Access the full text.
Sign up today, get DeepDyve free for 14 days.
Loading next page...
/lp/taylor-francis/lineaments-of-kodaikanal-palani-massif-southern-granulitic-terrain-of-CxiQyyuC8h
References
References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.
- Publisher
- Taylor & Francis
- Copyright
- © 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
- ISSN
- 2474-9508
- DOI
- 10.1080/24749508.2018.1452477
- Publisher site
- See Article on Publisher Site
Abstract
GeoloGy, ecoloGy, and landscapes, 2018 Vol . 2, no . 3, 188–202 https://doi.org/10.1080/24749508.2018.1452477 INWASCON OPEN ACCESS Lineaments of Kodaikanal-Palani massif, Southern Granulitic Terrain of Tamil Nadu, India: a study using SRTM DEM and LANDSAT satellite’s OLI sensor’s FCC N. Jawahar Raj and A. Prabhakaran d epartment of Geology, national c ollege, Tiruchirappalli, India ABSTRACT ARTICLE HISTORY Received 2 november 2017 In the present study an attempt has been made to study the lineaments of the Kodaikanal– a ccepted 29 d ecember 2017 Palani massif of Tamil Nadu in southern India. Lineaments extracted from eight different azimuth angles of the SRTM DEM, and Landsat-8 satellite’s OLI sensor’s FCC were integrated to generate KEYWORDS a lineament data base for the study area. The extracted lineaments were analysed using ArcGIS Kodaikanal hills; palani hills; and Rockworks software to obtain information regarding the number, length, predominant lineaments; sRTM’s deM; orientations of lineaments extracted individually from both data, and the final output. These olI’s Fcc apart spatial variation in lineament density has also been analyzed. Estimations from the final lineament output shows that, 2167 lineaments with their total length being 2997.63 km. Areas of high lineament density are found in the western and north western parts of Kodaikanal Taluk. NE–SW directions are predominant orient direction followed by those orienting in N–S and NW– SE directions, and these orientations are in agreement with the trends of the regional geological structures. Distinct variations in the estimations made of the lineaments extracted from SRTM and OLI data is found to exist. About 40 and 38% of the lineaments of the study area are discernible only in the SRTM data and OLI data, respectively and are not found in each other; only 22% of the lineaments of the study area are found commonly in both the data. Furthermore, NW–SE orienting lineaments are more discernible in SRTM data whereas N–S orienting lineaments are more discernible in OLI data. These variations underlines the fact that lineament mapping using any single data source as has been widely followed will not be adequate to give a reliable picture about the lineaments of an area, and further the study stresses the need to extract lineaments from varied satellite images and integrate them to get a reliable picture of the lineaments. 1. Introduction Remotely sensed data, both aerial photographs and satellite images have been used extensively to extract e t Th erm lineament is defined as a mappable linear or lineaments. While aerial photographs were widely used curvilinear feature of a surface whose parts align in a in the initial years, satellite images have become the most straight or slightly curving relationship that may be the common data source since the last two decades towards expression of a fault or other linear zones of weakness, extracting the lineaments. Sensor data such as Enhanced as derived from remote sensing sources such as opti- em Th atic Mapper (ETM), ETM , (Panchromatic) PAN, cal imagery, radar imagery or digital elevation models Advanced Spaceborne e Th rmal Emission and Ree fl ction (Sabins, 1996). Understanding of the lineaments of an Radiometer (ASTER) and Shuttle Radar Topography area can be useful for wide-ranging applications in vari- Mission (SRTM) have been widely used for the purpose. ous fields of geosciences. It was initially used mainly for For extracting lineaments from these sensor data a num- the exploration of petroleum (Blanchet, 1957; Mollard, ber of manual, semi-automatic and automatic techniques 1957) and later its utility expanded to other fields such as are employed and in recent years a number of automated groundwater detection, mineral exploration, recognition lineament extraction techniques are being used. Some of geological structures such as folds and faults, identi- of these techniques include Hough Transform (Argialas fication of seismic prone areas, landslide hazard inves- & Mavrantza, 2004; Wang et al., 1990), Lineament tigations, landform studies, detection of hot springs, Extraction and Stripe Statistical Analysis (Zlatopolsky, pollution migration and dispersion studies, prediction 1992), Segment Tracing Algorithm (Ni, Zhang, Liu, Yan, of possible sites of caves, various fields of civil engineer - & Li, 2016), Haar Transform (Majumdar & Bhattacharya, ing more commonly in studies pertaining to site selec- 1988; Porwik & Lisowska, 2004), Lineament Extraction tion for the construction of dams, power plants, bridges, roads, etc., and for selection of routes for laying roads algorithm of PCI Geomatica software (Hubbard et al., and in the selection of areas for new settlements. 2012). For the analysis of the extracted lineaments CONTACT n. Jawahar Raj njrtrichy@gmail.com © 2018 The a uthor(s). published by Informa UK limited, trading as Taylor & Francis Group. This is an open a ccess article distributed under the terms of the creative c ommons a ttribution license (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. GEOLOGY, ECOLOGY, AND LANDSCAPES 189 Figure 1. s tudy area. s ource: Information obtained from survey of India open s eries Map. Geographical Information System (GIS) technique has part of the largest block of them viz., the Madurai crustal become a powerful and an indispensible tool in view of block (Meert et al., 2010). This crustal block underwent its ability to process quickly, store results quantitatively extensive deformation and metamorphosed to granu- and also to generate maps which facilitate the study of lite facies during the Neoproterozoic (Bartlett, Harris, their spatial distribution. Dougherty, Hawkesworth, & Santhosh,1998; Cenki et al., 2004; Santosh, Tanaka, Yokoyama, & Collins, 2005). e s Th tudy of the ultrahigh-temperature metamorphic 2. The study area and its geological setting assemblages from a number of localities of this block e s Th tudy area, Kodaikanal–Palani massif, located in the reveal that the peak conditions inferred for the Ultra south central part of Tamil Nadu State in India is geo- High Temperature (UHT) rocks of this crustal block are graphically situated between north latitudes 9°54′56′′– in the range of 7–11 kbar and 950–1150 °C. The age 10°29′06′′ and east longitudes 77°12′03′′–77°49′56′′ of this metamorphism has been established as ranging (Figure 1), and forms part of the Survey of India’s top- between 600 and 480 Ma (; Braun & Kriegsman, 2003; ographic sheets 58 F/4, 7, 8, 11, 12, 15 and 58 G/5 of Clark et al., 2009; Collins, Santosh, Braun, & Clark,2007) 1:50,000 scale. Most part of the study area except the demonstrating that this metamorphism was synchro- southern part lies in the Kodaikanal Taluk of Dindigul nous with the final stages of Gondwana amalgamation District (Figure 2). The southern part lies in eni Th (Collins & Pisarevsky, 2005). The age of the Kodaikanal– District (confining to a portion of Uttamapalaiyam and Palani massif has been estimated to be late Archaean Periyakulam Taluks). e Th study area is bounded by the to early Palaeoproterozoic (ca. 2.54–2.43, Bartlett et al., Kerala State on its west, Palani and Dindigul Taluks of 1998; Brandt et al., 2011; Ghosh et al., 2004). Dindigul District on the north and east, respectively, Information relating to the rock types of the study and, Periyakulam and Uttamapalaiyam Taluks of Theni area was obtained from the Quadrangle map (58 F and District of Tamil Nadu State on the South. The areal G) of 1: 250,000 scales, published by the Geological extent of the study area is 1682.87 sq. km. The study area Survey of India in the year 1989. Charnockite is the has attracted the attention of geoscientists (Thanavelu, predominant rock of the study area (Figure 3) Table 2012), in view of the frequent landslides that occurs in 1 covering about 86% (465 sq. km) of the study area. the study area especially during the rainy season. Hornblende biotite gneiss is the other rock which e r Th egion in which the study area is located is referred occupy considerable portion, especially in the Palani as Southern Granulitic Terrain (SGT) and is composed of Taluk that falls within the study area, covering about a number of crustal blocks of which the study area forms 11% (192.55 sq. km) of the study area. The other rocks 190 N. JAWAHAR RAJ AND A. PRABHAKARAN Figure 2. a dministrative divisions. s ource: c ompiled information obtained from survey of India open s eries Map and Taluk map published by Government of Tamil nadu. Figure 3. Rock types. s ource: Information obtained from published geology map by Geological survey of India. occupy only meagre portion of the study area and these laterite and aeolian sands. Of these rocks the oldest rock include granite, anorthosite, granite gneiss, basic dyke, in the study area is calc. granulite. Younger to this rock calc. granulite, along with calcareous mud and clay, is the charnockite which is predominantly garnet-free GEOLOGY, ECOLOGY, AND LANDSCAPES 191 Table 1. Rock types of the study area and their areal extent. lineaments for the study. The DEM oer ff s visual per - spective capability, accentuation of terrain features, and Sl. No. Rock types Area (in sq. km) Area (in %) application of the three-dimensional analysis system, (1) a eolian sands 2.83 0.17 (2) laterite 1.76 0.10 and as such, it avoids the problem associated with the (3) c alcareous mud and clay 3.84 0.23 lack of stereo coverage in the imagery. Topographic (4) Basic dyke 0.86 0.05 (5) Granite gneiss 5.72 0.34 features which represent lineaments such as straight (6) anorthosite 6.06 0.36 valleys, continuous scraps, straight streams segments (7) Granite 27.20 1.62 (8) Hornblende biotite 192.55 11.44 and rock boundaries, systematic off set of streams, gneiss sudden tonal variations and alignment of vegetation (9) charnockite 1441.79 85.67 (10) c alc. granulite 0.26 0.02 were visually interpreted and digitized on screen. Such Total 1682.87 100.00 extraction of lineaments of the study area was carried out in eight different azimuth angles (45°, 90°, 135°, 180°, 225°, 270°, 315° and 360°) in order to facilitate consisting of hypersthene, biotite, plagioclase, perthite their extraction to the maximum possible extent. and quartz. The charnockites of the study area are of Furthermore, interpretation of lineaments at each of intermediate composition with a tonalitic to granitic these azimuth angles was done at two different scales affinity (Valdiya, 2016). Later tectonic activity and met- (1:50,000 and 1:80,000 scales) to ensure mapping of lin- amorphism has led to the retrogression of the granulites, eaments of all sizes. The extracted lineaments from each giving rise to granitic gneiss (which are confined to the azimuth angle were compared with other data sources western part of the study area) and hornblende biotite such as topographic maps, high resolution Google gneiss (which are found in the northern and western images, etc., to eliminate non-geological lineaments. margins of the study area). Extensive migmatization, This elimination of non-geological lineaments was presumably during the orogenic period was marked by performed for all the eight lineament maps extracted emplacement of later intrusive of granite, the remnants from the eight different azimuth angles. After this elim - of which are confined to the western parts of the study ination process, rest of the other lineaments in each of area. Anorthosite is confined to the north east margin the eight different azimuth angles was stored in eight and it occurs as elliptical body closely associated with different separate GIS shape files. This was followed the charnockites. Linear dykes of doleritic composition by combining all the lineaments obtained from these are found to occur within the hornblende biotite gneissic eight different shape files into a single shape file. From areas especially in the north eastern part of the study this output the redundant/duplicate lineaments were area. All the above described rocks are of Archaean eliminated and the merged SRTM lineament output age. These apart, calc. mud and clay, and laterites of of the study area was generated and was kept ready Tertiary age also occur but are limited in areal extent. for the analysis. This was followed by the generation Aeolian sands are of Quaternary age are also found and of False Colour Composite (FCC) from the Landsat-8 are restricted to a portion of the Uttamapalaiyam Taluk satellite’s OLI sensor data. This OLI sensor’s FCC image in the southern part of the study area. A major shear was visually interpreted onscreen for lineaments, and zone viz., the Karur–Kambam–Painavu–Trichur Shear after eliminating non-geological linear such as roads, Zone (KKPTSZ) cuts through the study area in a nearly topographic ridges, agricultural field boundaries, etc., NE–SW direction (Brandt et al., 2011; Plavsa et al., 2012; the lineament map was finalized (Figure 6). In the Shazia et al., 2015; Singh et al., 2006). next stage, the lineaments extracted from these two different data sets (SRTM DEM MERGED output and 3. Methodology OLI’s FCC image) were merged together into a sin- gle output. During this process, redundant or dupli- The present study has been accomplished in three stages cate lineaments were eliminated. This output has been where in the first stage, literature relevant to the pres- ent study which includes those relating to the various referred in the text as the final lineament output. In the aspects of lineaments, rock types, geological structure next stage estimations such as number of lineaments, and tectonic history of the study area were collected, length of lineaments and lineament density were made compiled and reviewed. This has been done to have a using Arc GIS software. Orientation of the lineaments thorough understanding of the theme under study. The of the study area was also analyzed using Rockworks second stage pertains to the extraction of lineaments. software – 2016 version (www.rockwork.com), one of Shuttle Radar Topographic Mission (SRTM) satellite the most commonly used software for the purpose. All data and Landsat-8 satellite’s OLI sensor data, both of these estimations and analysis were done for all the 9 May 2016, were freely downloaded from the website eight different azimuth angles and their merged out- – http://earthexplorer.usgs.gov/ for the purpose. The put of the SRTM data, OLI’s FCC image and for the SRTM satellite data was made use of to generate Digital final lineament output. The results of the analysis are Elevation Model (DEM) to facilitate the extraction of discussed in the following section. 192 N. JAWAHAR RAJ AND A. PRABHAKARAN area. Medium sized and longer lineaments constitute 4. Results about 11 and 4% of the total lineaments, respectively, Estimations regarding the number of lineaments in the while very long lineaments are few in number (25), con- study area from the SRTM DEM data (in eight different stituting just less than 2% of the total number of line- azimuth angles and their merged output), FCC data of aments of the study area. Further, in case of the final the OLI sensor, and, the final lineament output (which lineament output also, very short and short lineaments includes the final merged output of the SRTM DEM are predominating and they together constitute about and the OLI sensor’s FCC image) were made. The total 82% of the total number of lineaments of the study area. number of lineaments in the study area compiled from Medium sized and longer lineaments constitute about 11 all eight azimuth angles of the SRTM DEM merged out- and 4% of the total lineaments, respectively, while very put is 1351. Amongst the eight different azimuth angles, long lineaments are few in number (49), constituting the maximum number of lineaments (701 lineaments) just above 2% of the total number of lineaments of the was extracted from the 45° azimuth angle output, whilst study area. the least number of lineaments (363) was extracted Lineament density is the total length of all linea- from 225° azimuth angle. The numbers of lineaments ments divided by the area under consideration (1 sq. extracted from other azimuth angles were within these km in the present study). For understanding the spatial two extremes. In case of OLI sensor’s FCC image, lin- variation in lineament density in the study area, a grid eaments were extracted only from one azimuth angle of cells, 1 sq. km each was overlaid over the lineament as there is no option for viewing it in different azimuth map (Final lineament output) of the study area and the angles unlike SRTM DEM, and the number of linea- length of lineaments in each grid was estimated (Table ments extracted from it is 1307. The final lineament 3). Based on the range of the lineament density values output generated aer m ft erging the lineaments from the of the grids spread over the study area, different linea- merged output (1351 lineaments) of SRTM data and the ment density categories were demarcated by drawing OLI sensor’s FCC image (1307 lineaments), and elimi- isolines. Thus a map showing various lineament density nating the redundant lineaments (491) is found to con- zones was prepared using ArcGIS software and is shown sist of 2167 lineaments. in Figure 7. In the study area lineament density varies Estimations regarding the length of lineaments in the from 0 to 4.3 km/sq. km. The study area was demar - study area from the SRTM DEM image (in eight different cated into three different lineament density classes such azimuth angles Figure 4(a)–(h) and final merged output as low (<1 km/sq. km), moderate (1–2 km/sq. km) and Figure 4(i)), FCC data of the OLI sensor Figure 5, and, high (>2 km/sq. km). The lineament density is found the final lineament output Figure 6 were made (Table 2) to be moderate in most part of the study area covering using ArcGIS software. The total length of lineaments in about 61% (1023.82 sq. km) of the study area. It is found the study area compiled from all eight azimuth angles of to be high in about 26% (435.10 sq. km) of the study the SRTM DEM merged output is 1820.05 km. However area and such high density areas are confined mainly the number of lineaments extracted from each of the to the three patches, the largest of which is found in the eight different azimuth angles varied from 585.99 km western and north western parts of the study area espe- (225° azimuth angle) to 881.52 km (45° azimuth angle). cially in the western parts of Kodaikanal Taluk (Palani In case of FCC generated from the OLI sensor image the hills Northern Slope West Reserved Forest and Umaiyar total length of lineaments extracted from it is 1772 km. Hill Reserved Forest). e Th other patch, comparatively e t Th otal length of lineaments from the final lineament smaller, is located in the north eastern part of the study output is 2997.63 km. area especially in the north eastern part of Kodaikanal Taluk (Palani hills Northern Slope East Reserved Forest. Based on the length of the lineaments, the extracted e t Th hird patch, a narrow, linear and discontinuous one lineaments were classified into very short (<1 km.), short runs through Kodaikanal town, in the central part of the (1–2 km), medium (2–3 km), long (3–4 km) and very study area, in a NE–SW direction. Lineament density is long (>4 km) lineaments. Estimations show that in case found to be low in about 13% of the study area and such of the merged output of SRTM DEM, very short and low density class is found confined mostly to the fringes short lineaments are found to be more in number with of the study area. 602 and 544 lineaments, respectively, constituting about e Th analysis of rose diagrams constructed for lin- 85% of the total number of lineaments of the study area. eament outputs of each of the eight different azimuth Medium sized and longer lineaments constitute about 9 angles of the SRTM DEM (Figure 8(a)–(h)) reveals that and 4% of the total lineaments, respectively, while very the lineaments are oriented predominantly in an NE– long lineaments are few in number (27), constituting just SW direction in five azimuth angles viz., 90°,135°, 270°, 2% of the total number of lineaments of the study area. 315° and 360°. Even in case of the other three azimuth In case of OLI sensor’s FCC also, very short and short angles, NE–SW is one of the predominant orientation of lineaments are predominating, together they constitute about 83% of the total number of lineaments of the study the lineaments, though NW–SE is more predominating GEOLOGY, ECOLOGY, AND LANDSCAPES 193 Figure 4. (a) lineaments extracted by 45° a zimuth angle. (b) lineaments extracted by 90° a zimuth angle. (c) lineaments extracted by 135° a zimuth angle. (d) lineaments extracted by 180° a zimuth angle. (e) lineaments extracted by 225° a zimuth angle. (f ) lineaments extracted by 270° a zimuth angle. (g) lineaments extracted by 315° a zimuth angle. (h) lineaments extracted by 360° a zimuth angle. (i) d em merged output. s ource: (a-h) shuttle Radar Topography mission s atellite's deM data obtained from online Resources and (i) Generated from shuttle Radar Topography mission s atellite's deM data. in case of 45° and 180° azimuth angles, and nearly N–S lineaments in the study area, reveal that in case of the orientation in case of 135° and 225°. In case of the merged output of SRTM DEM, very short lineaments merged output (Figure 8(i)), the lineaments are pre- are found to be dominantly oriented in three directions, dominantly oriented in NE–SW and NW–SE directions. viz., NE–SW, NW–SE and near N–S directions (Figure e Th lineaments extracted from the OLI sensor image is 11). e Th shorter lineaments are predominantly oriented predominantly oriented in a near N–S direction (Figure in NE–SW direction (Figure 11(b)). In case of moder- 9), and lineaments oriented in NE–SW direction are next ate-sized lineaments two distinct preferred orientations in importance. From the analysis of rose diagram con- (NE–SW and near N–S) was observed (Figure 11(c)). structed for the final output (Figure 10), it is observed e Th longer and very longer lineaments are found to be that the lineaments of the study area are oriented in predominantly oriented in NNE–SSW (Figure 11(d)) diverse directions. However those orienting in NE–SW and NE–SW (Figure 11(e)) directions, respectively. directions are found to be predominant, followed by N–S Lineaments extracted from the OLI sensor’s FCC image and NW–SE orienting lineaments. shows that very short lineaments are predominantly ori- Rose diagrams constructed to understand the ented in two directions viz., near N–S and NNW–SSE existence of any size-wise preferred orientation(s) of directions (Figure 12(a)). The shorter lineaments are 194 N. JAWAHAR RAJ AND A. PRABHAKARAN Figure 4. (Continued) predominantly oriented in NE–SW direction (Figure DEM obscures the detection of these lineaments posing 12(b)). The moderate-sized lineaments are predomi- limitations in mapping lineaments. Though a glance at nantly oriented in three directions viz., NE–SW, near the number of lineaments extracted from these two dif- N–S and NW–SE directions (Figure 12(c)) while the ferent data sources seems less, a deeper analysis reveals longer lineaments are predominantly oriented in NE– interesting facts. During the process of compiling all SW direction (Figure 12(d)). Very long lineaments are the lineaments extracted from both the merged SRTM also oriented predominantly in NE–SW in addition DEM and OLI sensor’s FCC data towards generating to ENE–WSW direction (Figure 12(e)). In case of the the final lineament output, it was observed there were final lineament output of the study area, very short line - 491 (i.e., 22.66% of the total lineaments) redundant aments are predominantly oriented in a near N–S direc- lineaments i.e., found in both the data. The remaining tion (Figure 13(a)). All the other sized lineaments are 860 lineaments (39.69%) extracted from SRTM DEM predominantly oriented in a NE–SW direction (Figure data is exclusively extractable only from it and is not 13(b)–(e)). The moderate-sized lineaments in addition identifiable in OLI’s FCC. Similarly the remaining 816 to the NE–SW direction are also predominantly oriented lineaments (37.66%) extracted from OLI’s FCC are in NNE–SSW direction. exclusively extractable only from it and is not identi- fiable in ASTER DEM output. This clearly shows that lineament extraction from any one data source will 5. Discussion be grossly insufficient to get a complete picture of the Estimation of the number of lineaments from the final lineaments of an area. Further, analysis of the number lineament output has shown that altogether there are of lineaments from various azimuth angle reveal that 2167 lineaments of varied sizes in the study area. In case the number of lineaments extractable varies widely in of SRTM DEM’s merged output it is 1371 whereas it is different azimuth angles. Extraction of lineaments was slightly less (1307) in case of OLI sensor’s FCC. This in relatively easier from the 45° azimuth angle output as spite of the fact that while the lineaments of the merged the maximum number of lineaments was extracted from output of the SRTM data is a compilation of lineaments this output. But even from this output the proportion of extracted from eight different azimuth angles, whereas the lineaments extracted from this azimuth angle is only the lineaments of the OLI sensor’s FCC is only from 52% of the total lineaments of the merged SRTM data, one azimuth angle. This is due to the reason that linear and in case of other azimuth angles, the proportion is vegetation patterns are easily detectable in FCC and are still lesser. This underlines the inadequacy of extract- less discernible in DEM. In addition the shadow effect in ing lineaments from any single azimuth angle, which GEOLOGY, ECOLOGY, AND LANDSCAPES 195 Figure 5. lineaments extracted from lansat olI. s ource: From landsat 8 s atellite's olI s ensor obtained from online Resources. Figure 6. Final output. s ource: Generated both from sRTM and landsat 8 olI satellite images. 196 N. JAWAHAR RAJ AND A. PRABHAKARAN Table 2. Total number of lineaments in sRTM deM image. a particular sensor may not be apparent in another azi- muth angle or in another sensor. Hence mapping of lin- SRTM DEM eaments from any single satellite image/product may be Angles (in Total length (in Sl. No. degrees) Total numbers km) inadequate to provide a reliable picture on the number (1) 45 701 881.52 of lineaments of an area. This stresses the need to make (2) 90 398 701.62 use of a variety of satellite data as possible to enhance (3) 135 400 687.57 (4) 180 436 744.59 the identification of lineaments. (5) 225 363 585.99 Analysis of the length of the lineaments from the final (6) 270 464 621.81 lineament output reveals that the total length of linea- (7) 315 372 627.57 (8) 360 414 614.41 ments from the final lineament output is 2997.63 km. (9) Merged 1351 1820.05 e len Th gth of lineaments extracted from OLI sensor’s FCC is 1772 km, which is only slightly lesser than the length (1820.05 km) extracted from the merged output Table 3. lineament density classes and their areal extent. of SRTM DEM. This in spite of the fact that while the Lineament density lineaments of the merged output of the SRTM data is a Range (km/ Density Area (in sq. compilation of lineaments extracted from eight differ - Sl. No. sq. km) class km) Area (in %) ent azimuth angles, the lineaments of the OLI sensor’s (1) <1 low 223.95 13.31 (2) 1−2 Moderate 1023.82 60.84 FCC is only from one azimuth angle. es Th e variations in (3) >2 High 435.10 25.85 the length of lineaments extracted from varied sources Total 1682.87 100.00 reinforces the suggestion put forth, that any one satellite image may not be adequate to map the lineaments of an has been the common practice in mapping lineaments area, and as many varied data should be utilized to get a from DEM generated from SRTM/ASTER satellite reliable picture about the lineaments of an area. Further, images. Similar view has been put forth by Jawahar Raj the analysis of the length of lineaments extracted from et al. (2017) from the study of lineaments of the neigh- the eight azimuth angles of the SRTM DEM data reveals bouring Kolli hills. Furthermore, the study stresses the that the length is maximum in 45° azimuth angle out- need to extract lineaments from such DEMs from as put but still it constitutes only about 48.43% of the total many azimuth angles as possible to get a more reliable length of lineaments of the study area, obtained from the picture. The above discussion clearly brings to light the merged SRTM DEM output. This underlines the inade- fact that lineaments identifiable at an azimuth angle or quacy of extracting lineaments from any single azimuth Figure 7. lineament density. s ource: Generated both from sRTM and landsat 8 olI satellite images. GEOLOGY, ECOLOGY, AND LANDSCAPES 197 e f Figure 8. (a–h) orientation of lineaments extracted from sRTM deM. (i) orientation of lineaments – from the merged output of sRTM deM. angle, which has been the common practice in mapping lineaments of varied sizes from the final lineament out- lineaments from satellite image. Furthermore, the study put. In case of the SRTM DEM merged output and OLI’s stresses the need to extract lineaments from as many FCC also very short and short lineaments are predom- azimuth angles as possible to get a more reliable picture. inant and their proportion is almost similar (85 and Amongst the varied sizes of the lineaments, the very 83%, respectively). This clearly shows the remarkable short and short lineaments are found to be predominant consistency in the proportion of very short and short (constituting 82% of the total lineaments) as revealed lineaments irrespective of the data used towards the from the analysis of the estimation of the number of extraction of lineaments. 198 N. JAWAHAR RAJ AND A. PRABHAKARAN Figure 9. orientation of lineaments extracted – from landsat-8 Figure 10. orientation of lineaments (both from sRTM deM and s atellite’s olI sensor’s Fcc. olI sensor’s Fcc ). e lin Th eament density map prepared from the final direct relationship with degree of rock fracturing (Edet lineament output reveal that in the study area, linea- et al., 1998)/shearing (Chandrasekhar et al., 2011), per- ment density is high in areas closer to the KKPTSZ, meability of rocks (Masoud & Koike, 2011), ground- the major shear zone of the region. Also the lineament water yield from wells (Sener et al., 2005), degree of density maxima axis is parallel to the orientation of the hazardness especially relating to slope failures (Kiran & trend of the KKPTSZ. In view of the lineament density’s Ahmed, 2014), etc., it can be concluded that in the areas Figure 11. orientation of lineaments of varied sizes extracted from sRTM deM. GEOLOGY, ECOLOGY, AND LANDSCAPES 199 Figure 12. orientation of lineaments of varied sizes extracted from landsat-8 s atellite’s olI sensor. of high lineament density of the study area viz., Palani India, [GSI], 2006; Jayananda et al., 1995; Unnikrishnan- hills Northern Slope West Reserved Forest, Palani hills Warrier et al., 1995). However amongst these diverse Northern Slope East Reserved Forest and Umaiyar Hill orientations, the lineaments orienting in NE–SW direc- Reserved Forest areas, the degree of rock deformation is tions are predominant, followed by those orienting in likely to be high with the resultant higher degree of rock N–S and NW–SE directions. All these three orientations fracturing and shearing making these areas unsuitable (besides ENE-WSW) are the predominating orientations for the construction of dams and reservoirs as the pos- of the lineaments of the Indian Subcontinent (Rakshit sibility of water leakages into the subsurface, slope and & Prabhakar Rao, 1989), and also the Tamil Nadu State dam failures and rate of sedimentation would be high. (Geological Survey of India, 2006). The predominant However, these areas could be targeted for groundwater orientation of the lineaments (NE–SW) of the study area exploitation. corresponds well with the orientation of the KKPTSZ, e a Th nalysis of predominant orientation(s) of the the major shear zone that passes through the study area. lineaments of the study area (as inferred from the final u Th s the results of the analysis of the predominant orien - lineament output) shows that the lineaments of the study tations of the study area is in agreement with the results area are oriented in diverse directions reflecting the mul- of previous studies conducted pertaining to this region tiple episodes of deformation events that have occurred and with prominent geological structures of the study in the region through geologic time (Bartlett, Harris, area. Hawkesworth, & Santhosh,1995; Chetty & Bhaskar A comparative analysis of the predominant orienta- Rao, 2006; Drury & Holt, 1980; Geological Survey of tion(s) of lineaments extracted from the SRTM DEM 200 N. JAWAHAR RAJ AND A. PRABHAKARAN Figure 13. orientation of lineaments of varied sizes: sRTM deM + landsat-8 s atellite’s olI sensor. and OLI sensor’s FCC data show that while the linea- and OLI sensor’s FCC shows that in general NE–SW ments extracted from SRTM DEM data are found to be orienting lineaments are predominating irrespective of oriented predominantly in NE–SW direction followed lineament size with the exception of very short linea- by NW–SE direction, the lineaments extracted from OLI ments where distinct difference in their predominant sensor image are found to be oriented predominantly directions exists in both the data. While in case of SRTM in a near N–S direction followed by NE–SW direction. DEM, their predominant orientation is NE–SW, this es Th e results show that the NE–SW orienting lineaments direction is insignificant in case of OLI sensor’s FCC are easily identifiable in both the data whereas the NW– where they are predominantly oriented in a near N–S SE orienting lineaments and N–S orienting lineaments and NNW-SSE directions. This clearly reflects the easy are more discernible in SRTM DEM data and OLI sen- identification of NE–SW orienting shorter lineaments sor’s FCC data, respectively. from SRTM DEM data, and also the easy identification e a Th nalysis of the orientation of lineaments of var - of near N–S, and NNW-SSE orienting shorter linea- ied sizes, shows that in the study area the predominant ments from OLI sensor’s FCC. The results once again orientation of the lineaments of varied sizes deduced underlines the fact that lineament mapping using any from the final lineament output is found to be NE–SW single data like SRTM DEM /ASTER DEM/SWIR/FCC direction, with the exception of very short lineaments as has been widely followed will not be adequate to give a which are predominantly oriented in a near N–S direc- reliable picture about the lineaments of an area, and fur- tion. Comparison of the predominant orientations of ther stresses the need to extract lineaments from varied lineaments of varied sizes extracted from SRTM DEM satellite images to get a reliable picture of the lineaments. GEOLOGY, ECOLOGY, AND LANDSCAPES 201 Chetty, T. R. K., & Bhaskar Rao, Y. J. (2006). Constrictive 6. Conclusion deformation in transpressional regime, field evidence e p Th resent study provides a new lineament database from the Cauvery Shear Zone, Southern Granulite Terrain, India. Journal of Structural Geology, 28, 713–720. including the number and length of lineaments, line- Clark, C., Collins, S., Timms, N. E., Kinny, P. D., Chetty, T. R. ament density, predominant orientation of lineaments K., &Santhosh, M. (2009). SHRIMP U–Pb age constraints for the Kodaikanal–Palani massif which could useful for on magmatism and high-grade metamorphism in the several applications including developmental and man- Salem Block, southern India. Gondwana Research, 16, agement planning of the hills. It has also demonstrated 27–36. the inadequacy of mapping lineaments from any single Collins, A. S., Santosh, M., Braun, I., & Clark, C. (2007). Age and sedimentary provenance of the Southern Granulites, satellite data as has been widely adopted and strongly South India: U– Th–Pb SHRIMP secondary ion mass underlines the need to extract lineaments from a variety spectrometry. Precambrian Research, 155, 125–138. of satellite data to get a more reliable picture about the Collins, A. S., & Pisarevsky, S. A. (2005). Amalgamating lineaments of the area under study. eastern Gondwana: The evolution of the Circum-Indian Orogens. Earth-Science Reviews, 71, 229–270. Drury, S. A., & Holt, R. W. (1980). The tectonic framework of the South Indian craton: A reconnaissance involving Disclosure statement LANDSAT imagery. Tectonophysics, 65, T1–T15. Edet, A. E., Okereke, C. S., & Esu, E. O. (1998). Applications No potential conflict of interest was reported by the authors. of remote sensing data to groundwater exploration: A case study of the Cross River State, SE Nigeria. Hydrogeology Journal, 6, 394–404. doi:10.1007/s100400050162 References Geological Survey of India. (2006). Geology and mineral Argialas, D. P., & Mavrantza, O. D. (2004, July 12–23). resources of the states of India Tamil Nadu and Pondicherry Comparison of edge detection and Hough transform (Miscellaneous Publication No. 30). G.S.I, Chennai, 71p. techniques for the extraction of geologic features. In Ghosh, J. G. Wit, M. J. D., Zartman, R. E. (2004). Age and O. Altan (Ed.), Proceedings XXth ISPRS Congress of the tectonic evolution of neoproterozoic ductile shear zones in International Society of Photogrammetry and Remote the Southern Granulite Terrain of India with implications Sensing, Istanbul, Turkey. ISPRS Archives XXXV (Part for Gondwana Studies. Tectonics, 23, TC3006. B3), (pp. 790–795). Retrieved from http://www.isprs.org/ Hubbard, B. E., Mack, T. J., & Thompson, A. L. (2012). proceedings/XXXV/congress/comm3/papers/376.pdf Lineament analysis of mineral areas of interest in Bartlett, J. M., Harris, N. B. W., Hawkesworth, C. J., & Afghanistan (28 p). U.S. Geological Survey Open-File Santhosh, M. (1995). New isotope constraints on the Report 2012–1048. crustal evolution of South India and pan-African granulite Jayananda, M., Janardhan, A. S., Sivasubramanian, P., metamorphism. Memoir of Geological Society of India, 34, & Peucat, J. J. (1995). Geochronologic and Isotopic 391–397. constraints on granulite formation in the Kodaikanal area, Bartlett, J. M., Harris, N. B. W., Dougherty, Jon S., Southern India. Memoir Geological Society of India, 34, Hawkesworth, C. J., & Santhosh, M. (1998). The 373–390. application of single zircon evaporation and model Nd Jawahar Raj, N., Prabhakaran, A., & Muthukrishnan, A. ages to the interpretation of polymetamorphic terrains: an (2017). Extraction and Analysis of Geological Lineaments example from the Proterozoic mobile belt of south India. of Kolli Hills, Tamil Nadu: A study using remote sensing Contributions to Mineralogy and Petrology, 131(2–3), 181– and GIS. Arabian Journal of Geosciences, 10, 195. doi:10.1007/s12517-017-2966-4 Blanchet, P. H. (1957). Development of fracture analysis as Kiran, Raj S., & Ahmed, S. A. (2014). Lineament extraction exploration method. Bulletin of the American Association from Southern Chitradurga Schist belt using Landsat TM, of Petroleum Geologists, 41(8), 1748–1759. ASTERGDEM and geomatics techniques. International Brandt, S., Schenk, V., Raith, M. M., Appel, P., Gerdes, Journal of Computer Applications, 93(12), 12–20. A., &Srikantappa, C. (2011). Late neoproterozoic P-T Majumdar, T. J., & Bhattacharya, B. B. (1988). Application of evolution of HP-UHT granulites from the palni hills the Haar transform for extraction of linear and anomalous (South India): New constraints from phase diagram patterns over part of Cambay Basin, India. International modelling, LA-ICP-MS zircon dating and in situ EMP Journal of Remote Sensing, 9(12), 1937–1942. monazite dating. Journal of Petrology, 52, 1813–1856. Masoud, A., & Koike, K. (2011). Auto-detection and doi:10.1093/petrology/egr032 integration of tectonically significant lineaments from Braun, I., & Kriegsman, L. M. (2003). Proterozoic crustal SRTM DEM and remotely-sensed geophysical data. ISPRS evolution of southernmost India and Sri Lanka. Geological Journal of Photogrammetry and Remote Sensing, 66, 818– Society, London, Special Publications, 206, 169–202. Cenki, B., Braun, I., & Brocker, M. (2004). Evolution of Meert, J. G., Pandit, M. K., Pradhan, V. R., Banks, J., the continental crust in the Kerala Khondalite Belt, Sirianni, R., Stroud, M.,Newstead, B., & Gifford, J. (2010). southernmost India: Evidence from Nd isotope mapping, Precambrian crustal evolution of Peninsular India: A 3.0 U–Pb and Rb–Sr geochronology. Precambrian Research, billion year odyssey. Journal of Asian Earth Sciences, 39, 134, 275–292. 483–515. Chandrasekhar, P., Martha, T. R., Venkateswarlu, N., Mollard, J. D. (1957). Aerial photographs aid petroleum Subramanian, S. K., & Kamaraju, M. V. V. (2011). Regional search. Candian Oil and Gas Industries, 10(7), 89–96. geological studies over parts of Deccan Syneclise using Ni, C.Z., Zhang, S., Liu ,C., Yan, Y., & Li, Y. (2016). Lineament remote sensing and geophysical data for understanding length and density analyses based on the segment tracing hydrocarbon prospects. Current Science, 100(1), 95–99. algorithm: A case study of the Gaosong Field in Gejiu Tin 202 N. JAWAHAR RAJ AND A. PRABHAKARAN Mine, China. Mathematical Problems in Engineering. Article F., & Sajeev, K. (2015). Linking monazite geochronology ID 5392453, 1–7, doi:10.1155/2016/5392453 with fluid infiltration and metamorphic histories: Nature Plavsa, D., Collins, A. S., Foden, J. F., Kropinski, L., Santosh, and experiment. Lithos, 236–237, 1–15. doi:10.1016/j. M., Chetty,T. R. K., & Clark, C. (2012). Delineating lithos.2015.08.008 crustal domains in Peninsular India: Age and chemistry Singh, A. P., Kumar, N., , & Singh, B. (2006). Nature of the of orthopyroxene-bearing felsic gneisses in the Madurai crust along Kuppam–Palani geotransect (South India) Block. Precambrian Research, 198–199, 77–93. from gravity studies: Implications for Precambrian Porwik, P., & Lisowska, A. (2004). The Haar-Wavelet continental collision and delamination. Gondwana transform in digital image processing: Its status and Research, 10, 41–47. achievements. Machine Graphics & Vision, 13(1–2), 79–98. aTh navelu, C. (2012). Landslide hazard zonation on Rakshit, A. M., & Prabhakar Rao, P. (1989). Megalineaments macroscale of Kodaikanal hills, Dindigul district, Tamil on the face of the Indian sub-continent and their geological Nadu. Records of the Geological Survey of India, 144 (5), significance. Memoirs of Geological Sur vey of India, 12, 233. 17–24. Unnikrishnan-Warrier, C., Santosh, M., & Yoshida, M. Sabins, F. F. (1996). Remote sensing: Principles and (1995). First report of Pan-African Sm—Nd and Rb— interpretation (3rd ed., 494p). New York, NY: W. H. Sr mineral isochron ages from regional charnockites of Freeman and Company. southern India. Geological Magazine, 132(3), 253–260. Santosh, M., Tanaka, K., Yokoyama, K., & Collins, A. S. (2005). Valdiya, K. S. (2016). e m Th aking of India: Geodynamic Late Neoproterozoic Cambrian felsic magmatism along evolution (2nd ed., 924p). Switzerland: Springer. transcrustal shear zones in southern India: U-Pb electron Wang, P. J., & Howarth, P. J. (1990). Use of the Hough microprobe ages and implications for the amalgamation transform in automated lineament detection. IEEE of the Gondwana supercontinent. Gondwana Research, 8, Transactions on Geoscience and Remote Sensing, 28(4), 31–42. 561–567. Sener, E., Davraz, A., & Ozcelik, M. (2005). An integration Zlatopolsky, A. A. (1992). Program LESSA (lineament of GIS and remote sensing in groundwater investigations: extraction and stripe statistical analysis) automated linear A case study in Burdur, Turkey. Hydrogeology Journal 13: image features analysis – Experimental results. Computers 826–834. and Geosciences, 18(9), 1121–1126. Shazia, J. R., Harlov, D. E., Suzuki, K., Kim, S. W., Girish- Kumar, M.,Hayasaka, Y., Ishwar-Kumar, C., Windley, B.
Journal
Geology Ecology and Landscapes – Taylor & Francis
Published: Jul 3, 2018
Keywords: Kodaikanal hills; Palani hills; lineaments; SRTM’s DEM; OLI’s FCC