surveys. Factor analysis is applied on such data of Al-Awabed area, Northern Palmyrides. The seven

variables used in this research are: total radioactivity Ur1, eU, eTh, K%, eU/eTh, eU/K and eTh/K. The analysis and

interpretation show that a model of four factors (F1, F2, F3 and F4) is sufficient to represent them, where 94% of total

data variance is interpreted. Mapping of these four factors proved to be a powerful tool for a direct differentiation of

various rocks units, and a score lithological map of 11 radiometric units was established.

r 2004 Elsevier Ltd. All rights reserved.

Keywords: Uranium phosphate prospecting; Airborne spectrometric survey; Syria

1. Introduction

An airborne radiometric survey was carried out

during a project conducted in 1987 on some Syrian

regions in cooperation with the International Atomic

Energy Commission and Riso national laboratory SYR/

86/005 (Jubeli, 1990). It was found that gamma-ray

anomalies are mainly associated with phosphate depos-

its encountered in central Syria. The richest phosphorite

outcrops are in central southern Palmyrides, where they

have been economically mined from two mines for many

years, Khneifis and Al-Sharquieh, which are located

65 km and 45 km southwest of Palmyra, respectively

(Fig. 1). This paper presents a reinterpretation of the

airborne radiometric data of new phosphate deposits

e front matter r 2004 Elsevier Ltd. All rights reserve

radiso.2004.08.050

ing author. Tel.: +963 11 6111926; fax:

ess: jasfahani@aec.org.sy (J. Asfahani).

oelement (IAEA, 1976).

discovered through the airborne radiometric survey in

The Northern Palmyrides. This new discovery is based

on the proved relationship between radioactivity and

phosphate content. In fact, the total radioactivity (Ur)

map of the Northern Palmyrides from the airborne

survey shows a long narrow strip of anomalous total

radioactivity extending NE from Wadi Al-Awabed,

28 km northwest of the T4 oil pump station (Jubeli,

1998). Initially, the anomalous strip was linked with the

well-known phosphate deposits of Al-Rakheim. How-

ever, ground follow-up investigation of the anomalies

revealed another significant deposit represented by four

phosphate beds that outcrop in Wadi Rasm Al-Awabed.

The phosphate beds thicknesses ranges from 80 cm to

1.25m each with a total thickness of nearly 4m, and an

average P2O5 of 19.4% (Technoexport, 1967).

The main objective of this research is the reinterpreta-

tion of airborne gamma-ray spectrometric data of the Al-

Awabed area by using factor analysis technique, in order

to reconstruct a scored lithological map of the

d.

ARTICLE IN PRESS

Fig. 1. Simplified geological map of the Palmyrides Central Syria, showing Phosphatic deposits.

J. Asfahani et al. / Applied Radiation and Isotopes 62 (2005) 649–661650

outcropping units. In fact, this technique is considered as a

powerful tool in providing a better description of the

geophysical data, and an assessment of the underlying

factors controlling their variance. Statistical characteristics

of each radioelement (eU, eTh, K%), and their ratios (eU/

eTh, eU/K, and eTh/K) are also examined for determining

and outlining the significant radiometric anomalies

occurring through the choice of a statistical threshold

value of two standard deviations plus the arithmetic mean.

2. Geological setting

The Palmyrides are located in Central Syria and are

subdivided into northern and southern ranges separated

by an intermontane extensive basin filled with Neogene–

Quaternary deposits, i.e., Ad-Ddaw. Sedimentary forma-

tions exposed in the Palmyrides range in age from the

Upper Triassic to Neogene (Fig. 1); among these, the

Soukhneh group is characterized by its significant

phosphorite deposits (Al-Maleh and Mouty, 1994). It is

composed mainly of two rock types: calcareous and

siliceous. The first type is dominated by limestone, marly

limestone, limy marl and marl with characteristic limy

concretionary structures of few centimeters up to 2m in

size. The siliceous rocks are composed of thin layered flint

bands, lenses and nodules. The Soukhneh group is divided

into two lithological formations (Rmah and Swwaneh).

Fig. 2 shows a typical geologic column of phosphatic

deposits in Central Syria (modified by Jubeli, 1998).

Phosphatic layers thicken in the Central Palmyrides and

thin eastwards until they pinch out under marl Arak and

Tantour formations. Phosphatic deposits in Syria can be

classified in two types, A and B (Fig. 1). Type A presents

the Upper Cretaceous phosphates, while Type B presents

Paleogene (Lower Eocene) Syrian Desert phosphorites.

ARTICLE IN PRESS

Fig. 2. Geological column of phosphatic deposits in central Syria.

J. Asfahani et al. / Applied Radiation and Isotopes 62 (2005) 649–661 651

The phosphorite deposits in the region are

attributed to enrichment processes involving

phosphorus and plankton particles which indicates

a paleogeographic evolution related to Cenonian

transgression and the subsidence of the Arabian

Platform.

In addition, they are associated with primary and

secondary uranium mineralization. The former is

associated with phosphate precipitation while the latter

fills open cracks and pores, due to surface and subsur-

face water percolation (Abbas, 1987). Fig. 3 shows the

geological map of the Al-Awabed area.

ARTICLE IN PRESSJ. Asfahani et al. / Applied Radiation and Isotopes 62 (2005) 649–661652

3. The airborne radiometric survey

The airborne radiometric survey was carried out using

a compact, lightweight, four windows gamma-ray

spectrometer (Scintrex GAD-6, Canada) with a detector

of 12.5 L NaI(Tl) volume. The detector was maintained

at constant temperature and the gain was stabilized

before recording each mission. The system calibration

took place at the calibration pads at the Dala airport in

Sweden (Riso, 1987). An IGI Loran-C navigation

system was used to provide efficient flight path control.

It defines and records automatically all the waypoints

and fiducials of the flight tracks along the flight lines.

Details of the equipment and the survey operations can

be found in (Riso, 1987). The area covered by the

airborne survey consists of the following three areas:

�

The Syrian Desert (7189 line km at 4 km line spacing).

�

Ar-Rassafeh Badyieh (2240 line km at 4 km line

spacing).

�

The Northern Palmyrides range (1600 line km at 3 km

spacing).

In all cases, a constant terrain clearance of 30m was

maintained as a standard survey height and the aircraft

speed was 120 km/h.

Fig. 3. Geological map o

Settings of the four gamma-ray energy windows are

listed in Table 1. Fig. 4 shows the regions surveyed and

the resulting radiometric map.

The research area is located in the Northern

Palmyrides to the northwest of T4 oil pump station,

and is situated between 371300000 0E and 371450000 0E, and

between 3414l0300 0N and 341540000 0N. Fig. 5 shows the

surveyed eight E–W oriented parallel flight lines, and the

resulting radiometric map. Ur, eU, eTh and K% were

measured at 5190 stationpoints, as were the coordinate

points by Loran-C.

4. Statistical analysis of the data

Radioactive measurements acquired by the spectro-

metric gamma technique applied in the research area

were subjected to quantitative and qualitative statistical

analysis in order to draw a valid conclusion regarding

the nature and significance of the distribution of the

radioelements in it. The applied statistical analysis

includes single variate and bivariate statistics. In

addition, some quantitative statistical measures were

determined, such as the threshold levels, frequently

defined as the mean plus two standard deviations, which

indicates the beginning of anomalous values.

f Al-Awabed area.

ARTICLE IN PRESSJ. Asfahani et al. / Applied Radiation and Isotopes 62 (2005) 649–661 653

4.1. Single variate analysis

Single variate statistics were used to describe the

statistical characteristics of the distribution of each

radioactive variable. These include range, arithmetical

Table 1

Specification of the counting windows

Window

designation

Window setting

(MeV)

Radioisotope

mainly detected

Potassium 1.38–1.56 40K

Uranium 1.66–1.90 214Bi

Thorium 2.44–2.77 208Tl

Total-count 0.40–2.77

Fig. 4. A: Areas surveyed by airborne gamma-ray spectrometry

mean ðx̄Þ; measures of dispersion of the data and

standard deviation (s), as shown in Table 2.

4.2. Bivariate analysis

Correlation analysis has been applied as a bivariation

statistics in order to examine the mutual relations and

strength of association between pairs of variables

through calculation of the linear Pearson product

moment correlation coefficient ‘‘r’’.

4.3. Factor analysis

It is a multivariate statistical technique by which

variables on a set of samples are linearly combined

. B: Radiometric map resulting from spectrometric survey.

ARTICLE IN PRESS

Fig. 5. A: Flight lines of the spectrometric airborne survey in Al-Awabed area. B: Resulting total radioactivity (Ur) in Al-Awabed

area.

Table 2

Statistical characterestics of the 7 radioactive variables in Al-Awabed area

Variable Case number Min Max X̄ s CV% � X � 2s

Ur 5190 0.03 25.90 5.88 3.11 52.89 12.1

K% 5190 0.02 0.72 0.265 0.103 38.86 0.471

eU 5190 0 22.33 3.04 2.69 88.57 8.417

eTh 5190 0.29 8.06 3.012 1.14 37.84 5.29

eU/eTh 5190 0 16.77 1.20 1.32 109.6 3.844

eU/K% 5190 0 254 13.50 15.23 112.8 43.96

eTh/K% 5190 1.72 105 12.29 5.21 42.39 22.71

CV: coefficient of variability ð¼ s=X̄n100Þ:

J. Asfahani et al. / Applied Radiation and Isotopes 62 (2005) 649–661654

ARTICLE IN PRESS

Table 5

The four rotated factors

Factor variable 1 2 3 4

Ur 0.926 0.091 0.340 0.082

K% 0.024 0.478 �0.824 �0.011

eU 0.986 0.039 0.0142 0.075Th

J. Asfahani et al. / Applied Radiation and Isotopes 62 (2005) 649–661 655

giving rise to new fundamental factors, which can be

named and interpreted based on geological reasoning.

The number of variables is reduced to a minimum

number of independent variables, which will adequately

describe the data.

This technique has been applied on airborne gamma-

ray spectrometric data from a survey performed in

South Texas (Duval, 1976), in the Colorado quadrangle

(Wecksung, 1982), and in several prospected areas in

Egypt (Moustafa et al., 1990).

Using this technique, a system of factors is obtained

through the transformation of the three radioelements

(eU, eTh, and K%), their ratios (eU/eTh, eU/K%, and eTh/

K%), and the total radioactivity (Ur). These new factors

are constrained to reproduce as much as possible the

total variance of the original data. Each original data

point gains factor scores, representing the affiliation of

the samples to the newly defined factors. The mapping

of factor scores produces a set of new maps. Compara-

tive study of these maps with a geological map serves as

a powerful tool in reinterpreting the data to provide

direct differentiation of all rocks units on a lithological

score map.

e �0.091 �0.221 �0.915 0.0748

eU/eTh 0.854 0.149 0.299 �0.144

eU/K% 0.80 �0.326 0.261 �0.372

eTh/K% �0.05 �0.982 �0.0057 �0.027

Eigenvalue 3.126 1.695 1.588 0.155

% 44.654 24.215 22.688 2.22

Cum% 44.654 68.867 91.557 93.777

5. Results and discussion

By applying a single variate analysis, the statistical

characteristics of the distribution of each radioactive

Table 3

Correlation matrix of the 7 radiometric variables in Al-Awabed area

Variable Ur K% eU

Ur 1

K% 0.35 1

eU 0.92 0.03 1

eTh 0.21 0.65 �0.11

eU/eTh 0.69 �0.15 0.85

eU/K% 0.59 �0.35 0.76

eTh/K% �0.14 �0.47 0.09

Table 4

Unrotated factors

Variable F1 F2 F3

Ur 0.964 �0.134 0.202

K% 0.125 �0.755 0.531

eU 0.982 0.0611 �0.099

eTh 0.00091 �0.186 0.928

eU/eTh 0.82 0.094 �0.417

eU/K% 0.73 0.533 �0.204

eTh/K% �0.108 0.88 0.424

variable are determined for the Al-Awabed area

(Table 2).

The maximum equivalent uranium in the studied area

is 22.33 ppm, with an average of 3.04 ppm and a

standard deviation of 2.69 ppm.

Review of the computed coefficient of variability (CV)

of the radiometric variables (eU, eTh, and K%) showed

that uranium exhibits a relatively high value (88.57%),

when compared with those of thorium (37.84%) and

potassium (38.86%). A higher coefficient of variability

implies a lower degree of homogeneity. In other words,

the observed relative tendency of uranium toward

heterogeneity is interpreted to be attributed to the

relatively higher mobility of the uranium in comparison

eTh eU/eTh eU/K% eTh/K%

1

�0.39 1

�0.27 0.77 1

0.23 �0.19 0.29 1

F4 F5 F6 F7

0.0018 0.09 �0.008 0.03

0.194 0.12 0.03 0.002

�0.057 �0.002 0.0004 0.00

0.066 0.008 �0.003 0.00

0.116 0.006 0.004 0.00

0.307 0.1 0.002 0.00

�0.052 �0.02 0.003 0.00

ARTICLE IN PRESSJ. Asfahani et al. / Applied Radiation and Isotopes 62 (2005) 649–661656

with Th and K, which show relatively higher stability

under the same conditions.

Asfahani (2002) adopted this concept as a critical

parameter distinguishing between phosphatic rocks and

phosphatic sands in Khneifiss mine by interpreting

natural gamma-ray well logging measurements through

a statistical approach.

Table 6

Factor score coefficients

Variable F1 F2 F3 F4

Ur 0.509 �0.00124 �0.796 0.119

K% �0.0576 0.128 �0.382 �0.465

eU 0.341 �0.069 0.665 1.452

eTh �0.661 �0.102 �0.376 �0.113

eU/eTh 0.0622 0.0553 0.0745 �0.221

eU/K% 0.155 �0.044 �0.025 �1.67

eTh/K% 0.0038 �0.883 �0.125 0.371

Fig. 6. Score map of F1

Bivariate correlation analysis is also carried out, and

the coefficient matrix between the seven data variables in

the research area is shown in Table 3.

This correlation matrix shows a cluster of high

positive correlation between three variables (Ur, eU

and eU/eTh), High positive correlations have also been

found between eU/eTh and eU/K (0.77), and between eU/

eTh and eU (0.85).

The above matrix is used to obtain the unrotated

loading matrix of Table 4. The unrotated factors are

difficult to be interpreted, and therefore it is necessary to

rotate them into another form, which is equivalent to the

original unrotated matrix, but represents factor con-

struction. This can be achieved by using the varimax

method (Comery, 1973), which allows a reduction from

the data system of seven dimensional factors into four

principal factors (F1, F2, F3 and F4) without losing

significant information.

The four rotated factors are quite interpretable and

represent 94% of the total system information, which is

in Al-Awabed area.

ARTICLE IN PRESS

Fig. 7. Score map of F2 in Al-Awabed area.

J. Asfahani et al. / Applied Radiation and Isotopes 62 (2005) 649–661 657

sufficient to interpret the variable data as shown in

Table 5.

A high eigen value indicates the importance of each

factor for data representation. Factor 1 has a value of

3.126, whereas the other factors have lower values,

which indicates that the first factor is the most important

for representing the variation in the measurements.

The factor score coefficients of the four factors, shown

in Table 6, allow the construction of four standards

factor score maps (Figs. 6–9).

F1 explains 44.65% of the total variance, and has high

loading values of 0.926, 0.986, 0.854, and 0.8 for the

variables of total radioactivity (Ur), eU, eU/eTh, and eU/

K%, respectively (Table 5). This factor is therefore

composed of these four variables, and is directly related

to the U presence in the phosphate deposits outcropped

in the Al-Awabed area. Therefore it might be termed

uranium phosphate factor (U–P factor).

More than 43 detailed lithofacies cross-sections have

been established in the research area (Fig. 3) eight of

which were selected by F1.

Fig. 10 shows the correlation of the chosen lithofacies

cross-sections according to the profile P1–P2 of a

NE–SW direction. The thickness of the phosphatic layer

varies between 20 and 240 cm. Radioactive measure-

ments have been carried out along cross-sections by the

French SPP2 Saphymo. Phosphatic layers radioactivity

varies between 120 cps to more than 450 cps reflecting

P2O5 content and U concentration, since a positive

relationship between uranium concentrations and phos-

phate content have been established in most world

phosphate deposits (Afteh, 1967; Gavshin et al., 1974;

Altschuler, 1980; Abbas, 1987; Asfahani and Kamarji,

1996; Jubeli, 1998; Asfahani, 1999, 2002; Asfahani and

Abdul-hadi, 2001).

The second factor (F2) explains 24.21% of the

variability of the geophysical data. It is relatively highly

loaded for K% variable (0.478), and inversely highly

loaded for the ratio of eTh/K% (�0.982). This factor is

related to K presence and can distinguish between

different lithostratigraphic units according to their

alkalinity, therefore it can be termed a limestone factor

ARTICLE IN PRESS

Fig. 8. Score map of F3 in Al-Awabed area.

J. Asfahani et al. / Applied Radiation and Isotopes 62 (2005) 649–661658

due to its association with chalky limestone intercalated

with siliceous and marly clay. The N–S deep drainage

network’s effect is incorporated in such facies with the

factor (F2) map, Fig. 7. This factor seems to be divided

into four variable levels, depending on carbonate and

marly clay contents in the lithostratigraphic units.

The third factor (F3) explains 22.69% of the data

variability, and is inversely highly loaded with K% and

eTh, where the loading values are �0.824 and �0.915,

respectively. This factor reflects tectonic effects, espe-

cially in the zones of hard rock exposures that are

fractured and faulted in NW and SE of the studied area.

Therefore, this factor can be termed fracturing factor.

According to this factor, connected with hard rocks

like limestone, dolomitic limestone, three classified

levels, were set.

The fourth factor (F4) explains only 2.22% of the

data variability, and is inversely loaded with the ratio of

eU/K% (�0.372). At this stage of research it is difficult

to be precisely determined, though it may be connected

with accumulated erosional products of phosphate rocks

in wadis and lowlands.

Eleven interpreted lithofacies units are determined

through the comparison and matching of the three

mentioned score maps with the geological map of the

study area, as shown in Fig. 11. Table 7 shows the

ranges of the standard factor scores characterizing the

outlining rock units of Al-Awabed area.

The investigation of the standard factor score map of

Fl, (Fig. 6) indicates clearly the outlining of the

following phosphatic highly radioactive rocks:

P1:

Detrital phosphate sand with fish bones and flint

fragments.

P2:

Soft phosphate rocks with siliceous and calcareous

nodules.

P3:

Phosphate rocks with siliceous and calcareous

nodules.

P4:

Marly phosphate, interbeded with siliceous and

calcareous beds.

ARTICLE IN PRESS

Fig. 9. Score map of F4 in Al-Awabed area.

J. Asfahani et al. / Applied Radiation and Isotopes 62 (2005) 649–661 659

The standard factor score map of F2 (Fig. 7) is capable

to distinguish the following geological units:

M1:

Marly beds with calcareous nodules.

M2:

Organic limestone with siticeious intercaleted bands.

M3:

Alternating of limestone and marly clay beds.

M4:

Topsoil and eluvium.

The standard factor score map of F3 (Fig. 8) distin-

guishes the following geological units:

C1:

Bio. Dolomitic limestone and clastic limestone.

C2:

Marly limestone interbedded with siliceous bands.

C3:

Chalk like limestone, noduler limestone, clay with

baryte concretion.

6. Conclusion

Factor analysis enables geologists and geophysicists

to produce rapid radiometric score maps with a

minimum amount of subjectivity. The resulting score

maps have the advantages that rock types are better

correlated on the basis of all variables rather than on a

subjective correlation and compilation of individual

profiles or contour map. This analysis provides a useful

guide to a field geologist to extend his knowledge on the

geology of an area under study to prepare a preliminary

geological map, with areas of anomalous geophysical

character indicated by certain patterns.

The computed factor scores are directly used and

matched with a geological map of the area to

differentiate between various lithological units. A scored

lithological unit map is consequently established, in

which 11 units have been distinguished.

Factor 1, termed Phosphate Uranium, is the most

important in this research. The other two factors 2 and 3

are related to the alkalinity and to fracturing zones,

respectively.

The factor analysis technique can be efficiently

applied in other interesting areas in regions under

survey for solving geological problems related to

uranium and phosphate prospecting.

ARTICLE IN PRESS

Fig. 10. Lithofacies cross-section, showing lateral variations of phosphate beds thickness and radioactivity, Al-Awabed area.

Fig. 11. Radiometric lithological score map of Al-Awabed area.

J. Asfahani et al. / Applied Radiation and Isotopes 62 (2005) 649–661660

ARTICLE IN PRESS

Table 7

Standard factor score characterizing the rock units of Al-Awabed area

Factor Class From To Rock unit

F1 P1 4400 Phosphatic sand

P2 300 400 Soft phosphate rocks

P3 200 300 Phosphate rocks

P4 o200 Marly phosphate

F2 M1 450 Marl, Calcareous nodules

M2 25 50 Organic limestone, Flint bands

M3 0 25 Marly clay limestone

M4 o0 Top soil, eluvium

F3 C1 4100 Dolomitic limestone

C2 0 100 Marly limestone

C3 o0 Chalky limestone

J. Asfahani et al. / Applied Radiation and Isotopes 62 (2005) 649–661 661

Acknowledgement

The authors would like to thank Dr. I. Othman, The

General Director of Syrian Atomic Energy Commission

(SAEC), for his interest and permission to publish this

research.

References

Abbas, M., 1987. Geochemie de l’uranium des phosphorites des

Palmyrides Centrals, Syrie. These Sci. Univ. Louis Pasteur

Strasbourg, France, 166pp.

Afteh, S., 1967. The phosphate deposits of Syria, unpublished

Ph.D. Thesis, Kings College, University of London, 348pp.

Al-Maleh, A.Kh., Mouty, M., 1994. Lithostratigraphy of

Senonian Phosphorite deposits in the Palmyridean region

and their general sedimentological and paleogeographic

framework, Proceedings of 29th International Geological

Congress, Part C, pp. 225–232.

Altschuler, Z.S., 1980. The bearing of geochemistry on the

recovery of uranium and rare earth in phosphorites.

Proceedings of the 2nd International Congress, Phosphorus

Compounds, Boston, April 1980, pp. 605–625.

Asfahani, J., 1999. Determination of radioactive and phospha-

tic layers by measuring gamma-ray intensities in well logging

in the south Al-Abter region in Syria, using numerical

methods of analysis. J. King Abdulaziz Univ. Sci. 11, 39–51.

Asfahani, J., 2002. Phosphate prospecting using natural

gamma-ray well logging in the Khneifiss Mine, Syria.

Explor. Min. Geol. 11 (1–4), 61–68.

Asfahani, J., Abdul-hadi, A., 2001. Geophysical natural

gamma-ray well logging and spectrometric signatures of

South AL-Abter phosphatic deposits in Syria. Appl. Radiat.

Isot. 54 (3), 543–577.

Asfahani, J., Kamarji, Z., 1996. The automatic interpretation of

natural gamma-rays in well logging of the phosphatic

deposits in the Palmyra region in Syria. Appl. Radiat. Isot.

47 (516), 591–598.

Comery, A.L., 1973. A First Course in Factor Analysis.

Academic Press, New York, 316pp.

Duval, I.S., 1976. Statistical interpretation of airborne gamma-

ray spectrometric data using factor analysis. In: Proceeding

of a Symposium on Exploration of uranium ore deposits,

IAEA. SM-208/12, Vienna, pp. 71–80.

Gavshin, V.M., Bobrov, V.A., Zorkina, L.S., 1974. Quantita-

tive relation between uranium and phosphorus in phos-

phorites and phosphatic sedimentary rocks. Litho. Min.

Deposit, 6, pp. 118–126 (English transl. pp. 740–746).

IAEA, 1976. Radiometric reporting methods and calibration

in uranium exploration. Technical Report Ser. No.

174, 57p.

Jubeli, Y.M., 1990. Final report on uranium exploration in

Syria SYR/86/005. UNDP, IAEA and SAEC (in Arabic).

Jubeli, Y.M., 1998. The role of airborne radiometric survey in

defining the distribution of phosphate rocks in Syria desert

and the northern Palmyrides. Explor. Min. Geol. 6 (3),

269–278.

Moustafa, M.E., Rabie, S.I., El-Rakaiby, M.L., 1990. Rock

unit mapping using factorial analysis applied to airborn

gamma-ray spectrometric data, West G. Gattar area, Egypt.

Ann. Geol. Surv. Egypt. V.XLV, 295–300.

Riso, 1987. Aerial gamma-ray in Syria YR/87/005.

Technical Report, Riso National Laboratory, Roskilde,

Denmark.

Technoexport, 1967. Explanatory notes on the geological map

of Syria, mineral deposits and underground-water re-

sources. Ministry of Geology, USSR, 1967.

Wecksung, G.W., 1982. A factor analysis approach for

comparing aerial radiometric with other related data sets.

Special Research Workshop. Geophysics pp. 408–409.