Scholarly article on topic 'A Study on the Shoreline Changes and LAND-use/ Land-cover along the South Gujarat Coastline'

A Study on the Shoreline Changes and LAND-use/ Land-cover along the South Gujarat Coastline Academic research paper on "Earth and related environmental sciences"

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Procedia Engineering
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{"Coastal Erosion" / "Shoreline Change" / "South Gujarat" / "Band Ratios" / LULC}

Abstract of research paper on Earth and related environmental sciences, author of scientific article — A. Misra, R. Balaji

Abstract Shoreline change dynamics along the coastal districts of South Gujarat is studied by the application of multi-temporal remote sensing datasets. The coastal zone along the three districts of Surat, Navsari and Valsad in South Gujarat, India are reported to be facing serious environmental challenges, especially due to anthropogenic impacts. This study evaluates the decadal changes in historical shoreline changes, using satellite images of Landsat TM, ETM and OLI. The analysis of shoreline changes in these districts revealed significant variations in the form of shoreline erosion. Further, the Land-use/ land–cover(LULC) maps for each district for the year 2014 is prepared using band ratios as a pre-classification step, followed by implementation of a combination of supervised and unsupervised classification called hybrid classification. An accuracy assessment is carried out for each of the datasets and the overall accuracy ranges between 90 - 95%. The LULC study is carried out in order to identify the various classes in this region which are vulnerable to the environmental degradation. The maps prepared in this research will contribute to both the development of sustainable land use planning as well as shoreline protection measures.

Academic research paper on topic "A Study on the Shoreline Changes and LAND-use/ Land-cover along the South Gujarat Coastline"

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Procedía Engineering 116 (2015) 381 - 389

Procedía Engineering

www.elsevier.com/locate/procedia

8th International Conference on Asian and Pacific Coasts (APAC 2015)

A study on the shoreline changes and Land-use/ land-cover along

the South Gujarat coastline

Misra, Aa and Balaji, Ra*

aDepartment of Civil Engineering, IIT Bombay, Powai,Mumbai 400076 India

Abstract

Shoreline change dynamics along the coastal districts of South Gujarat is studied by the application of multi-temporal remote sensing datasets. The coastal zone along the three districts of Surat, Navsari and Valsad in South Gujarat, India are reported to be facing serious environmental challenges, especially due to anthropogenic impacts. This study evaluates the decadal changes in historical shoreline changes, using satellite images of Landsat TM, ETM and OLI. The analysis of shoreline changes in these districts revealed significant variations in the form of shoreline erosion. Further, the Land-use/ land-cover(LULC) maps for each district for the year 2014 is prepared using band ratios as a pre-classification step, followed by implementation of a combination of supervised and unsupervised classification called hybrid classification. An accuracy assessment is carried out for each of the datasets and the overall accuracy ranges between 90 - 95%. The LULC study is carried out in order to identify the various classes in this region which are vulnerable to the environmental degradation. The maps prepared in this research will contribute to both the development of sustainable land use planning as well as shoreline protection measures.

© 2015 TheAuthors.Published byElsevierLtd.Thisisan open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Peer- Review under responsibility of organizing committee , IIT Madras , and International Steering Committee of APAC 2015 Keywords: Coastal Erosion; Shoreline Change; South Gujarat; Band Ratios; LULC

* Corresponding author. Tel: (+91)22 2576 7321 (off), Fax.: (+91)22 2576 7302. E-mail address: rbalaji@iitb.ac.in

1877-7058 © 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Peer- Review under responsibility of organizing committee , IIT Madras , and International Steering Committee of APAC 2015 doi: 10.1016/j.proeng.2015.08.311

1. Introduction

The shoreline or coastline is the interface between the land and water which gets altered due to the various coastal processes that govern it such as, wave characteristics, near-shore circulation, sediment characteristics and beach forms etc. Shoreline change is a result of a process called littoral transport, which is responsible for moving eroded material in the coasts by means of waves and currents in the near shore zone. Apart from the natural processes, human induced factors such as dams or reservoirs, dredging, mining, and water extraction etc (Coastal Engineering Manual, 2002) can also be responsible for erosion or accretion. The shoreline has a tendency to changes it configuration in an attempt to reach a state of equilibrium (Pandian et al., 2004) in terms of its sediment budget which can be observed over a period of time. In the context of coastal vulnerability, accreting coastlines are considered less vulnerable, as they result in the addition of land areas by moving towards the ocean. On the other hand, eroding coastlines are considered highly vulnerable because of the resultant loss of natural as well as man-made resources associated with it. Thus, healthy beaches and shorelines are considered essential to the quality of life along the coast, and also provide buffers for storms and critical habitats for many species of plants and animals. Further, monitoring changes in the shoreline enables to identify the nature and processes that cause these changes in a particular area, assess the anthropogenic impacts and accordingly suggest management measures.

The delineation of shoreline is a pertinent exercise from the point of view of coastal zone management, watershed definition, and flood prediction. Traditional ground surveying techniques although are, relatively more accurate, often prove to be time consuming and almost impossible for a large coastal belt (Cracknell, 1999). Remotely sensed data on the other hand, can provide valuable information by virtue of their spatial and temporal scales with reasonable accuracy. This can be analyzed in a geographic information system (GIS) environment by measuring differences in past and present shoreline locations.

Several studies have been carried out to study the shoreline change and related subjects using geo-informatics as a tool. Muttitanon and Tripathi (2005) used Landsat 5 TM data in order to find out land use/land cover changes in coasts of Ban Don Bay, Thailand. Siddiqui and Maajid (2004) evaluated a multi-temporal principal component analysis (PCA) on Landsat Multispectral Scanner (MSS) and TM data to evaluate coastal changes between 1973 and 1998 in Pakistan. Ghanavati et al., (2008) used Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) data in order to monitor geomorphologic changes of Hendijan River Delta, southwestern Iran. In the Indian Context, various researchers have carried out shoreline change studies using remote sensing data. Mukhopadhyay et al., (2011) analyzed the coastal erosion and associated shoreline change in relation to sea surface height anomaly in the Chandipur coast in Balasore district of Orissa using multi temporal satellite imagery during the period 1990 to 2010. Kumar and Jayappa (2009) studied the accretion and erosion pattern along the Mangalore coast. Choudhary et al., (2013) conducted shoreline detection from Karwar to Gokarna, western coast of India. Gupta, (2014) carried out a study on Monitoring Shoreline Changes in the Gulf of Khambhat, India During 1966-2004 Using RESOURCESAT-1 LISS-III.

Further, in order to evaluate and predict the extent of geomorphic and ecological changes taking place, coastal zones require an enormous amount of site specific research, by virtue of the complexities associated with them even at the regional level (Manimurali and Dinesh Kumar, 2014). The existing land-use/land-cover (LULC) of a region is a cumulative output of the interaction between natural as well as anthropogenic variables and processes. Several studies have demonstrated the applicability of Remote Sensing (RS) and Geographical information system (GIS) as efficient and cost effective tools for analyzing the spatial and temporal dynamics of LULC (Hathout, 2002; Herold et al., 2003; Lambin et al., 2003; Siddiqui and Maajid, 2004; Muttitanon and Tripathi, 2005; Santhiya et al., 2010; Misra et al., 2013; Gilani et al., 2014) and other natural processes, wherein the former provides a valuable source of multi-temporal data, and the latter is useful for mapping and assessing the associated patterns. Thus, these tools provide a unique opportunity to develop information sources and support decision making activities in a plethora of coastal zone applications.

With this perspective, the current study aims to fulfill two main objectives, firstly to study the shoreline changes along the districts of South Gujarat using GIS as a tool to demarcate the eroding zones along this coastline. Previous literature available (Gupta, 2014; Manek and Balaji, 2014; Mahapatra et al., 2013; INCOIS, 2009) for this region report that shorelines adjoining these districts are particularly infamous for being erodible in nature, due to

both natural as well as anthropogenic reasons. Secondly, the LULC classes in this region for the year 2014 are quantified by using a combination of pre-classification (band ratio) and post classification (hybrid classification) techniques. This is mainly done to identify the prevailing LULC classes in this area and to understand the vulnerability of this region to changes. The overall objective of this study is to produce shoreline change and LULC maps that can be used efficiently by coastal managers to devise an effective coastal zone management plan for this region.

2. Study Area

The Gulf of Cambay, also called the gulf Khambat is a trumpet shaped gulf in the Arabian Sea that is situated between the Saurashtra peninsula and mainland Gujarat. Located approximately between latitude 20 30 and 22 20, 71 45 and 72 53 E, it covers an extent of about 3120km2. The GoC is about 70km wide and 130 Km long (Vora et. al., 1980) with a mid-depth of 30 m. Many rivers drain into the gulf, including the Sabarmati, Mahi, Narmada, Tapti and Shetrunji and is characterized by a number of estuaries, islands, mudflats, cliffs and mangroves. The gulf is dominated by strong tidal currents (semi-diurnal types with high tidal range) which are responsible for most of the depositional and erosional features of the gulf.

Fig. 1. Study Area

The study area (Fig.1) includes the three coastal districts of Surat, Navsari and Valsad, located in Southern Gujarat along the Gulf of Khambat. The district of Surat with a total population of 6,079,231 (Chandramauli, 2011) covers an area of 7657 sq. km and is bordered by the districts of Bharuch and Narmada in the North, Navsari and Dangs in the South and the Gulf of Khambat in the West. The town of Hazira is located in this district, which is an important transshipment port and is popularly known as the 'industrial hub' of India due to the presence of major industrial facilities. The district of Navsari covers an area of 2211 sq.km with a population of 1329672 and is bordered by the districts of Surat in the North and Dangs in the East. The district of Valsad is surrounded by the

district of Navsari in the North, Dang in the East, and Maharashtra in the South. The population of Valsad is 1705678 persons for an area of 3034 sq.km (Chandramauli, 2011).

3. Data and Methodology

3.1 Shoreline Change Analysis

The LandSat archive data for different years was downloaded from the website-http://earthexplorer.usgs.gov/.The important factors considered for finalizing the satellite images were cloud cover, similar tide conditions, similar season data, uniform projection factors, etc. The satellite data further underwent radiometric correction and data scaling to enable maximum visual interpretation. Landsat TM (19 July 1990, TE-3.33m); Landsat ETM (11 January 2001, TE- 2.98m) and Landsat OLI_TRS (12 April 2014, TE- 3.15m) datasets with UTM (Universal Transverse of Mercator) zone 43 North projection system were used for this study region.

3.1.1 Digitization of Shoreline

The shoreline features were identified using the tonal differences between the land and the sea. A band ratio technique was applied to differentiate the land and water pixels. Further vectorization technique was applied to get the shoreline features in Arc-GIS environment. To further refine the results, visual interpretation was carried out for editing the shoreline features to conform to the High Tide Line (HTL).

3.1.2 Study of Shoreline Change

The Digital Shoreline Analysis System (DSAS) is a freely available software application that works within the Environmental Systems Research Institute (ESRI) Geographic Information System (ArcGIS) software. The digitized shoreline for the years 1990, 2001 and 2014 in the vector format (. shp) are used as the input to the Digital Shoreline Analysis System (DSAS) to calculate the rate of shoreline change. The analysis also requires transect information and hence, transects (in the form of Shape file) are laid at every 500m interval along the shoreline. The DSAS tool basically estimates the Net Shoreline Movement (NSM) and End Point Rate (EPR) which are used to derive the output maps of this study. The NSM calculates the distance between the oldest and the youngest shoreline for each transect and the EPR is obtained by dividing the NSM, by the number of years elapsed between the two shoreline positions. The linear extents with negative NSM or EPR values indicate erosion whereas those with positive values indicate accretion.

3.2 Land-use/land-cover Mapping

In this study, the various LULC classes for each district are extracted from the 2014 Landsat imagery by using band ratio as the image enhancement technique. For this study, different band ratios were made for the study area by using ENVI 4.5 software. Band ratio using bands 3,4,5,7 were used to derive layers of ratios 3/4, 4/3 and 5/7 which were subsequently used to derive color composite combinations to discriminate different LULC features. The final color composite is created using 5/7 in red, 4/3 in green and 3/2 in blue which efficiently distinguishes the various features of the heterogeneous landscape of the study region. Further, the transformed images are used as image interpretation aids to classify the images of 2014. For this area, a methodology combining both supervised and unsupervised classification called hybrid classification is adopted. This approach encompasses three main steps (1) an initial spectral clustering, (2) assignment of clusters to user-defined classes and (3) maximum likelihood (or similar decision rule) classification of the entire image (Misra et al. 2013). Here, firstly we have applied unsupervised classification to the images by using the ISODATA clustering algorithm. In the second step, signatures of classes which overlap or get mixed with other classes are collected and assigned signature file, a result of the supervised approach. Finally, all signatures either are appended together to classify (as a supervised classification step) the complete and full extent of the originals image using maximum likelihood algorithm.

Accuracy assessment is then performed by a collection of 256 points from Google Earth Pro, Ground truth data and ancillary data and the overall accuracy as well as the Kappa coefficient is reported in Table 1.

Table 1. Overall classification accuracy and Kappa coefficient for all datasets

Study Region Year of Dataset Overall Accuracy of Classification Kappa Coefficient

Surat Landsat OLI 2014 92.54% 0.92

Navsari Landsat OLI 2014 94.56% 0.94

Valsad Landsat OLI 2014 91.82% 0.91

4.1 Shoreline Change

The shoreline change was estimated for the districts of Surat, Navsari and Valsad using the DSAS tool embedded in ArcGIS 10.1. The extents of the shoreline accreting or eroding for the periods 1990- 2001, 2001-2014 and 1990-2014 are shown in Fig.2. Of the entire length of 117km, about 65% of the shoreline is observed to be eroding over the period of 24 years. Onjal, Bhat, Danti and Umbergaon as well as the extents from Umbhrat to Vansi and Fansa to Maroli shows considerable erosional activity. Strong tidal currents are responsible for the accretion observed along the North Hazira Port. The shoreline changes from 1991 to 2001 show extreme rate of erosion especially along Umbhrat which has a negative NSM of 234m.

Fig.2. Shoreline changes from (a) 1990-2001 (b) 2001- 2014 (c) 1990-2014

From 2001- 2014 accretion with an average EPR of 0.65m/yr is witnessed. Overall, from 1990-2014, the shoreline analysis of this coastline (117km), reveals an eroding trend with an average EPR of -0.54m/yr and average NSM of -12.4m. The maximum accretion during this period is seen Umarsadi to Udwada where an erosion of 256.28m is seem from Umbhrat to Vansi. The cumulative action of waves and tides are responsible for the erosion/accretion trends observed along this coastline. Moreover, coastal protection is difficult as the coastal belt along GOC is mainly composed of clay sand or silt. As stated before, anthropogenic impacts are immense in these regions that greatly impact the coastal processes. A large number of sea walls, groynes, breakwaters and jetties alter the shoreline by disturbing the sediment dynamics of the region (Gupta 2014; Mahapatra et al. 2014). Thus, in totality the erosional activity of this region is caused by the combining effect of tides, waves and sediment transport.

The study highlights the advantage of using GIS tools for shoreline studies. The DSAS methodology used here provides very good qualitative estimates to understand the dynamics in a given area. The major drawback however is that the tool considers only the initial and final years for the study. Also, it takes into account a transect based analysis wherein certain important characteristics of the shoreline could be lost in places where there are no transects available. Nevertheless, the method is important from the perspective of environmental monitoring and hence can be used extensively for preliminary studies and understanding.

4.2 Mapping of land use land cover for Surat, Valsad and Navsari

The study domain of each district was extracted using a buffer zone of 20, 18, 35 km for Surat, Navsari and Valsad respectively. The domain sizes were chosen so that they cover the immediate coastal zone and urban development in the vicinity. The predominant classes for this region are water, intertidal mudflats, salt marshes, mangroves, sandy features, agricultural land, urban built up, aquaculture, vegetation and barren. Fig.3and Table.2 shows the LULC maps for each district and their corresponding percentage distribution.

Legend LULC Classes

mi Water | Vegetation 1 Urban Built-up

] Mangroves

| intertidal Mudflats*' Tidafflats Barren Ufl damply Spaces I Aquaculture

Short lino' Sandy tea tut 5 Agriculture*1 Fallow Land

Sail Marshes.' Salt Pan*

—T~r 10

"I—I 20 Km s

Legend

LULC ClâSSëS ] Marshy vegetation/ Mangroves

■ Water IHI intertidal Mudflats/TidaMats

1 Urban Built Up |_ Barren

Sandy Features Aquaculture

Salt Marshes Agricultural Land

Legend

LULC Classes I Marshy Vegetation/Mangroves

| Water |Intertidal Mudllals/ttdalllals | Vegetation Barren

| Urban Built Up H Aquaculture Sandy Features Agricultural Land Salt Marshes

I i rnrrrri 0 5 10 20 Kms

Fig.3. 2014 LULC maps for Surat, Navsari and Valsad

Table.2. Percentage (%) coverage of each LULC class

LULC Class_Percentage(%) coverage of each LULC class

Surat Navsari Valsad

Water 38.91 50.91 65.81

Intertidal Mudflats/Tidalflats 3.33 3.45 0.91

Salt Marshes/Salt Pans 3.02 8.14 0.86

Marshy vegetation/ Mangroves 0.84 0.89 0.14

Shoreline/ Sandy Features 0.08 0.46 0.17

Agricultural/ Fallow Land 37.87 26.25 23.02

Urban Built Up 7.56 2.23 2.47

Aquaculture 1.42 1.27 0.13

Barren 1.69 6.39 6.17

Vegetation 5.29 0.00 0.34

For Surat, agricultural land covers the maximum spatial extent of almost 74425.59 hectares. A total of 141370.7 hectares is covered by Intertidal mudflats/tidal flats, Salt marshes and mangroves. Aquaculture constitutes of about 2791.53 hectares. Only 148.86 hectares is covered by the sandy-features class. Heavy urbanization can be seen as the Urban built up class covers almost 14862.51hectares of the region under consideration. In case of Navsari, 910.3hectares is covered by mangroves. A considerable spatial coverage of Salt marshes can be seen of about 8292.1hectares. For the area studied for Navsari most of the region is covered with agricultural land. In case of Valsad it can be seen approx.23% of the area is covered by agricultural land class. The mangrove spatial extent is relatively less, about 428.76m. The shoreline as represented by the Sandy features class is well represented for this district covering and area of about 655.29 hectares. The Urban Built Up class covers an area of 9520.38 hectares. Thus, it is evident that the three districts encompass some extremely fragile ecosystems like mangroves, mudflats, salt marshes etc. According, to coastal vulnerability studies reported in literature (Manimurali et al., 2013), such features are generally considered to highly vulnerable to coastal hazards. Hence, these regions require immense protection from degradation.

5. Conclusion

This study is an effort to understand the dynamics of shoreline changes occurring along the South Gujarat coast and evaluating the cause of the same. The End Point Rate of -0.54m/yr highlights the eroding trend of the shoreline which is of immense concern especially from the sustainability point. For the South Gujarat districts, it can be seen that the urbanization leads to immense pressure on the nearby coastal resources. Further, through the LULC maps its can be witnessed that these district cover fragile ecosystems of mudflats, salt marshes etc and hence future environmental degradation along these coast could disrupt the normal functioning of the environment. Therefore, it is suggested that improved tools of remote sensing (high resolution data) and GIS accompanied with field survey and numerical modeling can enable better understanding of these regions so that a sound strategy can be devised for the conservation and restorations of these natural systems. Finally, the present research pertaining to the study of the shoreline changes and mapping of LULC will enable the decision makers to identify the susceptible zones and find better solutions to the existing coast problems in these locations.

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