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ORI GIN AL PA PER
SAR Remote Sensing of Buried Faults: Implicationsfor Groundwater Exploration in the Western Desertof Egypt
Ahmed Gaber • Magaly Koch • M. Helmi Griesh •
Motoyuki Sato
Received: 18 July 2011 / Published online: 6 September 2011
� Springer Science+Business Media, LLC 2011
Abstract The hydrological setting of a desert plain area located in Egypt, west of
Aswan city, is still not well understood, and thus, its groundwater potential remains
largely unknown. Images from the ALOS/PALSAR L-band sensor have been used
to detect and delineate the subsurface structures in this area. Linear, elliptical and
circular polarization transformations were applied to the ALOS/PALSAR full
polarimetric data by changing the orientation angle (w�) and elliptical angle (v�).
The circular polarization (w = 0� and v = 45�) proved to be the best transformation
for revealing buried faults in various strike directions, which have not been reported
in the last version of the official geologic map of this area. Such derived circular
polarization images were further enhanced by applying the Optimal Polarization
Contrast Enhancement method. The moisture content (O–S) of the study sites was
generally low, with an average of roughly 0.01%. The average Root Mean Square
Height (hRMS) of the surface roughness was also low with 0.01 cm across all sites.
The relative dielectric constant (er) of the sand in the study area produced a very low
value of 3.04. The effects of O–S, er and hRMS on the radar backscattered signals
turned out to be very low, thus providing, optimal conditions for L-band to penetrate
relatively deeply. Moreover, 21 GPR profiles were acquired using 270 MHz
shielded antennas to validate the radar remote sensing results. These GPR profiles
reveal obvious offsets in the subsurface stratigraphy suggesting that such highly
fractured zones are possibly favorable zones for groundwater accumulation.
A. Gaber (&) � M. Sato
Graduate School of Environmental Studies, Tohoku University, Sendai, Japan
e-mail: [email protected]
M. Koch
Center for Remote Sensing, Boston University, Boston, MA, USA
M. Helmi Griesh
Geology Department, Suez Canal University, Ismailia, Egypt
123
Sens Imaging (2011) 12:133–151
DOI 10.1007/s11220-011-0066-1
Keywords Buried faults � ALOS/PALSAR L-band � GPR � Groundwater
potential � Western Desert � Egypt
1 Introduction
Egypt has a rapidly growing population, now exceeding 80 million, which is
concentrated in less than 6% of its land area; thus, food, water and urbanization
demands are rapidly increasing. Such conditions necessitate the development of the
unused desert areas fringing the Nile Delta and Valley. In this context, a new
development corridor has been proposed by [1] which is aimed at gradually
extending development activities from the western side of the delta and valley to
tens of kilometers westward. This corridor is divided into 12 sectors. The present
study focuses on one of them, namely the Aswan sector (Fig. 1).
The area west of Aswan city, Egypt, also called El-Gallaba Plain, is mainly covered
by windblown dry sand and characterized by arid climatic conditions. Although
rainfall is not significant throughout the year, some rare and irregular storms take
place over scattered localities during the winter season. Geomorphologically, the
study area is composed of five landform types. These are: (1) the young alluvial plain
of the Nile which is traversed by the Nile River. (2) The old alluvial plains of the Nile
which comprise the terraces found at various heights on both the eastern and western
sides of the Nile Valley. They were formed as a result of the aggradations and
degradation of the Nile Valley relative to the Mediterranean Sea level changes. (3)
The calcareous structural plateau and its bounding slopes. The plateau is underlain by
Eocene limestone. It lies on both sides of the Nile Valley with cliffs overlooking the
Fig. 1 Location of the study area west of Aswan and the proposed development corridor [1]
134 Sens Imaging (2011) 12:133–151
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flood plain at the northern part of the area. (4) The structural plains which occupy the
flat portion of the area. They are essentially underlain by the Nubian Sandstone, and
(5) the desert hydrographic basins which include the dry drainage channels leading
into the Nile Basin and traversing the structural plains and the calcareous plateau.
Geologically, the study area is situated within the African Platform with its Pre-
Cambrian folded basement, thus its tectonic framework is related to the Last African
Orogenic belt [2, 3]. The entire Nile Valley in Egypt is controlled by wrench faults
that are generally parallel either to the Gulf of Suez or the Gulf of Aqaba directions
[4]. The stratigraphic sequence of the study area ranges in age from Pre-Cambrian to
Quaternary. The Pre-Cambrian rocks consist mainly of igneous and metamorphic
rocks. The sedimentary section overlying the basement complex ranges in age from
Palaeozoic to Recent. Thus, the study area has been affected by the same structural
deformation processes that generated the Nile Valley and shaped the Kom Umbo
basin that lies east of the Nile River. The study area lies in a relatively large basin
(Kom Umbo basin) which can receive a significant amount of surface runoff during
the rainy season from the eastern Red Sea mountains range (Fig. 2). Recently, two
productive oil fields have been discovered in this area, which are of great
importance for future land development plans. In spite of this recent discovery, the
hydrological setting of this area is still not well understood, and therefore, its
groundwater potential remains largely unknown.
In the last few years a number of Synthetic Aperture Radar (SAR) satellites have
been placed in orbit. These systems operate in different wavelengths including
L-band (1.30 GHz, 23 cm and 1.25 GHz, 24 cm), C-band (5.0 GHz, 6 cm), and
Fig. 2 Drainage patterns and watersheds draining into the study area basin
Sens Imaging (2011) 12:133–151 135
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X-band (10 GHz, 3 cm). They all have been acquiring radar images of sand sheet
covered areas in the desert, predominantly in the Great Sahara, North Africa. Sand
sheets and fine gravelly areas have usually dark radar signatures because of their
smooth and relatively flat surfaces, whereas sand dunes show a mixture of sunlit and
shadowed slopes [5]. The radar signatures are clearly influenced by the surface
roughness and type of landforms. Because of this fact, investigators were startled by
the first Shuttle Imaging Radar (SIR-A) L-band (1.25 GHz, 24 cm) data of the
Eastern Sahara in Egypt and Sudan that showed details of ancient drainage patterns
(paleodrainage valleys or ‘‘radar-rivers’’) eroded into the bedrock as well as faults
and terraces that underlie the sand sheets [6].
Field investigations in the Eastern Sahara [7] demonstrated that 1.5 m was the
maximum sand thickness (referred to as the radar imaging depth) through which
images of the substrate could be recorded, which corresponds to 0.25 times the
calculated skin depth of the material found at Bir Safsafa site for L-band (1.28 GHz,
23.5 cm) [7]. For active sand dune materials, the radar imaging depth was estimated to
be between 2 and 3 m. Bir Safsaf, Egypt, was subsequently chosen as a site for further
research on subsurface imaging during the two SIR-C/X-SAR shuttle missions [8].
Data acquired during those missions enabled analysis of penetration depth by radar
signals for L-band (1.25 GHz, 24 cm) and C-band (5.0 GHz, 6 cm) with HH, HV, VH
and VV transmitted and received polarizations and for X-band (10 GHz, 3 cm) with
VV polarization. Schaber [8] demonstrated that analysis of the subsurface geology
can be enhanced by using a multi-frequency and multi-polarization radar system.
These authors were able to show that detectability of most geologic features is
dependent mainly on radar frequency. For example, wind erosion patterns in bedrock
were detected by X-band (10 GHz, 3 cm), whereas geologic units and sand- and clay-
filled fractures in weathered crystalline basement rocks (which are potential sources
of economic mineral deposits) were detected by C-band (5.0 GHz, 6 cm) and L-band
(1.25 GHz, 24 cm). On the other hand, Quaternary paleo-drainage networks are
visible in L-, C- and X-band images because the sand cover ranges only between 1 and
20 cm, allowing penetration in all three wavelengths [8]. For the Safsaf site, an overall
ranking of the utility of the SIR-C/X-SAR frequency bands and polarizations for
general geologic mapping below the windblown sand cover was reported by [8] in
order of decreasing priority as LHV, LHH(VV), CHV, CHH(VV) and XVV.
Obviously, most of the modern sand sheets in the Eastern Sahara Desert are
transparent to L-band (1.28 GHz, 24 cm) radar enabling the detection of substantial
amounts of underlying information related to past fluvial activities.
The ALOS/PALSAR L-band (1.27 GHz, 24 cm) sensor is able to penetrate and
image buried structures in low electrical loss materials such as dry sands of the
Great Sahara [9, 10], and together with its quadrature polarization mode (HH, HV,
VH and VV), has the ability to collect and measure information on polarimetric
scattering properties of buried targets. Furthermore, the ALOS/PALSAR sensor
provides high resolution (10 m) imagery with variable incidence angles, and with a
much improved value of NEr0 (noise equivalent r0) around -23 dB, which is a
crucial parameter for subsurface imaging since buried structures are likely to have a
low backscattering return. In addition, the geo-location accuracy is better than 10 m
and the radiometric accuracy is better than 1 dB.
136 Sens Imaging (2011) 12:133–151
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This study aims at using PALSAR L-band data with its multi-polarization
channels to detect buried fault structures striking in various directions, that may
serve as potential conduits for groundwater accumulation in the Western Desert of
Egypt.
2 Methodology
In this work, the Shuttle Radar Topography Mission (SRTM), ALOS/AVNIR-2 and
ALOS/PALSAR full polarimetric data constitute the space satellite data that was
used to extract remotely sensed information about the study area. This information
was complemented by two field campaigns that were carried out in May 2009 and
March 2011 to obtain detailed, in situ information and confirm the image processing
results. The first field visit served mainly to become familiar with the different
surface features encountered in the study area and was therefore a reconnaissance
visit. The second field trip was carried out mainly to validate the processed radar
images by measuring the soil moisture content, surface roughness and acquiring
radar profiles by means of ground penetrating radar (GPR) survey at selected sites.
2.1 Satellite Data Processing
2.1.1 Watershed and Drainage Network Calculation
Topographic data were obtained from the Shuttle Radar Topography Mission
(SRTM), a joint project of NASA and the Department of Defense’s National
Imaging and Mapping Agency (NIMA). The data are available internationally at a
3-arc sec (90 m) horizontal resolution and 16 m vertical accuracy with a 90%
confidence level. The SRTM data have been acquired in C-band with a wavelength
of 5.7 cm and the derived digital elevation model (DEM) shows vast improvement
over previous global GTOPO30’s data. The void-filled seamless SRTM tiles are
available from the consortium of space information (http://srtm.csi.cgiar.org/). To
ensure hydraulic connectivity within the watersheds that can be derived from the
DEM, all the identified sinks (pits) in the resulting DEM were filled.
The D8 flow direction algorithm of [11] was employed for generating the surface
flow directions. This algorithm allows flow from a cell to one of the eight nearest
neighbors. Once the direction of the flow out of each cell is resolved, it is possible,
through the calculation of the flow accumulation, to delineate the drainage network
by counting all the cells upstream of a given cell. A drainage network can be defined
by specifying a threshold value above which water is said to be in permanent flow.
A threshold of 100 cells was selected as the derived drainage density. Subsequently,
the outlet points of individual basins were calculated from connected drainage
networks (Fig. 2).
The Kom Umbo basin and its western extension, where the study area is located,
may receive a significant amount of surface runoff from the Red Sea Hills during the
rainy season. Thus, the study area has a great potential of accumulating groundwater
within the fracture zones and basin sediments.
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2.1.2 Supervised Classification of Optical Data
Classification algorithms are generally grouped into supervised and unsupervised
methods. In the supervised case, the algorithm has prior information of the scene
content or of the terrain classes present in it. In this work, ALOS/AVNIR-2 optical
data (1B2 product level) acquired on May 2nd, 2008 with 10 m spatial resolution
was used, together with field information, to generate a supervised classification
map using the minimum distance technique [12].
The study area is covered mainly by windblown sand, in addition to fluvial and
calcareous deposits. The classification of the AVNIR-2 optical images was used to
locate the spatial distribution of these deposits. Thus, all available prior information
from published geological maps [13] and field visits was used to generate a
supervised classification map, which shows that the study area is mainly covered by
dry, relatively flat and homogenous sand and gravel layers (Fig. 3). It therefore
Fig. 3 ALOS/AVNIR-2 supervised classification map
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shows optimal conditions for microwave penetration, especially for the ALOS/
PALSAR L-band (1.27 GHz, 24 cm).
2.1.3 Radar Polarization Transformation of ALOS/PALSAR
The electric field of a plane wave can be described as the vector sum of two
orthogonal components, typically horizontal and vertical components. The two
components are characterized by their amplitudes and the relative phase between
them. When viewed along its direction of propagation, the tip of the electric field
vector of a fully polarized wave traces out a regular pattern. In its most general
form, the pattern is an ellipse, as shown in Fig. 4. The ellipse has a semi-major axis
of length a, and a semi-minor axis of length b. The angle of the semi-major axis,
measured counter-clockwise from the positive horizontal axis, is the ‘‘orientation’’
w of the EM wave, and can take on values between 0� and 180�. The degree to
which the ellipse is oval is described by a shape parameter called eccentricity or
‘‘ellipticity’’, defined as v = arctan (b/a), which can take values between -45� and
?45� [14]. The shape of the ellipse is governed by the magnitudes and relative
phase between the horizontal and vertical components of the electric field vector.
The quad polarization of ALOS/PALSAR L-band (1.27 GHz, 24 cm) images
(product level 1.1) acquired on the 29th of November 2009 with an incident angle of
25.6� were used in this work to image the subsurface structures along the study area.
These full polarimetric ALOS/PALSAR data were transformed into linear (w = 45�and v = 0�), different elliptical ((w = 45� and v = 11�) (w = 45� and v = 23�),
and (w = 135� and v = 34�)) and finally circular (w = 0� and v = 45�) polariza-
tion basis by changing both the orientation angle (w�) and elliptical angle (v�) to
detect and delineate the subsurface structures. All the output images were displayed
in Pauli RGB. The circular polarization transformation (w = 0� and v = 45�)
produced the best results and revealed very clearly two different sets of faults
(NW–SE and E–W), which are covered by an active longitudinal sand dune (bright
area in Fig. 5a).
Fig. 4 Polarization ellipseshowing the orientation angle w�and ellipticity v�
Sens Imaging (2011) 12:133–151 139
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2.1.4 Radar Polarization Filtering
The derived circular polarization images were further enhanced by applying the
Optimal Polarization Contrast Enhancement (OPCE) method [15] to maximize the
ratio of backscattered strength between faults and the surrounding sedimentary
material by calculating the power of any target as follows:
P ¼ g!½K� h!
where g and h are respectively the stocks vectors of the transmitter and receiver, and
[K] is the Kennaugh matrix which can be calculated at each pixel from the full
polarimetric ALOS/PALSAR data. The proper polarization states which optimize
the enhancement factors of target (KA) and target (KB) were calculated using the
following equation;
Fig. 5 Images of a AVNIR-2 optical sensor (R:4, G:2, B:1), and PALSAR microwave sensor: b Paulidecomposed of raw data (R:|SHH-SVV|, G:|SHV ? SVH|, B:|SHH ? SVV|), and after applying c lineartransformation (R:|S11-S22|, G:|S12 ? S21|, B:|S11 ? S22|), d and e elliptical transformation (R:|S11-S22|, G:|S12 ? S21|, B:|S11 ? S22|) and f circular polarization transformation (R:|SLL-SRR|, G:|SLR ?SRL|, B:|SLL ? SRR|)
140 Sens Imaging (2011) 12:133–151
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c ¼ maxg!T
KAh i h!
g!TKBh i h!
s:t: g21 þ g2
2 þ g23 ¼ 1
h2 þ h2 þ h2 ¼ 1
The initial contrast between the buried faults (KA) and the surrounding
sediments (KB) was 1.047321e ? 000 and was enhanced to 2.153422e ? 000 after
8 iterations (Fig. 6b). The proper Stokes vectors of the transmitter and receiver
were calculated (Table 1) from the previous equations and plotted on the Poincare
sphere to determine the best polarization states for imaging the buried faults in the
study area (Fig. 7). The buried structures have consistently lower backscatter
returns than the surrounding sediments which represent the clutter. From the
Poincare sphere, we can determine that the VV polarization provides a superior
image than the HH polarization for detecting the buried faults in the study area
(Fig. 7), while the best polarization for detecting the surrounding sediments is the
opposite configuration.
Fig. 6 Polarization filtering effect: a before, and b after applying the OPCE
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2.2 Field Measurement
Three test sites were selected for further investigation in the field and validation of
the ALOS/PALSAR processing results. Field measurements consisted of determin-
ing the volumetric moisture content of the soil, surface roughness and conducting a
Ground Penetrating Radar (GPR) survey to image and confirm the existence of the
buried faults. Field measurements were carried out in March 2011 and the results
are summarized below.
Table 1 The proper Stokes vectors for OPCE
Optimal transmit polarization Optimal receive polarization
g0 1.000000e ? 000 h0 1.000000e ? 000
g1 9.928611e-001 h1 -9.832537e-001
g2 1.098681e-002 h2 -1.133955e-001
g3 1.187688e-001 h3 1.426660e-001
Fig. 7 Poincare sphere showing the best polarization state for imaging the buried faults (Svv) andsurroundings (Shh)
142 Sens Imaging (2011) 12:133–151
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2.2.1 Soil Moisture Content
Soil moisture (O–S) and surface roughness information are the key parameters of
radar capability to penetrate the desert sand. The top 30 cm surface soil moisture
was measured at 20 sites (Fig. 8) using the Time Domain Reflectometery (TDR).
The TDR Probe sends microwave energy into the ground material, records the
reflected energy and converts that to moisture content. The moisture content of the
studied sites was generally low, with an average of roughly 0.001 during the month
of March when fieldwork was conducted (Fig. 9).
2.2.2 Surface Roughness
The characterization of surface roughness is generally accomplished by measuring
the height variations of the ground surface across a transect [16]. The parameters
Root Mean Square Height (hRMS) and correlation Length (Lc) are commonly
extracted from this direct measurement of roughness. The hRMS is the standard
deviation of the corresponding mean height of the soil surface at centimeter scale,
Fig. 8 Surveyed sites A, B and C where 21 GPR profiles were scanned using a 270 MHz antenna
Sens Imaging (2011) 12:133–151 143
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while the Lc is the length in centimeters from a point on the ground to a short
distance for which the heights of a rough surface are correlated with each other. The
hRMS has been measured with a pin profilometer, also known as a pin meter. The pin
meter uses evenly spaced 76 pins held parallel to each other at 2 cm intervals to
determine a surface height profile for the length of the pin meter (1.5 m) (Fig. 8).
Then the Lc can be calculated from the hRMS using [16] equation (Lc = g(hRMS,
O–S)). Values of hRMS and Lc were computed from the obtained measurements and
averaged over each site. The average hRMS was 0.01 cm across all sites, with a
maximum of 0.2 cm (almost flat). The average field measurement for Lc was
0.2 cm, ranging from 0.05 to 0.3 cm.
2.2.3 GPR Survey
GPR’s ability to pick up shallow subsurface stratigraphy as well as any offsets
within the stratigraphy makes it a powerful tool to determine more accurately the
geometry of faults. Wyatt and Temples [17] conclude that GPR is a viable method
with which to study faults, noting that high amplitude reflectors are important in the
interpretation of faults from GPR data. Consequently, the GPR method was used to
verify the resulting image products of ALOS/PALSAR and determine how deep the
L-band can penetrate and image near-surface areas covered by dry sand in Egypt’s
desert (Fig. 9). A total of 21 GPR profiles were acquired using the commercial GSSI
Fig. 9 Field measurements of a soil volumetric moisture (TDR), b surface roughness using a Pinmeter,c GPR profiles and d water depth and quality from drilled wells in the study area
144 Sens Imaging (2011) 12:133–151
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2000 Digital GPR unit with a 270 MHz shielded antenna (Fig. 8). The GPR profiles
were run perpendicular to the buried faults and their total length was around 230 m.
All profiles were processed by applying an Automatic Gain Control (AGC) and a
background removal. A dielectric constant of 3.4 was chosen for the material of dry
sand based on the low volumetric moisture content that had been previously
measured with the TDR. This value was used to convert the range setting into
penetration depth for each GPR profile. All profiles penetrated *6 m using 80 ns.
2.2.4 Groundwater Samples
Several water samples were collected during the first field campaign in May 2009
(Fig. 8). Field measurements and laboratory analysis provided information on the
depth to water, total depth of the well, subsurface lithology and water quality. All
this information was used to predict the quality and depth to water in the areas under
investigation.
3 Results and Discussion
The area west of Aswan city, represents the western extension of Kom Umbo basin
and has most probably been affected by the same geostructural settings that shaped
Kom Umbo basin. Topographically, this plain is relatively flat and covered by
fluvial deposits (sand and gravel) brought by an old E–W striking river course
(wadi), which is older in age than the present Nile River. Wadi El-Kubanyia is the
western remnants of this ancient wadi system. The connection between the present
day Wadi El-Kubanyia and its delta (El-Gallaba Plain) is not known yet, in part
because it is completely covered by an active longitudinal sand dune. This active
sand dune is moving from NW–SE directions and appears as a well defined
landform unit in the most recent geomorphologic map of Aswan sheet [18]. In
addition, no geological structures have been mapped and drawn on the most recent
official geologic map of this location [19]. This area appears on both maps simply as
covered by a longitudinal sand dune with no subsurface structures.
On the other hand, the current ground gradient (west of the Nile River) is sloping
W–E, thus Wadi El-Kubanyia is receiving water and sediments from the west
through fluvial processes, that also formed two terraces inside Wadi El-Kubanyia,
an old and higher terrace with E–W direction and a more recent lower terrace with
W–E direction. All these landform features were documented during the first
reconnaissance field visit in May 2009.
In an effort to image the subsurface structure of El-Gallaba Plain and determine
its connection with Wadi El-Kubanyia, which is currently covered by an active sand
dune, the ALOS/PALSAR L-band (1.27 GHz, 24 cm) and full polarimetric data
(HH, HV, VH and VV) was processed. The processed ALOS/PALSAR datasets
reveal that the circular polarization product produced better results for detecting and
identifying a set of subsurface faults striking in various directions with clearly
defined fault zone boundaries than the linear and elliptical polarization products.
Because the faults have different strike directions, the circular polarization mode is
Sens Imaging (2011) 12:133–151 145
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the best to image and reveal such faults, unlike the other linear and elliptical
polarizations, which detect only the faults that coincide with specific directions.
Therefore, the circular polarized transformed image may contain phase information
about the subsurface structures that is not revealed by the amplitude information
alone. Such phase information is not included in the linear and only partially in the
elliptical polarized transformed images. The authors plan to prove this hypothesis in
future work.
Furthermore, OPCE method significantly enhanced the boundaries of fault zones.
Subsequently, the processed PALSAR data was geo-coded and mosaicked in order
to digitize the linear features that represent faults to produce a final fault network
map. Two sets of faults are predominant in the study area; they strike in NW–SE
and E–W directions and have, so far, not been reported in the last version of the
official geologic map [19]. The moving longitudinal sand dune has the same
direction of the NW–SE faults, which suggests that the surficial sand dune is
controlled by these subsurface faults.
The NW–SE set of faults most probably represent the subsurface connection
between Wadi El-Kubanyia with its old delta system (El-Gallaba Plain). In order to
further investigate this hypothesis, the NW–SE set of faults were extended to reach
the current River Nile through the middle of Wadi El-Kubanyia along its edges.
This NW–SE fault system, which is located in the middle of Wadi El-Kubanyia,
separates the old and new sediments forming the two terraces, whereby the new
terrace represents the hanging wall of a normal fault and the old terrace represents
the footwall of the same fault. This interpretation was confirmed in the field by
running GPR profiles perpendicular to these suspected buried faults.
Sand is a natural soil covering a significant fraction of the terrestrial land surface,
especially in desert regions and along shorelines bounding oceans, lakes and rivers.
Since bound water is mostly absent in arid regions’ sands, microwave radiation can
easily penetrate these sands, thereby allowing the exploration of the bottom
topography of sand beds with this technology. However, in order to explore the
actual penetration capability, it is necessary to measure the dielectric properties of
sand. Several experimental studies on microwave dielectric properties of sand and
sandy soils have been conducted in the past and reported, for example, by [9, 20,
21]. Microwave dielectric measurements of Sahara sand from the Grand Erg
Oriental in southern Tunisia showed a significant loss factor due to the presence of
Hematite with a maximum depth of 1.5 m with ALOS/PALSAR frequency and
wavelength range (1.27 GHz and 24 cm) [9].
The dielectric constant is a key parameter for the electromagnetic wave
propagation inside the materials. A low dielectric constant (permittivity) means a
low attenuation and maximum penetration for the electromagnetic waves. Topp’s
calibration model [22], which is the most popular equation for calculating
the dielectric constant from the volumetric water content, was used to calculate
the dielectric constant of the sand based on the TDR field measured values using the
equation:
er ¼ 3:03þ 9:3hþ 146h2 � 76h3
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where h is the volumetric water content of soil. In the study area the moisture
content is very low with an average around 0.001. Furthermore, the dielectric
constant of the sand is 3.04 as calculated with the Topp’s equation. In addition, the
sand found in the study area is well sorted, because it is windblown active sand,
which means that it does not have significant loss factor (low impurities).
Matzler and Murk [23], measured the complex dielectric constant over the
frequency range of 0.1–1.8 GHz for very dry sand that had been collected at
Pancake Bay situated on the eastern shore of Lake Superior, Ontario, Canada using
a coaxial cavity resonator with circular cross section made with brass. Such
collected sand has very similar moisture content with respect to the sand found in
study area, west of Aswan. Matzler and Murk [23] reported that the real part of the
dielectric constant is essentially constant at all frequency ranges from 0.1 to
1.8 GHz. Unlike the real part, the imaginary part of the dielectric constant varies
with frequency over the observed range from 0.13 to 1.7 GHz.
The value of 0.014 was chosen as the imaginary part of the relative dielectric
constant (er00) for our study area based on Matzler and Murk [23] experiment at
1.27 GHz frequency. The microwave permittivity of dry sand is er = er0 ? jer
00,where, j = H-1. Thus, based on the previous equation, the real part of the relative
dielectric constant (er0) was calculated and equals 3.026. The effects of O–S, er and
hRMS on the radar backscattered signals measured in the study area turned out to be
very low providing good conditions for L-band to penetrate relatively deeply.
The skin depth is the term related to the propagation of plane EM wave, and is
commonly used to estimate the depth of investigation of an EM prospecting system.
Ulaby’s [24] proposed a relationship for skin penetration depth dp as a function of
observation frequency and soil moisture content, by considering the power of an
electromagnetic wave incident upon a soil surface. This relationship defines the
penetration skin depth as the depth in the soil at which the transmitted wave power
just below the soil surface diminishes to the proportion 1/e (i.e. 37%).
dp ffik0
ffiffiffiffi
e0rp
2pe00r
Conversely, based on Ulaby’s [24] radar observation depth relationship, Matzler
and Murk’s [23] value of the imaginary part of relative dielectric constant of dry
sand, and field observations and measurements conducted by the authors in the
study area, the skin penetration depth of ALOS/PALSAR L-band was calculated to
be approximately 5.75 m for the surveyed area west of Aswan City in Egypt.
The GPR profiles show clearly visible offsets in the subsurface layers (reflectors),
which are generated by two sets of normal faults. These subsurface layer
displacements are covered by dry and loose sand sheet with a thickness ranging
from 1 to 2 m (Fig. 10). This dry sand sheet covers very large areas as revealed in
the supervised classification of optical images and forms the longitudinal sand dune.
Mathematically, the ALOS/PALSAR L-band wave can propagate up to 5.75 m deep
(skin depth) and in practical terms it is capable of detecting buried faults at 2 m
depth as revealed from GPR profiles. Accordingly, the ALOS/PALSAR L-band
observation depth in the study area is around 2 m, which is 1/3 of the skin depth.
Sens Imaging (2011) 12:133–151 147
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Figure 10 shows three selected GPR profiles out of 21 that were acquired in the field
to image the buried faults.
The newly revealed faults were digitized onto a map and used to create a fracture
density map to locate concentrations of highly fractured zones within the study area.
It is believed that these sets of faults are connected with the Nile River through
Wadi El-Kubanyia and may possibly represent favorable zones of groundwater
accumulation (Fig. 11).
From the collected hydrological field information obtained from drilled wells, the
depth to water ranges from 35 to 70 m and sometimes 0 as in Kurkur Oasis, south of
the investigated site (Fig. 12). The total depth of the wells ranges from 100 to
150 m, and a few of them even reach the basement rocks which means the
sedimentary cover in the study area is relatively small. This observation is supported
by the geology found in Aswan city, where the granite rocks and Nubian Sandstone
crop out. On the other hand, the plain area west of Aswan sector has a somewhat
fixed lithology as listed here from top to bottom: Sandstone (range from 20 to 30 m
thickness), Mudstone (range from 30 to 40 m thickness), sandstone (range from 20
to 30 m thickness), which represents the main aquifer and finally mudstone around
Fig. 10 GPR profiles show the stratigraphic offsets (black dashed lines). They were surveyed using a270 MHz shielded antenna
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20 m thickness, followed by the basement rocks. Moreover, the collected water
samples from the surveyed wells were analyzed at the Desert Research Center
(DRC) in Cairo to determine the major and trace elements. The water analysis
results reveal that the groundwater is of very good quality for human consumption
and similar in its physical-chemical parameters to the river Nile water.
4 Conclusions
Water is a vital and essential natural resource for the initiation of any land
development plan. At the same time, satellite systems are providing continuous
streams of very valuable information on land surface and subsurface features,
including geostructural features. This work examines the use of ALOS/PALSAR’s
fully polarimetric data for geospatial information extraction and integration to reveal
potential areas for groundwater exploration west of Aswan City in Egypt.
Several buried faults in the Western Desert of Egypt were identified and mapped
from ALOS/PALSAR L-band circular polarized transformed data which are not
included in the last version of the official geologic map. The field measurements
show that the study area is mainly covered by very dry, homogenous and relatively
flat lying sands and, thus, show optimal conditions for microwave penetration.
Fig. 11 Extracted faults from a official geologic map, b processed ALOS/PALSAR data and c densitymap of highly fractured areas (brown color)
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A set of faults that were previously detected on satellite radar images, were
examined and validated in the field using conventional ground penetrating radar
(GPR) which is used for high resolution subsurface imaging. The GPR results show
obvious offsets in the subsurface strata and confirm that the ALOS/PALSAR L-band
can penetrate the dry sand in the study area up to few meters and, therefore, was
able to image two sets of buried faults (NW–SE and E–W). These faults represent
highly fractured zones in the bedrock and are potentially favorable for groundwater
accumulation, and thus, a promising resource in the Western Desert of Egypt.
Acknowledgments The authors would like to thank the Japan Aerospace Exploration Agency (JAXA)
for providing the ALOS data as part of the ALOS user agreement (ALOS-RA-81). This work is being
funded by the US—Egypt Science and Technology Joint Fund in cooperation with NSF and STDF under
Project Award # 1004283 and # 1975, respectively.
Fig. 12 Depth to water map in the study area
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