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Mapping of Coastal Landforms and Volumetric Change Analysis in the South West Coast of Kanyakumari, South India Using Remote Sensing and GIS Techniques ⇑ S

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Mapping of Coastal Landforms and Volumetric Change Analysis in the South West Coast of Kanyakumari, South India Using Remote Sensing and GIS Techniques ⇑ S The Egyptian Journal of Remote Sensing and Space Sciences xxx (2017) xxx–xxx Contents lists available at ScienceDirect The Egyptian Journal of Remote Sensing and Space Sciences journal homepage: www.sciencedirect.com Research Paper Mapping of coastal landforms and volumetric change analysis in the south west coast of Kanyakumari, South India using remote sensing and GIS techniques ⇑ S. Kaliraj a, , N. Chandrasekar b, K.K. Ramachandran a a Central Geomatics Laboratory (CGL), ESSO – National Centre for Earth Science Studies (NCESS), Akkulam, Thiruvananthapuram 695011, Kerala State, India b Centre for GeoTechnology, Manonmaniam Sundaranar University, Tirunelveli 627012, Tamil Nadu, India article info abstract Article history: The coastal landforms along the south west coast of Kanyakumari have undergone remarkable change in Received 29 March 2016 terms of shape and disposition due to both natural and anthropogenic interference. An attempt is made Revised 26 October 2016 here to map the coastal landforms along the coast using remote sensing and GIS techniques. Spatial data Accepted 26 December 2016 sources, such as, topographical map published by Survey of India, Landsat ETM+ (30 m) image, IKONOS Available online xxxx image (0.82 m), SRTM and ASTER DEM datasets have been comprehensively analyzed for extracting coastal landforms. Change detection methods, such as, (i) topographical change detection, (ii) cross- Keywords: shore profile analysis, (iii) Geomorphic Change Detection (GCD) using DEM of Difference (DoD) were Geomorphic Change Detection adopted for assessment of volumetric changes of coastal landforms for the period between 2000 and DEM of Differencing GIS and remote sensing 2011. The GCD analysis uses ASTER and SRTM DEM datasets by resampling them into common scale South-west coast of Kanyakumari (pixel size) using pixel-by-pixel based Wavelet Transform and Pan-Sharpening techniques in ERDAS Imagine software. Volumetric changes of coastal landforms were validated with data derived from GPS-based field survey. Coastal landform units were mapped based on process of their evolution such as beach landforms including sandy beach, cusp, berm, scarp, beach terrace, upland, rockyshore, cliffs, wave-cut notches and wave-cut platforms; and the fluvial landforms. Comprising of alluvial plain, flood plains, and other shallow marshes in estuaries. The topographical change analysis reveals that the beach landforms have reduced their elevation ranging from 1 to 3 m probably due to sediment removal or flat- tening. Analysis of cross-shore profiles for twelve locations indicate varying degrees of loss or gain of coastal landforms. For example, the K3-K30 profile across the Kovalam coast has shown significant erosion (À0.26 to À0.76 m) of the sandy beaches resulting in the formation of beach cusps and beach scarps within a distance of 300 m from the shoreline. The volumetric change of sediment load estimated based on DoD model depict a loss of 241.69 m3/km2 for 62.82 km2 of the area and land gain of 6.96 m3/km2 for 202.80 km2 of the area during 2000–2011. However, an area of 26.38 km2 unchanged by maintaining equilibrium in sediment budgeting along the coastal stretch. The study apart from providing insight into the decadal change of coastal settings also supplements a database on the vulnerability of the coast, which would help the coastal managers in future. Ó 2016 National Authority for Remote Sensing and Space Sciences. Production and hosting by Elsevier B. V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by- nc-nd/4.0/). 1. Introduction landforms of the coastal transition zone are sensitive to erosional and depositional processes due to actions of waves, littoral current, Geomorphic landforms of a coast is an expression of the charac- wind, sediment transport and certain anthropogenic activities teristics of prevailing coastal processes over long-term scale. The (Carter, 1988; Carter and Woodroffe, 1994; Bird, 2000; Bauer, 2004; Pavlopoulos et al., 2009; Chandrasekar et al., 2012). Coastal landform configurations are dependent on the pre-existing coastal Peer review under responsibility of National Authority for Remote Sensing and settings, geological structures and a variety of coastal processes. Space Sciences. ⇑ Therefore, mapping of landforms provides Insight into such Corresponding author. morpho-hydrodynamic milieu. (Davies, 1972; Nordstrom, 2000; E-mail addresses: [email protected] (S. Kaliraj), [email protected] (N. Chandrasekar), [email protected] (K.K. Ramachandran). Woodroffe, 2002; Amos, 1995; Chandrasekar and Kaliraj, 2013). http://dx.doi.org/10.1016/j.ejrs.2016.12.006 1110-9823/Ó 2016 National Authority for Remote Sensing and Space Sciences. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Please cite this article in press as: Kaliraj, S., et al.. Egypt. J. Remote Sensing Space Sci. (2017), http://dx.doi.org/10.1016/j.ejrs.2016.12.006 2 S. Kaliraj et al. / The Egyptian Journal of Remote Sensing and Space Sciences xxx (2017) xxx–xxx Along the Indian coast too, the tectonic and structural formations signature, and pattern recognition of image properties using math- and continental shelves primarily responsible for shaping the land- ematical that would be able to detect, cluster and classify the fea- forms which are acted upon subsequently by the prevailing hydro- tures to represent the real world. Previous investigations have dynamic settings characteristics (Nayak and Sahai, 1985; underlined advantages of using DEM and Lidar datasets for geo- Chandrasekar and Rajamanickam, 1995; Sajeev et al., 1997; Sanil morphic detection and volumetric change of sediment load along Kumar et al., 2006; Magesh et al., 2014). the coastal area (Shaikh et al., 1989; Anbarasu, 1994; Lillysand Most of the landforms along southern coast of Tamil Nadu par- and Kiefer, 2000; Wright et al., 2006; Waldhoff et al., 2008; ticularly on the south west coast of Kanyakumari district have Smith and Pain, 2009; Blanchard et al., 2010). Assessment of topo- undergone morphological deformation due to the effect of Tsu- graphical changes using DEMs provide insight on changes of sedi- namic occurred on December 26, 2004 (Chandrasekar et al., ment load due to erosion or deposition processes signifying past 2012). Artificial structures like groins, revetments, seawall and jet- and present morphological structural response to coastal processes ties those came up in the recent years have modified the coastal over time (Lane et al., 2003; Zhang et al., 2005; Wheaton et al., processes causing severe erosion on down-drift side in the coastal 2010; Schwendel et al., 2012). The DEM datasets acquired on two area (Kaliraj et al., 2013). Assessment of coastal landform changes different times can preferably be used to measure vertical differ- can help in the analysis of coastal vulnerability (Nicholls et al., ence in sediment loads of the coastal landforms based on topolog- 2007; Kaliraj and Chandrasekar, 2012; James et al., 2012; ical and morphometric rules (James et al., 2012). The DEM datasets Joevivek et al., 2013). Conventionally, mapping of coastal land- such as SRTM and ASTER are being used for Geomorphic Change forms is performed using pre-existing maps, field observation Detection analysis because of its mission specified accuracy, i.e. and other collateral data sources compiled for different times high vertical accuracies over terrain surface and bare soils and and different scales which can lead to inaccurate information due medium accuracies in terms of spatial resolutions (Cuartero to dynamic nature of coastal landforms (Desai et al., 1991; et al., 2004). The topographical changes of the sediment load in Embabi and Moawad, 2014). The mapping of coastal landforms the coastal landforms has been estimated from the temporal DEMs using multi-temporal satellite images can provide robust informa- using the extracted cross-shore profile analysis that provide ade- tion on shape, distribution, and morphological status during past quate information on geomorphic change of the various landforms and present (Butler and Walsh, 1998; Bocco et al., 2001; Smith in vertical scale (Gyasi-Agyei et al., 1995; Zandbergen, 2008; et al., 2006; Bubenzer and Bolten, 2008; Abermann et al., 2010). Dawson and Smithers, 2010; Hicks, 2012). The GIS-based Geomor- Recent technological advancement in remote sensing and survey- phic Change Detection (GCD) analysis provides volumetric change ing techniques provides adequate information on spatial distribu- of coastal landforms from the DEMs acquired for different periods tion of coastal landforms in GIS environment enabling us to of interval (Lee, 1991; Wheaton et al., 2007; Siart et al., 2009; prepare coastal geomorphologic map with higher granularity on James et al., 2012). The GCD analysis is concerned with DEM of Dif- a larger scalability (Chockalingam, 1993; Chandrasekar et al., ference (DoD) algorithm to estimate quantitative changes of land- 2000; Slaymaker, 2001; Nayak, 2002; Jayappa et al., 2006; Smith forms, in a diverse set of environments, and at ranges of spatial and Pain, 2009; Kaliraj and Chandrasekar, 2012). Coastal landforms scales and temporal frequencies (Wheaton et al., 2010; Hicks, of an area can be extracted using the Landsat ETM+ image with or 2012). The volumetric change of geomorphic features is estimated without slope and topographical measurements onto a GIS based using two DEM data sets acquired for two different periods can complementary platform (Mujabar and Chandrasekar, 2011). result in estimating of land loss and land gain for a vast area appro- Moreover, recent advances in remote sensing and GIS play an priately validated through field surveys and measurements important role on the development of numerical modelling of sur- (Dawson and Smithers, 2010). Maksud Kamal and Saburoh Midor- face processes for quantitative assessment of morphological ikawa (2004) have obtained the area and volume of geomorphic changes of landforms (Blanchard et al., 2010). GIS technique is an features that closely matched with field measurements.
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