mapping of coastal landforms and volumetric change analysis in the south west coast of kanyakumari south india using remote sensing and gis techniques

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 b Central Geomatics Laboratory (CGL), ESSO – National Centre for Earth Science Studies (NCESS), Akkulam, Thiruvananthapuram 695011, Kerala State, India Centre for GeoTechnology, Manonmaniam Sundaranar University, Tirunelveli 627012, Tamil Nadu, India a r t i c l e i n f o Article history: Received 29 March 2016 Revised 26 October 2016 Accepted 26 December 2016 Available online xxxx Keywords: Geomorphic Change Detection DEM of Differencing GIS and remote sensing South-west coast of Kanyakumari a b s t r a c t The coastal landforms along the south west coast of Kanyakumari have undergone remarkable change in terms of shape and disposition due to both natural and anthropogenic interference An attempt is made here to map the coastal landforms along the coast using remote sensing and GIS techniques Spatial data sources, such as, topographical map published by Survey of India, Landsat ETM+ (30 m) image, IKONOS 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) crossshore profile analysis, (iii) Geomorphic Change Detection (GCD) using DEM of Difference (DoD) were adopted for assessment of volumetric changes of coastal landforms for the period between 2000 and 2011 The GCD analysis uses ASTER and SRTM DEM datasets by resampling them into common scale (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 to m probably due to sediment removal or flattening 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/bync-nd/4.0/) Introduction Geomorphic landforms of a coast is an expression of the characteristics of prevailing coastal processes over long-term scale The Peer review under responsibility of National Authority for Remote Sensing and Space Sciences ⇑ Corresponding author E-mail addresses: s.kaliraj@ncess.gov.in (S Kaliraj), profncsekar@gmail.com (N Chandrasekar), raman.kk@ncess.gov.in (K.K Ramachandran) landforms of the coastal transition zone are sensitive to erosional and depositional processes due to actions of waves, littoral current, wind, sediment transport and certain anthropogenic activities (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 settings, geological structures and a variety of coastal processes Therefore, mapping of landforms provides Insight into such morpho-hydrodynamic milieu (Davies, 1972; Nordstrom, 2000; 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 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 and continental shelves primarily responsible for shaping the landforms which are acted upon subsequently by the prevailing hydrodynamic settings characteristics (Nayak and Sahai, 1985; Chandrasekar and Rajamanickam, 1995; Sajeev et al., 1997; Sanil Kumar et al., 2006; Magesh et al., 2014) Most of the landforms along southern coast of Tamil Nadu particularly on the south west coast of Kanyakumari district have undergone morphological deformation due to the effect of Tsunamic occurred on December 26, 2004 (Chandrasekar et al., 2012) Artificial structures like groins, revetments, seawall and jetties those came up in the recent years have modified the coastal processes causing severe erosion on down-drift side in the coastal area (Kaliraj et al., 2013) Assessment of coastal landform changes can help in the analysis of coastal vulnerability (Nicholls et al., 2007; Kaliraj and Chandrasekar, 2012; James et al., 2012; Joevivek et al., 2013) Conventionally, mapping of coastal landforms is performed using pre-existing maps, field observation and other collateral data sources compiled for different times and different scales which can lead to inaccurate information due to dynamic nature of coastal landforms (Desai et al., 1991; Embabi and Moawad, 2014) The mapping of coastal landforms using multi-temporal satellite images can provide robust information on shape, distribution, and morphological status during past and present (Butler and Walsh, 1998; Bocco et al., 2001; Smith et al., 2006; Bubenzer and Bolten, 2008; Abermann et al., 2010) Recent technological advancement in remote sensing and surveying techniques provides adequate information on spatial distribution of coastal landforms in GIS environment enabling us to prepare coastal geomorphologic map with higher granularity on a larger scalability (Chockalingam, 1993; Chandrasekar et al., 2000; Slaymaker, 2001; Nayak, 2002; Jayappa et al., 2006; Smith and Pain, 2009; Kaliraj and Chandrasekar, 2012) Coastal landforms of an area can be extracted using the Landsat ETM+ image with or without slope and topographical measurements onto a GIS based complementary platform (Mujabar and Chandrasekar, 2011) Moreover, recent advances in remote sensing and GIS play an important role on the development of numerical modelling of surface processes for quantitative assessment of morphological changes of landforms (Blanchard et al., 2010) GIS technique is an effective platform for mapping thematic features with corresponding attributes Geo-computational algorithms facilitates automatic extraction of geomorphic landforms from the combination of datasets such as, satellite image, DEM and topographical map using numerical modelling, pixel-based classification and cellular automated techniques in GIS environment (Dawson and Smithers, 2010) High spatial resolution images of IKONOS, Quick Bird, and GeoEye incorporated with DEMs are progressively used for assessment of volumetric changes of coastal landforms (Bubenzer and Bolten, 2009; James et al., 2012) The mapping of geomorphic landforms using remotely sensed images requires knowledge of basic interpretation elements such as tone, texture, shape, size and pattern, for unambiguous delineation of landforms For example, the beaches and associated landforms have been identified based on linear shape and fine to medium coarse pattern (Rao, 2002) Landforms are interpreted using multispectral images based on interpretation element keys to extract the information relatively accurate up to the post-field verification process (Maksud Kamal and Saburoh Midorikawa, 2004) According to Tomar and Singh, 2012, the coastal landforms are classified on the basis of topographical variations resulting from differential erosion and accretion processes, for example, the geomorphic units of alluvial plain, pediplain, structural hills and residual hills are mapped using DEM incorporated multispectral IRS-ID LISS-III images using visual interpretation technique along with field check While digital analysis of landform extraction is faster, appropriate based on spectral signature, and pattern recognition of image properties using mathematical that would be able to detect, cluster and classify the features to represent the real world Previous investigations have underlined advantages of using DEM and Lidar datasets for geomorphic detection and volumetric change of sediment load along the coastal area (Shaikh et al., 1989; Anbarasu, 1994; Lillysand and Kiefer, 2000; Wright et al., 2006; Waldhoff et al., 2008; Smith and Pain, 2009; Blanchard et al., 2010) Assessment of topographical changes using DEMs provide insight on changes of sediment load due to erosion or deposition processes signifying past and present morphological structural response to coastal processes over time (Lane et al., 2003; Zhang et al., 2005; Wheaton et al., 2010; Schwendel et al., 2012) The DEM datasets acquired on two different times can preferably be used to measure vertical difference in sediment loads of the coastal landforms based on topological and morphometric rules (James et al., 2012) The DEM datasets such as SRTM and ASTER are being used for Geomorphic Change Detection analysis because of its mission specified accuracy, i.e high vertical accuracies over terrain surface and bare soils and medium accuracies in terms of spatial resolutions (Cuartero et al., 2004) The topographical changes of the sediment load in the coastal landforms has been estimated from the temporal DEMs using the extracted cross-shore profile analysis that provide adequate information on geomorphic change of the various landforms in vertical scale (Gyasi-Agyei et al., 1995; Zandbergen, 2008; Dawson and Smithers, 2010; Hicks, 2012) The GIS-based Geomorphic Change Detection (GCD) analysis provides volumetric change of coastal landforms from the DEMs acquired for different periods of interval (Lee, 1991; Wheaton et al., 2007; Siart et al., 2009; James et al., 2012) The GCD analysis is concerned with DEM of Difference (DoD) algorithm to estimate quantitative changes of landforms, in a diverse set of environments, and at ranges of spatial scales and temporal frequencies (Wheaton et al., 2010; Hicks, 2012) The volumetric change of geomorphic features is estimated using two DEM data sets acquired for two different periods can result in estimating of land loss and land gain for a vast area appropriately validated through field surveys and measurements (Dawson and Smithers, 2010) Maksud Kamal and Saburoh Midorikawa (2004) have obtained the area and volume of geomorphic features that closely matched with field measurements Stereopair of images are able to provide three-dimensional representations of the features through accurate derivation of digital elevation models (DEMs) The topographical changes of landforms estimated from these datasets have positive correlation with field measurements and hence useful for monitoring how landforms change over time due to subsidence or uplift of the coastal surface (Cuartero et al., 2004; Mith and Clark, 2005) Knight et al., 2011 have incorporated images and DEMs for rapid assessment of landform changes for large areas and have demonstrated that the remote sensing provides complete requirements if synergized with ground validation and measurements which can even be extended to geomorphological studies across all spatial scale Mapping of landforms through field observation allows the most direct way to capture the landform characteristics and enable as a basis for terrain assessment and geomorphological analysis The accuracy of field mapping is subjective and affected by the skills and experience of one who maps The volumetric change of sediment load estimated using DEMs are capable of generating superior results on land loss and land gain that are relatively closer to the fieldbased measurements apart from providing spatial ensemble of coastal landforms with exceptional details (Smith and Pain, 2006) Many researchers have confirmed that the DEM derived results along with field data can produce relatively high accuracy in geomorphic change measurement for coastal area (Aniello, 2003; Nikolakopoulos et al., 2006; Zandbergen, 2008; Potts et al., 2008; Toutin, 2008; Blanchard et al., 2010) The primary aim of 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 S Kaliraj et al / The Egyptian Journal of Remote Sensing and Space Sciences xxx (2017) xxx–xxx the present study is to map coastal landforms and assess the volumetric change of sediment load over a decade along the south-west coast of Kanyakumari using integrated remote sensing and GIS techniques The present study therefore used different change detection techniques such as (i) topographical change analysis, (ii) cross-shoreprofile change analysis, (iii) DEM of Difference (DoD) algorithm based Geomorphic Change Detection (GCD) analysis for estimating the volumetric changes (land loss or land gain) along the coastal stretch using the ArcGIS platform This studyapart from assimilating decadal changes in landforms would also delineate various influencing factors that would form primary information source for coastal vulnerability management and would help in the preparation of developmental plans against any possible natural disasters that likely to affect the coastal region Study area The study area is located along the south-west coast of Kanyakumari district, Tamil Nadu, India The geographical coordinates extend from 77°90 49.2000 E to 77°340 15.0000 E longitude and 8°60 32.6000 N to 8°140 15.3000 N latitude The coastal stretch is extended for a length of 58 km from Kanyakumari to Thengapattinam in southeast to northwest direction (Fig 1) There are three major drainage networks such as Pazhayar, Valliyar and Thamirabarani along with their tributaries flowing in southerly direction from the Western Ghats These are primary sources contributing discharge to maintain coastal landforms debouching their sedi- ment load during both southwest and northeast monsoons (Chandrasekar and Mujabar, 2010) The coastal area is characterized by various landforms such as sandy beaches, coastal plains, beach terraces, sand dunes, rocky shore, estuaries and other fluvio-marine landforms (Kaliraj et al., 2013) The coastal upland in the Kanyakumari, Muttam and Colachel area are mainly associated with rocky-shores and offshore outcrops acting as natural barrier to wave actions and storm surges Sandy beaches are formed on the Sanguthurai, Chothavilai, Pillaithoppu, Ganapathipuram, Rajakkamangalam, Colachel and Simonkudiyiruppu coastal stretches due to swashing of large amount of sediments resulting from waves (Hentry et al., 2010) However, the major parts of the coastal areas namely Kovalam, Pallam, Manavalakurichi, Mandaikadu and Inayamputhenthurai are noticed with severe erosional activities due to backwashing of sediments by destructive wave actions Onshore margin of the study area comprises Late Quaternary deposits composed of complex settings of granite-biotiteilluminate underlain sandstone interlined with sand, silt and clay partings and overlaid by sandy materials (Loveson, 1993) The coastal surface is generally sloping towards sea interspersed with settlements, coconut plantation, shallow water bodies like backwater and creeks (Jena et al., 2001; Magesh et al., 2014) Along the near shore area, the sand dunes are roughly parallel to shore though discontinuously distributed along the coast The coastline along the Kanyakumari coast have experienced erosion due to high-energy wave action The Teri sand dunes (reddish brown) are located along the coastal stretch from Kovalam to Manakudi with thickness increasing from 1.5 m in coastal headlands to a maximum of 7.0 m in the interior terrestrial area The crystalline Fig Geographical location of the study area 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 S Kaliraj et al / The Egyptian Journal of Remote Sensing and Space Sciences xxx (2017) xxx–xxx rock types such as quaternary rocks, clay sand and sandy materials are predominantly found along the coast The rocky boulders and sea cliffs are found in the Muttam, Kanyakumari and Cape Comorin coasts and sandstones are found along the study area are made up of igneous rock, and silt clay materials (Loveson, 1993) The alluvial sediments admixture with clay are found deposited at the mouth of the Thamirabarani estuary in Thengapattinam and Pazhayar estuary in Manakudi Sandstone with clay intercalation structures is present along the eastern part of Thengapattinam coast The study area is prevailing with a sub-tropical climate with the normal annual rainfall varying from 826 mm to 1456 mm and the annual mean minimum and maximum temperatures are 23.78 °C–33.95 °C respectively The landforms along the coast frequently alter in morphological distribution due to both natural and anthropogenic factors and hence the present study is performed to understand coastal landforms and their changes 2.1 Coastal and oceanographic characteristics of the study area Evolution of coastal landforms in various locations along the study area is mainly subject to ocean and coastal processes Wave height is one of the main factors considered in setting up of hazard management system along the coastal region Mean significant wave height along the coast is estimated around 1.4 m rendering higher energy along the coast causing erosion or subsidence of beaches (Hentry et al., 2012) The low-energy waves (with wave height