CHAPTER- V
SPATIAL AND TEMPORAL SIGNATURES OF THAR DESERT IN INDIA
The broad level characterization of land cover
classes have been discussed in previous chapter. The
detailed investigations of variation exists within one of the
land cover class, namely arid/semi-arid („Thar‟ desert),
carried out using C-band scatterometer data is discussed
in this chapter.
A portion of hot (“Thar”) desert in India has been
assessed using time-series of backscatter response. Major
dune types were identified and their temporal trends were
investigated. The annual variation of ERS-2 C-band 2000
scatterometer data over this region showed the variability
of backscattering coefficient of the order of 11.27 dB (20.08 to -8.71 dB) during one year.
These variations were also analysed in terms of
scattering due to various factors like soil moisture,
vegetation, rainfall and surface roughness. In addition, nine
dune types were identified for detailed signature studied.
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5.1 INTRODUCTION
Optical as well as microwave remote sensing data have been
successfully used for monitoring and mapping of deserts all over the world. In
optical bands, the desert shows higher reflectance whereas, in microwave
frequencies, active sensor shows low backscattering coefficient values and
passive sensors show high brightness temperature values (Mishra et al,
2002).
Among the space-borne SAR systems, C-band data is widely used for
various land applications due to availability of ERS-1/2, Radarsat, and Envisat
SAR. In addition to this, ERS-1/2 (C-band) and QuikSCAT (Ku-band)
scatterometers have also been investigated for land applications (Birrer et al.
1982; Drinkwater et al. 2000 & 2001; Kennett et al. 1989; Kerr and Megagi
1993; Long et al 1994, 1999; Mougin et al. 1995; Prigent et al. 2005; Wagner
et al, 1999a, 1999b; Wismann, 1998). Spaceborne scatterometers have
provided continuous synoptic microwave coverage of earth for nearly two
decades.
Stephen et al. (1997) analysed the normalized radar cross section
(NRCS) measurement, obtained over Thar Desert in Pakistan between May
1994 and May 1996. Spatial variations in the radar cross section are
compared with vegetational and meteorological parameters. Seasonal as well
as inter-annual variations are investigated by correlating the radar backscatter
with Phenological, meteorological and AVHRR NDVI data. It is demonstrated
that valuable information can be delineated from the ERS scatterometer data
over arid regions in order to provide data for environmental and especially
climatic change studies.
5.2. STUDY AREA
The study area is Indian part of the Thar Desert, which is located
between 24o 36‘ – 29o 21‘ N Latitude and 69o 32‘ - 75o 26‘ E Longitude (Figure
5.1). The Thar Desert (also known as the ―Great Indian Desert‖) in India is
geographically, located in the state of Rajasthan, between the foothills of the
Aravalli – ranges in the east and the international border with Pakistan in the
west.
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Dune types
Figure 5.1: Study Area and Dune type (the Thar Desert)
It lies mostly in the Indian state of Rajasthan, and extends into the
southern portion of Haryana and Punjab and further into the northern region of
Gujarat state. The Thar desert is bounded on the northwest by the Sutlej
River, on the east by the Aravalli Range, on the south by the salt marsh known
as the Rann of Kutch (parts of which are sometimes included in the Thar), and
on the west by the Indus River. Depending on the areas included or excluded,
the nominal size of the Thar can vary significantly. According to the WWF
definition, the Thar has area of 238,700 km². Another source gives the area of
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446,000 km² that has 805 km length and about 485 km width, out of this
208,110 km² is in India. Of the Indian portion, 61% falls in Rajasthan, 20% in
Gujarat and 9% in Punjab and Haryana (combined).
The Thar Desert is dominated by the south-west monsoon, which
controls both the wind vector and the vegetation cover. The configuration of
atmospheric dynamics and sinking air masses in the region inhibit rain in this
region despite the fact that considerable precipitable moisture exists in the
atmosphere. Minor changes in the atmospheric circulation patterns result in
amplified changes in the rainfall, the winds and the Aeolian dynamism. It is an
austere area where water is scarce and occurs at great depths, from 30 to 120
m below the ground level.
The region is dominated by Aeolian bedforms of different dimensions,
including the sand dunes. The thickness of Aeolian cover can range from 1m
to 100 m. West-ward, the natural vegetation becomes gradually sparse,
cultivation on dune slopes becomes less frequent, and reactivation of the high
dunes are more recurrent. Aeolian activity in the Thar Desert is mainly
restricted to the period of summer winds associated with the south west
monsoon.
The north eastern wind of winter months plays only a minor role in
Aeolian activity and is largely limited to the northern fringe of the desert.
Strong sand and dust shifting winds begin from March onwards when the
surface is dry and maximum wind speed (20 km/h or more) is reached at all
the meteorological stations during the month of June. May and July are also
very windy. Since this is also the period when much of the ground flora is dry,
the environment is suitable for Aeolian activities. The wind and the sand
dynamics cease with the arrival of monsoon rains (end of June along the
eastern margin of the desert, and mid-July in the western part). Higher wind
strength and lower rainfall favours erosivity of the wind (Singhvi and Kar
2004).
5.3 MATERIALS AND METHODS
The data available from ERS-2 Scatterometer of South Asian region,
for year 2000 was used to generate the backscattering images of India. The
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8.9 km enhanced resolution for ERS-2 C-band data was used. In addition to
this, SPOT VEGETATION - NDVI product of same year was used in this
study. All the scatterometer and NDVI data were co-registered with the r.m.s
value of 0.01 using Arc info software.
A portion of the Thar Desert in India was extracted and the backscatter
time-series was analysed along with the meteorological and biophysical
parameters. Dune map (Singhvi and Kar, 2004) was used to identify the major
dune types in this desert region. For identifying the presence of vegetation, the
Landsat data (ETM+) was visually interpreted.
The NASA Shuttle Radar Topographic Mission (SRTM) DEM (90 m
resolution) was also used to measure the height variation in the area. This
data (5 deg x 5 deg tiles) was obtained from the USGS ftp site. The SRTM
90m DEM's has a resolution of 90m at the equator.
Subsequently, nine locations over six sand dunes type with or without
vegetation (Figure 5.1) were identified and signatures statistics were extracted
and analysed. A transact profile was also generated from Shahgarh in
Western portion to Aravalli (Near Jaipur) in the Eastern portion.
Attempts were made to assess the aerodynamic roughness length Z 0,
which can be correlated with o. The height above the displacement plane at
which the mean wind becomes zero (when extrapolating the logarithmic windspeed profile downward through the surface layer) is the theoretical height that
must be determined from the wind-speed profile, although there has been
some success at relating this height to the arrangement, spacing, and physical
height of individual roughness elements such as trees or houses. Attempt was
made to calculate the Z0 using a log-linear model (Prigent et al., 2005).
5.4 RESULTS AND DISCUSSION
5.4.1 Spatio-Temporal Backscatter Pattern
The Thar Desert presents picture of contrast in backscatter image in
comparison to other land covers in India (Figure 5.2). The monthly averaged
o images over Thar Desert and surrounding arid region are shown in Figure
5.2. The Thar Desert is characterized by low o value (-25 to -13 dB),
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surrounded by (arid region) comparatively high o value (-13 to -9 dB). As
discussed by Stephen at al. (1997) the geophysical parameters of the land
could also be reflected in the incidence angle diversity of the ERS
scatterometer.
JAN
FEB
MAR
APR
MAY
JUN
THAR
DESERT
30O44'N
67O48'E
19O57'N
76O16'E
JUL
AUG
SEP
YEAR - 2000
Sigma-0 (dB)
-25 - -22
-22 - -18
-18 - -16
OCT
-16 - -15
NOV
DEC
-15 - -14
-14 - -13
-13 - -11
-10 - -9
Figure 5.2: Monthly averaged o over arid area including the Thar Desert in
the year 2000.
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The data in year 2000 over this region showed the variability of o of
the order of 11.27 dB (-20.08 to -8.71 dB). This large range of o values
observed in desertic terrain is attributed to the changes in dunes roughness
(Singh et al. 2006).
These variations can be explained in terms of scattering due to various
factors like soil moisture, vegetation, rainfall, and surface roughness due to
wind. In general, high backscattering was observed in the months of July and
August and low backscattering was observed in the months of May and June
(Table.5.1 and Figure 5.3).
It is observed in (Figure 5.3) that the Min-Max range of observed o
over arid area is lowest during the period of December and January and
highest in the month of May and June. As given in the table 5.1, observed
maximum o value is around
(-9±1) dB during the entire year. In contrast to
monthly maximum o values, the large variation is observed in the minimum
values of o from about -17 dB during winter (December and January) period
to about -20 dB in the months of May and June i.e. summer. Lower o values
observed during the summer period could be the result of the reduced
fractional vegetation cover that reduces the effective surface roughness. The
high o value (-10 to -9 dB) has also been found over mountainous region,
which is due to high topography (Figure 5.4).
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Table 5.1: o Variability in the Thar Desert (Year 2000)
MIN o MAX o RANGE
S.N. MONTHS
(dB)
(dB)
(dB)
1
January
-16.72
-9.97
6.745
2
February
-17.61
-10.07
7.531
3
March
-18.98
-9.92
9.06
4
April
-19.65
-9.98
9.67
5
May
-20.08
-9.98
10.1
6
June
-19.94
-9.86
10.08
7
July
-18.17
-8.76
9.406
8
August
-16.94
-8.71
8.233
9
September -17.76
-9.70
8.059
10
October
-17.64
-10.35
7.295
11
November
-18.03
-9.94
8.095
12
December
-17.53
-9.91
7.611
0
MIN
MAX
Sigma-0 (dB)
-5
-10
-15
-20
-25
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Figure 5.3: Variability of o over the year 2000.
119
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
-2
-4
Sigma-0 (dB)
-6
-8
-10
ELEVATION
(M)
500
400
-12
-14
300
-16
200
-18
SHAHGARH JAISALMER
JODHPUR
PHALODI
-20
0
71
142
213
285
356
427
498
MERTA
DEGANA
570
640
ARAVALLIS
712
100
783
Distance (Km)
Figure 5.4: Transact Profile of o values
5.4.2 Effect of vegetation cover
The minimum o observed for sand-dune areas without vegetation
cover, in the last week of June, are attributed to dry soil conditions. During this
period, lower NDVI values were observed. The increase in o was attributed
mostly due to presence of vegetation in the second week of September and
roughness arises due to dune size and shape. As mentioned by Stephen et al.
(2007), the values of o could be modulated with view direction [incidence
angles θ (thetas) and azimuth Φ (phi angles)], where the modulation
characteristics reflect the surface geometry. It also varies spatially and reflects
the spatial inhomogeneity of the sand surface.
High correlation has been observed in o and NDVI (Figure 5.5). As
seen in Figure 5.5, in areas of sand dunes with-vegetation cover the minimum
o observed in the last week of May, that is -19.5 dB, which is due to lack of
soil moisture during summer period. The increase in value of o continues
subsequently with the growth of vegetation and corresponding increase in
surface roughness.
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0.3
NDVI
0.35
0.25
0.2
Parabolic dunes
0.15
-12
Sigma-0 (dB)
Linear dunes
-14
-16
Transverse dunes
-18
Netwok transitional
parabolic dunes
Ju
l
Au
g
Se
p
O
ct
N
ov
D
ec
Ja
n
Fe
b
M
ar
Ap
r
M
ay
Ju
n
-20
Figure 5.5: o and NDVI response for dunes (with vegetation cover).
The low value of o is attributed to dry smooth Soil and sparse
vegetation cover. During this period, the NDVI value is also found to be of the
lowest order (0.16). The maximum o observed in this area is -12.7 dB mostly
due to presence of vegetation cover (NDVI=0.27).
A gradual decrease is observed in o values until last week of June.
Afterwards, a sudden increase in o is observed for a period of July and
August, as the moisture level increases due to arrival of monsoon in this
region (Figure 5.6). Onset of monsoon suddenly increases the soil moisture
content, which leads to less transmission of energy through the medium and
increase in surface scattering. From September onward o decreases due to
decrease in soil moisture attributed to percolation of water and high
evaporation rate.
In the summer season i.e. from the beginning of March, moisture
content in the desert region decreases significantly, due to increase in surface
temperature resulting in lower o (Figure 5.7).
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Parabolic-With and Withoutout Veg
Sigma-0 Vs Rainfall
20
0
RF - 24
Parabolic - Without Veg
Parabolic- with Veg
16
-6
14
-8
12
-10
10
-12
8
-14
6
-16
4
-18
2
-20
0
01
-J
13 an
-J
25 an
-J
06 an
-F
18 eb
-F
01 eb
-M
13 ar
-M
25 ar
-M
06 ar
-A
18 pr
-A
30 pr
-A
12 pr
-M
24 ay
-M
05 ay
-J
17 un
-J
29 un
-J
u
11 n
-J
23 ul
04 Jul
-A
16 ug
-A
28 ug
-A
09 ug
-S
21 ep
-S
03 ep
-O
15 ct
-O
27 ct
-O
09 ct
-N
21 ov
-N
03 ov
-D
15 ec
-D
27 ec
-D
ec
Sigma-0 (dB)
-4
18
Rainfall (inch)
-2
Figure 5.6: o v/s Mean-24 hrs Rainfall (Parabolic Dunes)
Parabolic-With and Withoutout Veg
Sigma-0 Vs Temp.
0
40
-2
35
-4
30
25
-8
-10
20
-12
15
Temp. (deg C)
Sigma-0 (dB)
-6
-14
10
-16
Parabolic - Without Veg
Parabolic- with Veg
T Mean
-18
0
01
-J
a
19 n
-J
a
06 n
-F
e
24 b
-F
e
13 b
-M
a
31 r
-M
a
18 r
-A
p
06 r
-M
ay
24
-M
a
11 y
-J
u
29 n
-J
un
17
-J
04 ul
-A
u
22 g
-A
u
09 g
-S
e
27 p
-S
e
15 p
-O
c
03 t
-N
o
21 v
-N
o
09 v
-D
e
27 c
-D
ec
-20
5
Figure 5.7: o v/s Mean Temperature (Parabolic Dunes)
5.4.3 Backscatter Response to Dune types
From Figure 5.8 it is evident that the overall range of o follows a cyclic
pattern for all the features. Due to physical scattering mechanism (surface
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roughness and dielectric properties as well as volume scattering from
vegetation) attributing to variability in o, it is possible to discriminate dune
types.
-9
Parabolic - Without
Veg
Sand streaks
-11
Linear- Without Veg
Sigma-0 (dB)
-13
Transverse-Without
Veg
Star Dune type-1
-15
Netwok transitional
parabolic-without
Veg-2
-17
Network Sinuous
Dunes
Barchans and
Barchanoids
-19
Major obstacle
dunes
01
-J
19 an
-J
06 an
-F
24 eb
-F
13 eb
-M
31 ar
-M
18 ar
-A
06 pr
-M
24 ay
-M
11 ay
-J
29 un
-J
u
17 n
-J
04 ul
-A
22 ug
-A
09 ug
-S
27 ep
-S
e
15 p
-O
03 ct
-N
21 ov
-N
09 ov
-D
27 ec
-D
ec
-21
Figure 5.8: Temporal trend of radar Backscatter for major Dune Types
The discrimination of different sand dunes is best possible in the month
of June (Figure 5.9). Various types of Dunes can be classified in the month of
June and July comparing their backscatter values (Figure 5.9).
Variability of backscatter coefficient, corresponding to different Dune
types in the month of June, is 5.75 dB (-11.75 to -17.5 dB) due to dry Soil and
no rainfall condition, whereas it is 2.75 dB (-10.5 to -13.25 dB) in August due
to rain and sparse vegetation. Higher o (-14 to -13 dB) range (blue colour in
Figure 5.2) may also be due to presence of some paleochannel loaded with
moisture which needs to be validated. The order of o of different dune types
studied (in increasing order) is as under:
Network transitional parabolic > Major obstacle > Network Sinuous >
Parabolic > Barchans and Barchanoids > Sand streaks > Linear > Transverse
> Star > Megabarchanoids
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-9
Parabolic Dune - Without Veg
-10
Parabolic Dune - With Veg
Sigma-0 (dB)
-11
Sand streaks
-12
-15
Netwok transitional parabolic Dune
- With Veg
Netwok transitional parabolic Dune
- Without Veg
Netwok transitional parabolic Dune
- bare soil (sand)
Network Sinuous Dunes
-16
Barchans and Barchanoids
-17
Major obstacle Dune
-13
-14
-18
0
June
1
July
2
Aug
3
Months→
4
Figure 5.9: Separability of different dune types in the months of June, July and
August.
5.5 HIGHLIGHTS OF THIS CHAPTER
C-band radar time-series backscatter response for the year 2000
covering the Thar Desert region was studied. The data showed the variability
of o of the order of 11.27 dB (-20.08 to -8.71 dB). Major dune types were
identified and their temporal trends were also studied. In general, high
backscattering was observed in the months of July and August and low
backscattering was observed in the months of May and June.
Over Thar Desert region lower values of o were observed and found to
vary gradually from the summer to the monsoon, and winter seasons. The
sharp change in moisture level in desert region is also reflected clearly from
o. It can also be concluded that the dune type separation using o is best
possible in the month of June. Time series analysis using scatterometer data
over many years (decades) may give better insight into the formation of the
dunes, ―dune shift‖ and spread of desertification.
The dune spacing using SRTM-DEM and its relation with o in the Thar
can also be attempted in future. The study indicated the potential of C-band
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scatterometer data for monitoring temporal variability for modelling and
monitoring desert ecosystem.
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