Pal_et_al[1] SAR FFT Lineament IJRS
-
Upload
sanjitiitkgp -
Category
Documents
-
view
229 -
download
0
Transcript of Pal_et_al[1] SAR FFT Lineament IJRS
-
8/2/2019 Pal_et_al[1] SAR FFT Lineament IJRS
1/16
Extraction of linear and anomalous features using ERS SAR data over
Singhbhum Shear Zone, Jharkhand using fast Fourier transform
S. K. PAL{, T. J. MAJUMDAR*{ and A. K. BHATTACHARYA{
{Department of Geology and Geophysics, Indian Institute of Technology,
Kharagpur721 302, India
{Earth Sciences and Hydrology Division, Marine and Water Resources Group, Remote
Sensing Applications and Image Processing Area, Space Applications Centre (ISRO),
Ahmedabad380 015, India
(Received 14 July 2005; in final form 24 February 2006)
Digital filtering of ERS-2 SAR data using the fast Fourier transform (FFT) has
been attempted over Singhbhum shear zone (SSZ) and its surroundings for
extraction of linear and anomalous patterns. The results show that numerous
lineaments as well as drainage patterns could be identified and demarcated by
FFT digital filtering method. Major as well as several minor drainage patterns
are easily detectable from the filtered image, which are structurally controlled
and not observed in the original map. Comparison of the present interpretation
of the study area to existing geological map/earlier interpretation has been done
effectively. This technique was found to be more effective in identifying the
lineaments using ERS SAR data compared with using Landsat imagery over
the study area. The present study reveals that maximum lineaments occurring in
the north of SSZ are NNE, NNW and NW trending, while maximum lineaments
occurring in the south of SSZ are NE, ENE, WNW, and NW trending. The
demarcated geological structures may have a great significance to locate the
hidden ore/mineral occurrences. The existences of various mines, such as
Baharagora, Mosaboni, Surda, Narwa, Bhatin, Jadugoda, Rakha, and
Tatanagar along the shear zone, correlate well with the interpreted results.
1. Introduction
Linears are naturally/culturally occurring features observed in remote sensing
imagery. They are seen in remotely sensed images as a simple or composite linearfeature on the surface. Their parts align in straight or slightly curving relationships
that differ distinctly from the patterns of adjacent features in various combinations
of stream patterns, tonal changes or tonal vegetation and topographic alignments.
Presumably, a lineament expresses a subsurface phenomenon (Sabins 1997).
Lineaments, which may be continuous or discontinuous, under certain circum-
stances, may be regarded as the surface manifestation of fault and fracture zones.
These have been linked with local or regional tectonics and used as potential zones
for oil, gas and mineral exploration (Rakshit and Swaminathan 1985, Mah et al.
1995, Majumdar 1995, Sabins 1999, Briere and Scanlan 2000, Chernicoff et al.
2002).
*Corresponding author. Email: [email protected]
International Journal of Remote Sensing
Vol. 27, No. 20, 20 October 2006, 45134528
International Journal of Remote SensingISSN 0143-1161 print/ISSN 1366-5901 online # 2006 Taylor & Francis
http://www.tandf.co.uk/journalsDOI: 10.1080/01431160600658172
-
8/2/2019 Pal_et_al[1] SAR FFT Lineament IJRS
2/16
Radar is an active system which illuminates the surface with a beam of microwave
radiation. Radar is most sensitive to surface roughness and soil moisture differences
(variation in the complex dielectric constant which is a measure of the electrical
properties of surface materials). Radar can penetrate the surface micro-layer in the
soil covered areas (Prost 2001). Lineaments are extremely well manifested on SAR
images, and on several occasions structural features; for example, fractures, folds,faults etc. have been detected, as well as extended in SAR imageries. Also, look
angle and direction have a major impact on the response and manifestation of
surficial features in SAR imageries. Earlier results have shown that RADARSAT-1
C-band horizontally polarized images have been very useful for geomorphology,
geological structures and rock units mapping (Singhroy and Molch 2004, Harris
1984, Lowman et al. 1987, Masuoka et al. 1988). The SAR image is more effective
than optical imagery for studying features such as surface roughness and
topography. This is due to variation in radar backscatter as a function of
wavelength (C-band , 5.6 cm), incident angle and polarization. Useful information
on terrain morphology and surface relief (related to geological structure) is providedby SAR imagery, due to effect of radar backscatter sensitivity to slope angle and to
shadow effects caused by topographic relief (ERS-2 SAR website). An image
transform (viz. FFT, Hadamard, Haar) is a 2D spectrum derived from the
decomposition of the image data which can be utilized to extract features from
images (Pratt 1978, Majumdar 1995, Majumdar and Mohanty 1999).
2. Geological setup of the area
The regional geotectonic/geological map (Saha 1994) of the study area derived from
Landsat imagery and ground data has been presented in figure 1. The area has been
extensively surveyed using ground-based geological (Dunn 1929, Sarkar 1963, Naha
1965, Saha 1994) techniques. It has a major tectonic element (Singhbhum Shear
Zone) that separates the cratonic block (Singhbhum-Orissa Iron Ore Craton) in the
south from the Proterozoic mobile belt (Singhbhum Mobile Belt) in the north. It
runs in a northward dipping direction along a northwardly convex arcuate belt for a
length of more than 160 km from Bharagora in the east to Chakradharpur in the
west. The Singhbhum Shear Zone occurs as a curvilinear belt with an EW trend.
Singhbhum rocks, like those of other Precambrian terrains, have undergone many
phases of deformation and metamorphism. Rocks to the south of the Singhbhum
Shear Zone are relatively less metamorphosed compared with those to the north.
Rocks of Dhanjori Group are exposed in the southern part of Singhbhum Shear Zone.
This group consists of conglomerate, arkose, quartzite and lava flows. The equivalent
of the bottom part of this succession is identified as the Singhbhum Group to the
north of Singhbhum Shear Zone. Similarly, the equivalent of lava flows in the north is
called Dalma Lava. Dolerite dikes have intruded in the Singhbhum Granite and occur
mostly in the southern part of Singhbhum Shear Zone.
3. Data sources and area of interest
ERS-2 SAR Path Radiance Image (PRI)/Precision Image (Path: 0842; Row: 0198)
of 30 September 2002 over the Singhbhum Shear Zone and its surroundings,covering an area between latitudes 22u159N t o 2 3uN, and longitudes 86uE to
86u459E, has been used in this study (shown in the box in figure 1). The Precision
Image is a path oriented and system corrected product, being the basic product used
4514 S. K. Pal et al.
-
8/2/2019 Pal_et_al[1] SAR FFT Lineament IJRS
3/16
for a variety of remote sensing applications. Scene size is 100 km in range direction
and at least 102.5 km in azimuth direction. Spatial resolution is 25 m in range
direction and 15 m in azimuth direction. The registration of SAR imagery with the
rectified IRS (Indian Remote Sensing Satellite)-1C imagery has been accomplished
through image-to-image co-registration using nearest neighbourhood re-sampling
technique. The rectified precision image has been transformed from spatial domain
to frequency domain, i.e. Fourier transformed image using the fast Fourier
transform (FFT) method. Thereafter, power spectrum has been generated from this
Fourier transformed image. This power spectrum has been edited to enhance the
linear and anomalous patterns, such as, structural and tectonic configuration of thearea.
Singhbhum, particularly the western part, is full of hills alternating with valleys,
steep mountains, and deep forests on the mountain slopes. Singhbhum contains best
Sal forests and the Saranda (seven hundred hills) forest area is well known world
over. Climatologically, the study area may be divided into three seasons: Winter
from November to February, summer from March to May, and the rainy season
from June to October. The cold season is delightful while it is unpleasantly hot in the
summer season with hot westerly winds prevailing. On account of the barrier of hills
in the southeast, the atmosphere is generally dry. The rainfall is the highest in July
and August. Monsoon generally breaks in the second week of June. December andJanuary are the coldest months while April and May are the hottest.
The soil in Singhbhum has been classified mainly into three groups: rocky, red
and black soils. Rocky soil remains practically uncultivated. Red soil is spread
Figure 1. Geological map over the study area (after Saha 1994).
Extraction of linear and anomalous features using ERS SAR data 4515
-
8/2/2019 Pal_et_al[1] SAR FFT Lineament IJRS
4/16
throughout the area: it is sandy and loamy and has poor fertility. Black soil is very
fertile. Rice is the main crop.
Howrah-Nagpur and Rajkharsawan-Chaibasa-Gua railway lines are mainly used
for mineral transportations. Apart from them, there are a number of forest roads.
Singhbhum is rich in natural resources, both for minerals and forest produce.
4. Methodology
The steps involved in enhancing a digital image, f(x, y), using frequency domain
technique are: (i) to compute Fourier transform F(u, v) of f(x, y) by FFT method, (ii)
to multiply the obtained F(u, v) with a filter function H(u, v), and finally (iii) to take
the inverse Fourier transform of G(u, v), i.e., product of F(u, v) and H(u, v). The
flowchart for digital image enhancement using FFT method has been presented in
figure 2. Interpretation of the FFT filtered imagery by visual pattern recognition of
surface features resulting from variations in radar backscatter in the source image as
well as from differences in surface roughness and topography, is carried out bystudying tone, and textural variations (Masuoka et al. 1988, Paganelli et al. 2003,
Singhroy and Molch 2004).
Figure 2. Schematic diagram for FFT filtering technique.
4516 S. K. Pal et al.
-
8/2/2019 Pal_et_al[1] SAR FFT Lineament IJRS
5/16
4.1 Fast Fourier transform
Fast Fourier transform (FFT), a classical image filtering technique, is used to
convert a raster image from the spatial domain into a frequency domain image. The
FFT calculation converts the image into a series of two-dimensional sine waves of
various frequencies. The Fourier image can be edited accordingly for imageenhancement such as sharpening, contrast manipulation and smoothing. Sharpening
is achieved by using a high-pass filter whose function is to attenuate low frequencies,
whereas image smoothing is done by low-pass filter. Sometimes combination of both
low-pass as well as high-pass filters, known as band pass filter, is used. In the
frequency domain, the high-pass filter is implemented by attenuating the pixel
frequencies with the help of different window functions, viz. Ideal, Bartlett
(Triangular), Butterworth, Gaussian, Hanning and Hamming etc. (ERDAS 2001).
Let us consider a function f(x, y) of two variables x and y, where x50, 1, 2, , N
2 1, and y50, 1, 2, , M2 1. The function f(x, y) represents digital value of an
image in the xth row, yth column; Mand Nare the maximum numbers of rows and
columns in the image which are multiple of two. Then the forward Fourier
transform of f(x, y) is defined as (Gonzalez and Woods 1992, Jahne 1993)
F u, v ~ 1MN
XM{1
x~0
XN{1
y~0
f x, y exp{j2p ux=Mzvy=N 1
for u50, 1, 2, , N21, v50, 1, 2, , M 2 1 and j~ffiffiffiffiffiffiffiffi{1
p; u and v are the
frequency variables.
The inverse Fourier transform of F(u, v) returns to f(x, y) which is defined as
f x,y ~XM{1
u~0
XN{1
v~0
F(u, v)expj2p(ux=Mzvy=N) 2
for x50, 1, 2, , N2 1, and y50, 1, 2, , M2 1. Equations (1) and (2) are known
as frequency transform pair.
4.2 Interpretation of ERS SAR FFT filtered imagery
The dielectric constant of a rock at radar wavelength is specially influenced by the
water content of the rock. Dry rock has a dielectric constant of the order of 38,
whereas that of water is 80. With increasing moisture content in the rock the
dielectric constant will increase almost linearly. De Loor (1982) has given a generalreview of dielectric properties of wet materials. The depth penetration in soil and
rock material is inversely related to the dielectric constant, but directly to the radar
wavelength used. In moist rocks and soils the depth penetration will be only skin-
deep. In dry sand area a reasonable penetration can be obtained with the use of
radar of longer wavelength (Koopmans 1983).
The most important radar parameters for lineament mapping are:
(i) look direction, which determines the preferential enhancement of the terrain;
(ii) incidence angle, which affects the topographic enhancement; and
(iii) spatial resolution, which affects the amount of fine structural detail to be
seen (Harris 1984).
Rock type (lithology) has no obvious effect on radar return in the area with forest
cover as is the case in Singhbhum. However, structure and major lithologic units can
Extraction of linear and anomalous features using ERS SAR data 4517
-
8/2/2019 Pal_et_al[1] SAR FFT Lineament IJRS
6/16
be delineated through their topographic expression (Lowman et al. 1987, Sabins
1999).
The filtered images have been interpreted for identification of structural features,
lineaments and fracture/fault planes. The lineaments are readily identifiable surface
features due to tone, contrast and textural variations associated with topographic
variation, lithological transition, and drainage patterns, whereas fracture planes and
(or) fault planes are linear features along the offset between sets of lineaments. The
resulting lineaments have been analysed in regional geological context, compiled,
and plotted on Rose diagrams to outline the variability in strike directions. The
identified lineaments have been compared with the known regional structural
trends.
Figure 3. Filtered enhanced image of the study area after IFT of filtered power spectrumusing (i) low-pass filter with Butterworth window (D053500, LFG51, HFG50) and (ii) high-pass filter with Ideal window (D0550, LFG50, HFG51).
4518 S. K. Pal et al.
-
8/2/2019 Pal_et_al[1] SAR FFT Lineament IJRS
7/16
5. Results and discussion
ERS-2 SAR path radiance data of the study area has been transformed into Fourier
image using FFT. Fourier image has been edited in frequency domain and then
transformed back to spatial domain to get the enhanced linear and anomalous
patterns. In order to band pass the particular frequency range through this Fouriermagnitude image (power spectrum), lower frequency components of radius 3500
(D025u2 + v2) has been suppressed using a low pass filter with the help of
Butterworth window function (low frequency gain, LFG51.5, high frequency gain,
HFG50) and high frequency components of radius 50 has been suppressed with the
help of Ideal window function (LFG50, HFG51.5). Finally the filtered spectrum is
transformed back to spatial domain to obtain the Fourier filtered image (figure 3).
Similarly, some other band pass filters have also been tested with different radii, viz.,
using various window functions (figures 4 and 5) for better topographic as well as
Figure 4. Filtered enhanced image of the study area after IFT of filtered power spectrumusing (i) low-pass filter with Butterworth window (D053500, LFG51.5, HFG50.3) and(ii) high-pass filter with Ideal window (D05100, LFG50, HFG51.5).
Extraction of linear and anomalous features using ERS SAR data 4519
-
8/2/2019 Pal_et_al[1] SAR FFT Lineament IJRS
8/16
surface features enhancement, which aids in interpretation of lineaments expressedby physiographic features, surface geology transitions and/or associated vegetation
coverage variations. The filtered images exhibit numerous linear and anomalous
patterns over the study area (figures 35). The interpreted linear and anomalous
features have been overlapped on the enhanced SAR image (figure 6). Finally, the
interpreted map of the lineament and drainage patterns in the study area has been
prepared and presented in figure7. However, since the look-direction is towards west in
ERS SAR image with descending (NS) passes, main features including the Singhbhum
Shear Zone, Dalma Thrust Belt, Rakha mines area (Dhanjori formation), and the
Subarnarekha river which are almost perpendicular to eastwest direction have been
enhanced (figures 1, 6 and 7). Also, rock type (lithology) has no obvious effect on radarreturn in the area with forest cover as is the case in Singhbhum (Lowman et al. 1987,
Sabins 1999). But orientation of radar look direction to the topographic and tectonic
grain of the terrain is useful for studies in structural geology (Harris 1984).
Figure 5. Filtered enhanced image of the study area after IFT of filtered power spectrumusing (i) low-pass filter with Gaussian window (D054000, LFG52, HFG50.1) and (ii) high-pass filter with Ideal window (D05300, LFG50, HFG52).
4520 S. K. Pal et al.
-
8/2/2019 Pal_et_al[1] SAR FFT Lineament IJRS
9/16
The topographic enhancement reflected by brightness contrast, texture and tonal
variation between Singhbhum-Orissa Iron Ore Craton in the south and SinghbhumMobile Belt in the north, interpreted as Singhbhum Shear Zone (SSZ). The
structural mapping of the study area has been divided into two major parts, north of
the Singhbhum Shear Zone and south of the Singhbhum Shear Zone. In the
southern part of SSZ, WNW, NW, and NNW trending lineaments and NE trending
fractures/faults are delineated by brightness contrast and texture variation over the
Dhanjori group of meta-volcanics and meta-sediments. The NE, NNE, ENE, and
NW trending lineaments are observed over Singhbhum granite and Gurumahisani
Group (figures 6 and 7). Besides, a few folds having closures towards the east with
axial plane traces running EW have been identified in the southern part of SSZ. In
the northern part of SSZ, lineaments over the Dalma Volcanic have been tracedalong the major Dalma fold. These lineaments have NW, NNW, NE, and NNE
trends. Some NE and NW trending fractures/faults have been delineated across
these lineaments. Another prominent shear zone has been identified due to high
Figure 6. Overlap of structural features on the FFT enhanced ERS-2 SAR imagery.
Extraction of linear and anomalous features using ERS SAR data 4521
-
8/2/2019 Pal_et_al[1] SAR FFT Lineament IJRS
10/16
tonal and textural variations between Dalma Volcanic and Singhbhum Group.
Kuilpal granite in the centre of Singhbhum group occurring north of DalmaVolcanics, has been demarcated by the distinct lineaments. Some folds having
closures towards south with axial plane traces trending NS, are observed over the
Dalma volcanic range, whereas some other folds, having closures towards east, with
Figure 7. Structural map of the study area as interpreted from the FFT filtered ERS-2 SARimage.
4522 S. K. Pal et al.
-
8/2/2019 Pal_et_al[1] SAR FFT Lineament IJRS
11/16
axial plane traces running EW, are identified over the Singhbhum group in the
north-west part of the study area. High contrast and darker tone emphasize the
main drainage pattern of the study area. Summary of lineament orientations is
presented in table 1. The synoptic Rose diagrams of lineaments and fractures/faults
orientation have been presented in figure 8. A total of 805 structural features have
been identified, out of which 695 are linear features (lineament/fault/fracture) and110 are folds/curvilinear features. The identified linear features have vector mean of
value 88 with circular variance 0.59 and circular standard deviation 78. The number
of linear features identified in the north of SSZ is 382, which have a vector mean of
value 156 with circular variance 0.32 and circular standard deviation 49, whereas the
number of linear features identified in the south of SSZ is 313, which have a vector
mean of value 81 with circular variance 0.27 and circular standard deviation 45. The
identified linear features in the north of SSZ have greater circular variance as well as
greater standard deviation than that of linear features in the south of SSZ which
clearly indicate that the rocks in the area north of SSZ have undergone several
phases of deformation compared to the rocks in the area south of SSZ (Sarkar andChakraborty 1982).
From the overall study, it is clear that maximum lineaments occurring in the
north of SSZ are NNE, NNW and NW trending, while maximum lineaments
occurring in the south of SSZ are NE, ENE, WNW, and NW trending. The major
river in the study area, Subarnarekha, as delineated from the filtered SAR imagery is
observed to be running almost parallel along the northern boundary of SSZ for
some distance, and then following intermittently in between the SSZ and Dalma
volcanic (figure 6). High contrast and darker tone emphasize the main drainage
pattern of the study area. It can be concluded that the major river, Subarnarekha
and its tributaries, are structurally controlled. Some short length seasonal streams
Table 1. Summary of lineaments orientation as identified from FFT filtered ERS-2 SARimagery.
Lineament trendTotal number of
lineamentVectormean
Circularvariance
Circular standarddeviation (u)
South of SSZNorth-northeast 26 18 0.01 9North-east 81 46 0.01 9
East-northeast 70 77 0.01 9West-northwest 65 105 0.01 9North-west 57 134 0.01 8North-northwest 14 163 0.01 7Total lineament to the southof SSZ
313 81 0.27 45
North of SSZNorth-northeast 92 15 0.01 9North-east 51 42 0.01 8East-northeast 55 72 0.01 9West-northwest 50 106 0.01 8North-west 50 135 0.01 9
North-northwest 84 163 0.01 7Total lineament to the northof SSZ
382 156 0.32 49
Total lineament 725 92 0.62 82
Extraction of linear and anomalous features using ERS SAR data 4523
-
8/2/2019 Pal_et_al[1] SAR FFT Lineament IJRS
12/16
are also found to be structurally controlled in the south-western part of the studyarea as observed from the digitally enhanced image. Subarnarekha river crosses
Dalma volcanic ridge near Burudhi at an obtuse angle, while one tributary of the
Subarnarekha river, Dudh Nadi crosses the Dhanjori volcanic ridge almost
orthogonally, which indicates the existence of a prominent fractures/faults in this
region (Geological Survey of India 1998). In addition, numerous fractures/cross-
fractures/faults have also been mapped over the study area from the filtered SAR
imagery, as can be seen from figures 6 and 7. These demarcated structures have great
significance from the economic point of view since they can be host to various
mineralized bodies along the weak zones. The various mines, such as, Baharagora,
Mosaboni, Surda, Narwa, Bhatin, Jadugoda, Rakha, and Tatanagar are along theshear zone, which are also identifiable from the processed SAR image.
The structural interpretation map of a part of the present study area, as generated
by Majumdar (1995) using FFT techniques on Landsat imagery and the
Figure 8. Synoptic Rose diagram representing different lineament trends interpreted onFFT filtered ERS-2 SAR imagery.
4524 S. K. Pal et al.
-
8/2/2019 Pal_et_al[1] SAR FFT Lineament IJRS
13/16
corresponding Rose diagram have been presented in figures 9 (a) and (b), whereas
the structural map of the same area interpreted from the present study and the
corresponding Rose diagram are shown in figures 10 (a) and (b). The comparison of
figures 9 and 10 reveals that the present study is more effective for delineation ofstructural features.
6. Conclusions
The present study shows that digital filtering technique using fast Fourier transform
on ERS SAR imagery is an effective tool for extraction of linear and anomalous
Figure 9. (a) Structural interpretation map of a part of the present study area carried out byMajumdar (1995) on Landsat imagery using FFT techniques. (b) Synoptic Rose diagram.
Figure 8. (Continued.)
Extraction of linear and anomalous features using ERS SAR data 4525
-
8/2/2019 Pal_et_al[1] SAR FFT Lineament IJRS
14/16
patterns in a tectonically disturbed area. The present study reveals that maximum
lineaments occurring in the north of SSZ are NNE, NNW and NW trending, while
maximum lineaments occurring in the south of SSZ are NE, ENE, WNW, and NW
trending. Also, numerous linear features, faults/fractures and folds could be
identified and demarcated using this technique on SAR imagery which may have a
great significance to locate the hidden ore/mineral occurrences. Since a number of
transformations have occurred during last 1800 Ma in SSZ because of collisions of
two plates, identification of these linears and comparison with earlier results will be
helpful for tectonic studies in this region. Corresponding Rose diagrams are very
helpful for quantification of lineament occurrences. Major, as well as several minor,
drainage patterns which are structurally controlled, are easily detectable in thefiltered image. It is found to be more suitable and effective in delineating lineaments,
as well as drainage patterns, in the study area using ERS SAR data than that
obtained earlier from Landsat imagery using the same FFT technique. However,
cultural linears/systematic noise patterns will also be extracted which need to be
discarded during final interpretation.
Acknowledgements
The authors wish to thank the anonymous referees for their critical comments and
suggestions for the improvement of the manuscript. They are also thankful to Dr R.
R. Navalgund, Director, SAC, Dr K. L. Majumder, Deputy Director, RESIPA/SAC and Dr S. R. Nayak, Group Director, MWRG/RESIPA for their keen interest
in this study. Thanks are due to Shri R. Bhattacharyya and Shri S. Chatterjee,
ESHD for their help at various stages of this activity.
Figure 10. (a) Structural map of the same area as interpreted in the present study. (b)Synoptic Rose diagram.
4526 S. K. Pal et al.
-
8/2/2019 Pal_et_al[1] SAR FFT Lineament IJRS
15/16
ReferencesBRIERE, R.P. and SCANLAN, M.K., 2000, Lineaments and Lithology Derived from a Side-
Looking Airborne Radar Image of Puerto Rico (Woods Hole, MA: US Geological
Survey).
CHERNICOFF, C.J., RICHARDS, J.P. and ZAPPETTINI, E.O., 2002, Crustal lineament control on
magmatism and mineralization in northwestern Argentina: geological, geophysical,and remote sensing evidence. Ore Geology Reviews, 21, pp. 127155.
DE LOOR, G.P., 1982, Dielectric properties of wet materials. Proceedings of the IGRASS82
Conference, Munich.
DUNN, J.A., 1929, The geology of north Singhbhum. Mem. Geological Survey of India, 54,
166 pp.
ERDAS MANUAL 8.5, Field Guide, 2001, 698 pp.
ERS-2 SAR. Available online at: http://www.ga.gov.au/acres/prod_ser/levels.htm (accessed 12
May 2005).
GEOLOGICAL SURVEY OF INDIA, 1998, Quadrangle Geological Map No. 73 J. (Geological
Survey of India, Calcutta).
GONZALEZ, R.C. and WOODS, R.E., 1992, Digital Image Processing, 716 pp. (MA: Addison-Wesley).
HARRIS, J., 1984, Lineament mapping of Central Nova Scotia using Landsat-MSS and
Seasat-SAR imagery. Proceedings of the 9th Canadian Symposium on Remote Sensing,
1417 August 1984, Newfoundland, pp. 359373.
JAHNE, B., 1993, Digital Image Processing, 383 pp. (Berlin: Springer-Verlag).
KOOPMANS, B.N., 1983, Side-looking radar, a tool for geological surveys. Remote Sensing
Reviews, 1, pp. 1969.
LOWMAN, P.D., HARRIS, J., MASUOKA, P.M., SINGHROY, V.H. and SLANEY, V.R., 1987,
Shuttle Imaging Radar (SIR-B) investigations of the Canadian Shield: Initial report.
IEEE Transactions on Geoscience and Remote Sensing, V. GE-25, No.1, pp. 5566.
MAH, A., TAYLOR, G.R., LENNOX, P. and BALIA, L., 1995, Lineament analysis of LandsatThematic Mapper Images, Northern Territory, Australia. Photogrammetric
Engineering and Remote Sensing, 61, pp. 761773.
MAJUMDAR, T.J., 1995, Application of fast Fourier transform over a part of Singhbhum shear
zone for extraction of linear and anomalous features. ITC Journal, 3, pp. 241245.
MAJUMDAR, T.J. and MOHANTY, K.K., 1999, Textural classification of single band SIR-B
data over a part of Brahmaputra Basin, India. GeoCarto International, 14, pp. 6166.
MASUOKA, P.M., HARRIS, J., LOWMAN, P.D. and BLODGET, W., 1988, Digital processing of
orbital radar data to enhance geologic structure: examples from the Canadian Shield.
Photogrammetric Engineering and Remote Sensing, 54, pp. 621632.
NAHA, K., 1965, Metamorphism in relation to stratigraphy, structure and movements in parts
of east Singhbhum, eastern India. Quarterly Journal of Geology, Mineralogy andMetallurgy Society of India, 37, pp. 4188.
PAGANELLI, F., GRUNSKY, E.C., RICHARD, J.P. and PRYDE, R., 2003, Use of RADARSAT-1
principal component imagery for structural mapping: a case study in the Buffalo
Head Hills area, northern central Alberta, Canada. Canadian Journal of Remote
Sensing, 29, pp. 111140.
PRATT, W.K., 1978, Digital Image Processing, 750 pp. (New York, NY: John Wiley & Sons).
PROST, G.L., 2001, Remote Sensing for Geologists: A Guide to Image Interpretation. Gordon
and Breach Science Publishers, Second edition, USA.
RAKSHIT, A.M. and SWAMINATHAN, V.L., 1985, Application of digitally processed and
enhanced LANDSAT imagery, for geological mapping and mineral targeting in the
Singhbhum Precambrian mineralized belt, Bihar-Orissa. International Journal ofRemote Sensing, 6, pp. 457471.
SABINS JR, F.F., 1997, Remote Sensing: Principles and Interpretation, 494 pp. (New York, NY:
W.H. Freeman & Co).
Extraction of linear and anomalous features using ERS SAR data 4527
-
8/2/2019 Pal_et_al[1] SAR FFT Lineament IJRS
16/16
SABINS JR, F.F., 1999, Remote sensing for mineral exploration. Ore Geology Reviews, 14, pp.
157183.
SAHA, A.K., 1994, Crustal evolution of Singhbhum-North Orissa, Eastern India. Mem.
Geological Society of India, 27, 341 pp.
SARKAR, A.N. and CHAKRABORTY, D., 1982, One orogenic belt or two? A structure
reinterpretation supported by Landsat data products of the Precambrian meta-morphics of Singhbhum, Eastern India. Photogrammetria, 37, pp. 185201.
SARKAR, S.N., 1963, On the occurrence of two intersecting Precambrian orogenic belts in
Singhbhum and adjacent areas. Indian Geological Magazine, 100, pp. 6992.
SINGHROY, V. and MOLCH, K., 2004, Geological Applications of RADARSAT-2. Canadian
Journal of Remote Sensing, 30, pp. 893902.
4528 Extraction of linear and anomalous features using ERS SAR data