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Grandjean G., Paillou Ph., Baghdadi N., Heggy E., August T. , and Lasne Y., 2006. Surface and subsurface structural mapping using low frequency radar. A synthesis of the Mauritania and Egyptian experiments. Journal of African Earth Sciences (JAES), vol. 44, pp. 220-228.

Surface and subsurface structures mapping using low frequency radar. A synthesis of the

Mauritanian and Egyptian experiments

1G. Grandjean,

2Ph. Paillou,

1N.Baghdadi,

3E.Heggy,

2T.August, et

2Y.Lasne

1BRGM, Orléans, France (g.grandjean@brgm.fr).

2Observatoire Astronomique de Bordeaux, Floirac, France

3Université du Caire, Egypte.

Abstract

Satellite imagery allows high-precision coverage of broad areas while significantly reducing exploration costs. It provides

valuable information for geological mapping and mineral exploration, since it brings out structures such as lineaments, faults,

lithological contacts, etc. Particularly, the use of radar imagery constitutes a very useful complement to optical images, especially as

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regards the surface but also the subsurface structures detection. Actually, in desert areas, radar waves penetrate the dry surface

sand layer and highlight concealed geological structures or fossil river systems. We present here a synthesis of two experiments

designed to compare the contribution of radar and optical images to geological exploration. Studied sites were in the regions of

Akjoujt in Mauritania and Bir Safsaf in Egypt. In the case of subsurface penetration of the radar wave into the sand layer, the

geological radar or GPR (Ground Penetrating Radar) is a use to confirm the volume-related origin of the backscattering. The

confirmation technique consists in correlating the reflectivity of the GPR section with the backscattering of the radar image. Several

sites were studied in the both regions above-cited. Radar imagery, clearly demonstrates their capacity for high-precision detection

of surface geological structures, whether they are vein-type, lithological, or paleohydrogeological in nature. Their value is evident for

arid environments, where outcrops can be distinguished on the basis of their specific roughness. We also confirmed in that work

that low frequency radar (L-band) can retrieve information about subsurface structures down to a couple of meters deep, where

optical sensors cannot.

Introduction

Exploration for natural resources inevitably involves the mapping of geological structures; the extent of the areas to be

mapped and the optimization of cartographic surveying thus become significant issues. Satellite imagery allows high-precision

coverage of broad areas while significantly reducing exploration costs. It provides valuable information for geological mapping and

mineral exploration, since it brings out structures such as lineaments, faults, lithological contacts, etc., and enables identification of

mineral occurrences through analysis of their spectral signatures. In recent years, numerous optical sensors equipped with imaging

devices for acquiring a variety of spectral and radiometric information have been launched (SPOT, LANDSAT, ASTER, HYPERION,

etc.); this has led to improvements in geological interpretation (Emran et al., 1996; Kettles et al., 2000; Hubbard et al., 2003; Kruse

et al., 2003). Similarly, the contribution of SAR (Synthetic Aperture Radar) imagery has proved to be particularly useful. Radar

sensors provide valuable information on geological structure and lithology, by giving geologists data that characterize the

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geomorphological landscape. The use of radar imagery constitutes a very useful complement to optical images, especially as

regards surface but also subsurface structures. In desert areas, radar waves penetrate the dry surface sand layer and highlight

concealed geological structures or fossil river systems (Farr et al., 1986; Schaber et al., 1986; Schaber et al., 1997; Paillou et al.,

2003; Grandjean et al., in press).

The originality of our approach lies in the combination of GPR (Ground-Penetrating Radar) and SAR data providing a

quantitative interpretation of SAR backscattering from GPR reflectivity. GPR is thus used to derive geometrical and dielectric

characteristics of the subsurface structures. This technique was successfully demonstrated over the Assal region in the Republic of

Djibouti (Paillou et al., 2001) and the Pyla sand dune in France (Grandjean et al., 2001), where we accurately quantified the

penetration capabilities of microwaves, particularly L and P-bands.

This work was designed to compare the contribution to geological exploration of radar and optical images at different sites in

the regions of Akjoujt in Mauritania and Bir Safsaf in Egypt. For each site, we first compare the SAR polarimetric L-band images

with optical ones. In some places where microwaves penetration is supposed to occur, we compare SAR backscattering with GPR

reflectivity in order to discern between surface or subsurface backscattering processes. We first analyze the Mauritania experiment,

mainly concerned with surface interactions, and discuss on the contribution of radar techniques to geological mapping. In a second

part, we focus on the Egypt experiment, where microwaves penetration was observed and validated using GPR. These results,

presented as a synthesis of the work realized within the last four years, open the way for the mapping of subsurface heterogeneities

such as lithology variations, moisture, or sedimentary structures.

The Mauritania experiment

In Mauritania (Fig.1), three representative sites were selected in the southwestern part of the Precambrian Reguibat Shield (an

autochthonous domain) at the boundary with tectonic units of the Mauritanides chain (an allochthonous domain). At the first site,

located at the southern end of the Amsaga area, the Archean basement is composed of migmatitic gneiss and granite belonging to

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the Rag el Abiod migmatitic complex (Barrère, 1967). This basement is cut by basic dolerite veins belonging to several cycles of

various ages (Paleoproterozoic, Mesoproterozoic, Neoproterozoic, and Mesozoic). The second site is located in sedimentary

formations made up of Cambrian-Ordovician units, near an ESE-WNW-trending tectonic contact that corresponds to the boundary

between the autochthonous units in the north and the para-autochthonous and allochthonous units in the south. The third site,

located some 20 km west of the second, corresponds to a partially sand-covered wadi environment.

Figures 2, 3, and 4 illustrate the responses of the radar (SIR-C, X-SAR) and optical (ASTER) sensors over the three study

sites. For sites 1 and 2, we note a good mapping of surface structures represented by a significant surface roughness (presence of

pebbles and micro-relief), with the radar signal increasing strongly with surface roughness. The results confirm the fact that the

sensitivity of the radar signal to surface roughness increases with wavelength. For this reason, the results obtained with the SIR-C

sensor are better in the L-band (wavelength about 23 cm) than in the C-band (wavelength about 6 cm). The X-band (wavelength

about 3 cm) of the X-SAR sensor appears unsuitable, owing to its very weak signal dynamics. Although discrimination is better in

HH polarization than in HV polarization, using the C-band, the polarization effect does not seem to be crucial. Optical imagery offers

a low mapping potential when compared with L- or C-band radar images. In fact, the linear dykes are not detected by the optical

images. Similarly, the circular structures at the second site are hard to interpret on the optical images.

At site 3, we observe a strong backscattering from the river bed. This strong response could be due neither to surface

roughness nor to the presence of moisture, but the surface is very smooth, and covered with fine sand. This response is probably

due to a volume scattering caused by subsurface penetration of the radar wave (into the sand layer). To confirm the volume-related

origin of the backscattering, GPR is used for sounding the subsurface because it enables the local detection and mapping of

structures concealed by the sand. The confirmation technique consists in correlating the reflectivity of the GPR section with the

backscattering of the radar image. Since their level of correlation is satisfactory, we thereby conclude that the origin of the

backscattering lies within the first 50 cm, as indicated by the GPR. This information was also confirmed in the field by examining the

types of deposit present. Beneath the layer of eolian sand, a few centimeters thick, the deposits are clayey and contain grains of

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millimeter size. At the place where the greatest backscattering was observed, the grains reach centimeter size. Therefore, this layer

must indeed be responsible for the observed signal. We will develop a more quantitative comparison between SAR and GPR

signals in the next section, purely dedicated to the study of subsurface effects on radar images.

The Egypt experiment

The Bir Safsaf region is located in the southern Egyptian desert, known as the Dard el-Arba’in Desert (Fig.5). Middle to late

Mesozoic, continental to shallow-marine sediments are covered by active aeolian deposits and quaternary soils referred to as the

Selima Sand Sheet (Issawi, 1972; Maxwell et al., 2001). It is part of the “Uweinat Uplift” which extends from Gebel Uweinat in the

West to Bir Safsaf in the East, underlying an area of about 40,000 km² in which crystalline rocks are exposed (Schandelmeier et al.,

1983). It separates the deep intra-cratonic Dakhla basin from the more shallow basins of Northern Sudan. The northern part of the

Bir Safsaf formation consists of magmatic rocks of mainly granitic composition, with complex intrusive relationships (hornblende-

bearing gneisses, porphyritic granite, abundant dykes). The southern part is mainly composed of red and subordinate grey colored,

medium to coarse grained gneisses and migmatites, and the composition of rocks is mainly granitic. Bir Safsaf outcrops generally

rise a couple of meter above the surrounding plains, and are sometimes hard to observe on Landsat scenes. The typical landscape

is a flat plain, floored by quartzitic sandstones, interbedded shales, and conglomerates of the “Nubia Sandstone” of late Cretaceous

age with outcrops of granite and granitic gneiss of the African Shield of Precambrian age (Schaber et al., 1986). The superficial

sand sheet of the sediment cover is a centimeter to a meter thick eolian deposit covered by a thin lag of quartz granules or small

pebbles. It overlies the granitic bedrock and alluvium containing medium to coarse sand, and calcified pebble gravel (Maxwell et al.,

2001). Structural trends in the Bir Safsaf region are mainly constituted of East-West normal faults.

Bir Safsaf is one of the desert site where sand-buried paleodrainage channels of middle Tertiary to Quaternary age were

discovered using L-band radar images from the SIR-A mission (McCauley et al., 1982; McCauley et al., 1986). Schaber et al. (1986,

1997) have shown from field investigations that the dry sand sheet that covers the Bir Safsaf region can be penetrated by L-band

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frequencies down to one meter. This was also confirmed by laboratory measurements of radar transmission through sand (Williams

and Greeley, 2001). They have shown that widespread alluvial deposits represent the last stage of filling of a former, regionally

extensive, river-valley network that by Quaternary time was reduced to isolated depressions of very low relief. According to

McCauley (1986), field research along the late Quaternary river networks strongly suggests that human occupation sites were

controlled by the patterns of fluvial environments along ephemeral run-off channels. One of the main paleodrainage systems

discovered on SIR-A images, and later confirmed on SIR-B and SIR-C scenes, lies south of Bir Safsaf near Wadi Safsaf. It presents

a complex of channels, each less than 1 km wide, inset into the broader alluvial valley. Large quantities of authigenic calcium

carbonate has formed in surface alluvium during the climatic fluctuations of the late Quaternary, probably generated through

groundwater deposition and mineralization, rhizoliths around plant roots, and calcic soil formation. McCauley and Schaber (1986)

observed various morphologic types for the calcium carbonate found in alluvium, among which irregulary-shaped nodules

(containing more than 70% CaCO3) and vermicular rhizoliths play a key role in backscattered radar signal.

For our further analysis of both SAR and GPR data, we shall consider a simplified model of the near surface stratigraphy that

is consistent with the backscattered radar signal and the regional geology. The five-layers model used is presented in Table 1, the

radar interface (i.e. the place where most of the incident signal is backscattered) being located at the interface between the

compacted sand layer – CSL – and the calcified pebble-gravel – CPG. As it was described by Schaber et al. (1986, 1997), the

incident radar wave penetrates the first modern sand sheet – MSS – and compacted sand layers, and is reflected and diffused by

the rougher CPG layer that generally covers the “Nubia sandstone” bedrock – NSB. Observed paleodrainage channels are

generally filled with small pebble alluvium – SPA, sometimes containing CPG and sandstone gravels. This simple model for the

near surface is also consistent with recent studies by Maxwell et al. (2001), concluding that the actual landscape is a combination of

an initial fluvial landscape inherited from Tertiary erosion, and climatic cycling during the Quaternary that formed the low relief

aeolian surface. As the first sand layers are rather transparent for the radar, sand deposits that could produce surface changes

have a low effect on the backscattered signal. The main part is the backscattered radar signal being due to a buried interface, it

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should be very stable with time, also leading to very high coherence values in interferometric SAR data as will be shown in the

following.

We used SIR-C data acquired during the Space Radar Laboratory mission 1 in April 1994. These data have been calibrated by

JPL for radar backscatter coefficient 0, and are full polarimetric (i.e. HH, HV, VH, and VV polarizations are available). We extracted

parts of 114.4 data take, acquired on April 16, 1994, for both C and L bands. The incidence angle was around 45 degrees with a

pixel size of 12.5 meters. Figure 6 shows the LANDSAT 7 scene and the corresponding SIR-C image (L-band; HH) related to the

Bir Safsaf site. The comparison of these two images clearly shows the interest of radar data compared to optical ones. To relate the

contrasted values of the backscattering signal to a surface – roughness effects – or subsurface – penetration effects – origin, we

used the GPR to sound the soil down to few meters deep along a profile crossing the southern anomaly (dark area).

The profile was recorded at both 500 MHz and 900 MHz frequencies using two different antennas in monostatic mode, i.e. the

transmitter and the receiver antennas located at the same place. While the antennas are pulled along the profile, a radar impulsion

is emitted by the transmitter, which determines the central frequency and the bandwidth of the signal. The wave propagates into the

ground and is recorded at the receiver, after it has been reflected and diffracted by the soil dielectric contrasts. For a given

antennas position, a GPR recording, i.e. a scan, represents the time variations of the electric field reflected from the ground. In

order to compare the backscattered power 0 derived from SIR-C data to GPR profiles, we need to compute a new quantity

representing, for each position, the total power at the receiver antenna. This quantity is computed by integrating in time the absolute

value of the electric field reflected from the ground. To take into account the pixel size of SIR-C images (12.5m), profiles were

averaged along the profile over a distance window of 12 m. We then computed for each averaged scan located at the position (x),

the quantity Pw taken as the integral of the instantaneous amplitude, i.e. the envelope of the electric field (Grandjean et al., in

press). Fig.7 presents the comparison between the Pw profile extracted from 900 MHz GPR data, and the 0 one extracted from L-

band SIR-C data. The total power in SAR images mainly contains the diffuse component of the backscattering since we have a

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side-looking system, while the total power extracted from GPR data contains both the diffuse and specular components (nadir-

looking system). It can be noticed that the average trend in Pw and 0 profiles look comparable, since it corresponds to the diffuse

backscattered component in both case. The Pw curves show in addition some sharp peaks, that can be attributed to a local specular

response of buried scatterers (rocks contained in sedimentary layers or located at the interface between two layers). The average

20 dB difference between the Pw and 0 curves is due to the fact that GPR data are not calibrated in absolute. This first quantitative

comparison between the backscattered power in GPR and SAR data should allow to estimate SAR profiles from the averaged GPR

total power (and vice versa). This method provides a valuable tool to help the interpretation of SAR images, that cover large areas,

from selected GPR acquisitions in the same field.

Fig.8 (bottom) presents the geological interpretation resulting from the analysis of the GPR section (top) and SAR data. We

can clearly observe the paleodrainage channel appearing in the northern part. It strongly contrasts with the “bank”, on the southern

part that presents a strong backscattered radar signal due to the rough interface at the top of NSB layer. From correlations between

GPR section and some geological information, this channel is filled with two different sedimentary deposits, with some calcified

pebble-gravel (CPG) at the interface. The upper layer is composed of SPA, absorbing the incident radar wave and presenting a low

radar return, while the lower layer contains alluvium mixed with CPG. The rough interface located between these two layers which

fill the upper paleodrainage channel is responsible for some backscattered power that can be observed in both SAR and GPR data.

Conclusion

These two experiments showed that spatial techniques, and especially radar imagery, have a capacity for high-precision

detection of geological structures, whether they are vein-type, lithological, or paleohydrogeological in nature. Their value is evident

for arid environments, where outcrops can be distinguished on the basis of their specific roughness, and concealed structures on

the basis of the volume and/or subsurface backscattering that they generate. The numerous veins mapped in the Akjoujt region

using SAR images provide an invaluable contribution to the current geological map. In addition, they allow geological structures

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seen at specific locations on the ground to be integrated into a comprehensive interpretation. We also confirmed in that work that

low frequency radar (L-band) can retrieve information about subsurface structures down to a couple of meters deep, where other

sensors (optical) cannot. The use of GPR systems allowed us to confirm the presence of buried paleodrainage channels that were

observed more than 10 years ago by McCauley and Schaber. We have shown that the average trend of the total power computed

from GPR data at 900 MHz can be compared to the backscattered power extracted from L-band SAR images, opening the way to

new interpretations of SAR images using GPR acquisitions. The quantitative analysis of both C and L-band SAR and 500 and 900

MHz GPR data allowed us to derive detailed geological descriptions of the subsurface structures, leading to new interpretations of

the local geological context and revealing unknown deep structures. Future work will consists in acquiring airborne L and P-band

SAR images over selected regions in order to benefit from a higher spatial resolution and establish potentials of the P-band (435

MHz), as compared to 500 MHz GPR profiles, to detect deeper subsurface structures down to 5 meters.

Acknowledgments

Authors would like to acknowledge JPL/NASA for providing SIR-C data. They also thank the University of Cairo, the Egyptian

Geological Survey, the Mining Authorities of Mauritania for their support in organizing field expeditions. This work was funded by

BRGM (French geological survey), CNES (French space agency) and PNTS (French national remote sensing program) .

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Tables

Layer Texture Thickness Permittivity

Modern sand sheet (MSS)

Bimodal fine sand Typically 5 cm 2.85-0.05j

Compacted sand layer (CSL)

Bimodal fine sand and granules

5 cm to 1 m, typically 30 cm

2.95-0.08j

Small pebble alluvium (SPA)

Small pebbles, clays and coarse sand

50 cm to 2 m 3.15-0.15j

Calcified pebble-gravel (CPG)

CaCO3 nodules, coarse-grained alluvium

5 cm to 50 cm, typically 20 cm

3.80-0.17j

“Nubia sandstone” bedrock (NSB)

Sandstone with interbedded shales

1 m and more, basal part of pits

3.55-0.16j

Tab. 1 : The five-layers model used for the near surface stratigraphy, after Maxwell et al., (2001) and Schaber et al., (1986). Permittivity measurements realized by the PIOM (Bordeaux, France) and performed on soil samples are included.

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Figures

Fig. 1 : Location of the study sites (black square) in the vicinity of Akjoujt (Mauritania).

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SIR-C : CHH,LHH,LHV

X-SAR : XVV

ASTER : B3,B4,B1 (Green,PIR,MIR)

Photo

Fig. 2 : Comparison between SIR-C, X-SAR and ASTER images of the site 1. This area is characterized by the presence of linear

dykes, clearly observed on the SIR-C polarimetric image (from Baghdadi et al., submitted).

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SIR-C : CHH,LHH,LHV

X-SAR : XVV

ASTER : B3,B4,B1(Green,PIR,MIR)

Photo

Fig. 3 : Comparison between SIR-C, X-SAR and ASTER images of the site 2. This area is characterized by the presence of circular

outcrops, clearly observed on the SIR-C polarimetric image (from Baghdadi et al., submitted).

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SIR-C : CHH,LHH,LHV

X-SAR : XVV

ASTER : B3,B4,B1 (Vert,PIR,MIR)

Photo

Fig. 4 : Comparison between SIR-C, X-SAR and ASTER images of the site 3. This area is characterized by the presence of a

buried paleochannel, only observed on the SIR-C polarimetric image (from Baghdadi et al., submitted).

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Fig. 5 : Location of the study sites (black square) in the vicinity of Bir Safsaf (Egypt).

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Fig. 6 : Location of GPR profile for the Bir Safsaf site. Top: Landsat 7 scene; Bottom: SIR-C scene (L-band, HH polarization). The

dark line shows the GPR profile location (from Paillou et al., 2003).

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Fig. 7 : Comparison between GPR total power Pw at 900 MHz and total backscattered power 0 in L-band (from Paillou et al.,

2003).

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MSS

CSL

CPG

SPA

SPA + GPG

NSB

5

m

PR2A PR2B

Fig. 8 : Cross sections for the Bir Safsaf site. Top: 900 MHz GPR profile; Bottom: geological interpretation sketch (from Paillou et al., 2003).

5

m