a study on the land use pattern change along the coastal...

INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 1, No 4, 2011

© Copyright 2010 All rights reserved Integrated Publishing services

Research article ISSN 0976 – 4380

A study on the Land use pattern change along the coastal region of Nagapattinam, Tamil Nadu

Arunachalam S1, Maharani K2, Chidambaram.S2, Prasanna.M.V2, Manivel M3 Thivya C4

1- Scientist E, NDC, National Remote Sensing Centre, Hyderabad 2- Department of Earth Sciences, Annamalai University, Chidambaram

3- Professor and Head, Department of Geology, Bharathidasan University, Tiruchirapalli. 4- Department of Applied Geology, School of Engineering and Science

[email protected]

ABSTRACT

The ground water in a particular coastal aquifer is to be described, evaluated and explained primarily by application of principles of aquatic chemistry to hydrogeological systems to understand the migration of solutes using field data. The origin of salinity is not only due to seawater intrusion but there are other possible sources. There is a lot of human pressure on the coast line due to urbanization, industrialisation, aquacultural and agricultural activities. Apart from these factors, salinity increase in the coastal aquifers, sea level changes, changes in coastal configurations due to mining activities and impact of the natural calamities like floods, tsunami and earth quake also add to the magnitude of the problem. This study aims to bring out the Land use/land cover pattern of study area were studied using IRS P6 LISS III data and correlate with the water level, Electrical conductivity of ground water and rainfall variations. Two data products were selected during May 2000 and august 2009 to study the land use pattern variations. The land use/land cover patterns were visually interpreted and digitized using ERDAS IMAGINE, MapInfo and Arc GIS software. The study reveals that the agricultural area has increased by 172sq.km and settlements by 28.5 sq. km there is a decrease in water bodies and others (includes waste land).

Keywords: Groundwater, Coastal aquifer, Remote sensing, Landuse/ Landcover, Spatial Distribution

1. Introduction Coastal areas are highly dynamic and undergoing rapid change. In view of this fact, it is essential to review decisions made and developments undertaken pertaining to the coast from time to time. Land use refers to man’s activities and the varied uses which are carried on over land and land cover refers to natural vegetation, water bodies, rock/soil, artificial cover and others noticed on the land (NRSA, 1989).The knowledge of landuse / land cover changes is very important in understanding natural resources, their utilization, conservation and Management (Nagamani and Ramachandran, et.al 2003) uses. Some studies examined the effect of land use/land cover change on land surface temperature.

(Achard, 2002; Anderson, 1976; Andersson, 2009) which was found to be positively correlated with impervious surface. Some studies estimated the relationship between the land surface

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Research article ISSN 0976 – 4380 temperature and vegetation abundance (Anon, 1992. Landuse is a product of interactions between a society's cultural background, and its physical needs on the one hand, and the natural potential of land on their (Achard, 2002). In order to improve the economic condition of the area without further deteriorating the bio environment, every bit of the available land has to be used in the most rational way. This requires the present and the past landuse/ land cover data of the area (Asselman, 1995) has emerged as a central issue within the scientific community concerned with global environmental change (Balak Ram & Kolarkar, 1993).To improve the economic condition of the area without further deteriorating the bio environment, every bit of the available land has to be used in the most rational way. Land-use, land-use change and forestry (LULUCF) contribute to ongoing anthropogenic climate change (Bannerman, 1998; Bannerman, 1998; Bloomfield & Pearson, 2000; Boers, 1996; Bondeau, 2007; CEC, 1995) and have consequently received increasing research attention over the last decade (Chaurasia, 1996; Dale, 1997; De Moor, 2008; De Wit, 1999; DeFries, 1997; Dengiz, Orhan, 2009; Duhamel, 1995; ECE-UN, 1989). LULUCF can also make a significant contribution to the reduction of GHGs, by increasing the carbon storage of terrestrial ecosystems (carbon sequestration), by conserving existing carbon stocks (e.g. by avoiding deforestation or land degradation), and by providing renewable energy (biomass production) Eiten, 1968; Elena Cantarello, 2011; Fosberg, 1961). Such LULUCFactivities are expected to provide a significant and cost effective way by which atmospheric CO2 concentration can be reduced, at least in the short- to medium-term (Furukawa, 2005; Hauenstein, 2005; Houghton, 1994; Houghton, 1999).Temporal changes in land cover have become possible in less time, at lower cost and with better accuracy through remote sensing technology (Houghton, 2003).

Detection of long term changes in land cover may reveal an idea for the shift in local or regional climatic conditions and analyzing the basis of terrestrial global monitoring (Jansen, 1998).Changes in land use and land cover are among the major drivers of terrestrial ecosystem transformations (Jing Jiang & GuangjinTian, 2010; Kachhwala, 1985; Kuechler, 1988) as they have an impact on the global carbon cycle(Kumar,1994) the climate(Lal,2003; Lal,2001) the biodiversity(Lambin,1997)and the landscape ecology(Le HegaratMascle, 2006; Li, Y., Liao, 2003; Lorenzo Benini, 2010).More than world’s half population lives within 60km of the coast and would rise to almost three quarters by 2020(Louisa 2002). Remote sensing satellite data provides a synoptic view of the coastal zones. The modern scientific technologies of remote sensing and digital image processing are extremely useful in periodic assessment of the coastal LULC changes and analyze them to formulate better management. Hence the coastal areas are fragile and they are more persistent to land use changes. An attempt has been made in this study to bring out the land use decadal changes and correlate it with Water level, Electrical conductivity of groundwater and rainfall pattern during the period of study.

1.1 Study area The study area covers an area of about 2978.7Sq.Km and is composed of coastal alluvium holding good amount of water. It falls between the 10o10’N to 11o20’N and 79o15’E to 79o50’E (fig.1). The subsurface water is being tapped by the industries along the coastal regions, apart from the industrial threat. Paddy cultivation is also practiced in many parts of this region extracting sufficient amount of water from the aquifer, the addition of the fertilizers has also

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Research article ISSN 0976 – 4380 affected the medium. More over this region has salt pans, back waters and several distributary Channels. The study area has few major rivers like Kollidam and Cauvery in the north, Virasolanar, Uppanar in the central part and Arasalar, TirumalairajanAr, Vettar, Kedurai Ar, Pandavai Ar, Vedaranyam canal and Harichandra Nadi in the southern part of the district42. Decrease in others and increase of muddy and swamps paddy cultivation and increase and slow regeneration of mangroves are caused considerable damage. Mangroves are being cut down for fuel and buried material. Creeks have been blocked there by resulting in the sweetening of the water upstream killing of the mangroves43on the east coast, salt marsh vegetation occurs as either being interspersed within mangroves (pichavaram area), on the high tidal mudflats (Muthupet).

Figure 1: Location map of the study area

1.2 Geology and Geomorphology of The Study Area In the study area formations are fluvial origin. It consists of sandy coastal fluvio-marine formation. The formations include mixture of sand, silt, clay, and natural levee complexes (fig.2). The entire block comes under sedimentary terrain and the formation includes Alluvium, sandy clay, and has Muthupet and Vedaranyam swamps in the southeast. The area forms part of Cauvery delta with gentle slope towards Bay of Bengal (Meyer, 1992).The chief of geomorphology feature of the study area is alluvial plain deposit, alluvium of the Cauvery River and is distributaries, and narrow fluvio-marine deltaic plain deposits (East coast formation). The fluvial deposits comprise flood plain, point bar, channel bar and palaeo channels with admixtures

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Research article ISSN 0976 – 4380 of sand, silt, clay and gravel. These coastal lowlands of Tamilnadu has an elevation of 1- 20 m from MSL (except Cuddalore sandstone uplands which rise upto 80 m) exhibit wide ranging features to marine origin (fig.3). The shore zone part of the area consists of long sandy barrier beaches and beach ridges interspersed with low beach cliff.

Figure 2: Geological map of the study area

The rainfall is influence of both southwest and northeast monsoon. A sufficient amount of the rainfall occurs as very intensive storms resulting mainly from cyclones generated in the Bay of Bengal especially during northeast monsoon. The study area receives rainfall almost throughout the year. Rainfall data analysed shows the normal annual rainfall of the area is 1230 mm. The rainfall pattern in the area shows interesting features. Annual rainfall, which is 1500 mm at Vedaranyam, the southeast corner of the area, rapidly decreases to about 1100 mm towards west of the study area.

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Figure 3: Geomorphology map of the study area

2. Materials and Methods In present study 17 ground water sampling stations were considered and the secondary data was collected for these regions during 2000 and sampling was conducted in these observation wells during 2009. The water level data for both the periods were collected from central groundwater board and the rainfall data from Indian Meteorological division, Chennai. The satellite data set was obtained from NRSA, IRS P6 LISS III image for year 2000 and 2009were used, and Survey of India Taluk map drawn on 1:50,000 scales were used for the analysis.

Traditional classification systems deals with land cover and/or land-use(Mueller-Dombois, 1974; Muller,2007; Murcia,1995; Nabuurs,2007; Navalgund, 2007; Nobi, 2009; Osumba,2009; Pacala,2004; Panigrahy, 2010; Petit,2002; Prabaharan, 2010; Ramkumar, 2010) are limited in their capacity of storage of classes and often do not contain the whole variety of occurring land

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Research article ISSN 0976 – 4380 covers or land-uses. Some describe (semi) natural vegetation in great detail while accommodating cultivated areas in a single class or vice versa. More important, they are based upon the approach of class names and class descriptions that do not consistently use a set of criteria to make class distinctions (Ramsar, 1971). Furthermore, the criteria used are often not inherent characteristics but describe the environmental setting of the land cover and land-use, respectively. The distinction between land cover and land-use is not always appreciated or adhered to in the above mentioned classifications (Reid, 2000). In the present classification the land use was classified into settlements, crop, forest land, others, water body, muddy area and salt pan.The present study involves three main steps. In the first step, the spatial distribution based on the groundwater level, Electrical conductivity and rainfall data were plotted. Second step involves the classification of satellite data for 2000 and 2009 using landuse types. Analysis of satellite data includes registration, classification to identify the landuse /land cover using supervised classification comparison (Fig.10 & 11). Finally the land use types were correlated with the spatial plots of EC, WL and rainfall. 3. Results and discussion The rainfall distribution was studied in seven different locations (Nagapattinam, thirupoondi, thalagnayiru, thrangampadi, sirkazhi, mayiladuthurai and vedaranyam) during 2000 and 6 locations during 2009 (Nagapattinam, thirupoondi, thalagnayiru, thrangampadi, sirkazhi and Mayiladuthurai). The total rainfall obtained from these observation stations during 2000 account for about 11345.1mm, and that during 2009 accounts for about 8635.9mm. Hence it is understood that the region had experienced heavier rainfall during 2000 than 2009. The rainfall was dominant in both the monsoons at all the stations during 2000, but during 2009 only NE monsoon was predominant. Some of the researchers have identified that the decrease in vegetation cover has resulted in decrease of rainfall (Reis, 2006; Richardson, 1994).

Figure 4: Data representing rainfall pattern for the year 2000

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Figure 4: Data representing rainfall pattern for the year 2009

Figure 5: Spatial distribution of groundwater level for the year 2000

The spatial distribution of groundwater level for 2000 shows that the groundwater is deeper in the central part of the study area and is shallow in the northern and southern part of the study area, similar trend was noted in the groundwater contours of 2009 but the water table was

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Research article ISSN 0976 – 4380 comparatively shallower than that of 2000.The onset of the agricultural activities during the South west monsoon of 2009.Removal of land cover exposes soil to erosion (wind and water), which when combined with soil disturbances by livestock, speed the erosive processes leading to reduction in infiltration and increased runoff (Rogan, 2002). The spatial distribution of groundwater level for 2000 shows that the groundwater is deeper in the central part of the study area and is shallow in the northern and southern part of the study area, similar trend was noted in the groundwater contours of 2009 but the water table was comparatively shallower than that of 2000.The onset of the agricultural activities during the South west monsoon of 2009.Removal of land cover exposes soil to erosion (wind and water), which when combined with soil disturbances by livestock, speed the erosive processes leading to reduction in infiltration and increased runoff (Rogan, 2002).

Figure 6: Spatial distribution of groundwater level for the year 2009

The spatial distribution of the Electrical conductivity of groundwater during 2000 shows that the EC value ranges from <260 to >2870 micro mho/cm. and the highest value is occupied in the central part of the study area, which is indicated by the deeper water table. The electrical conductivity of the 2009 ground water ranges from <360 to >3660 micro mhos/cm. the spatial pattern of EC during 2009 is similar to that of the 2000 but the area occupied by the higher EC has increased in the central part of the region and its also to be not that the average Conductivity of the groundwater in the region has also increased. The delivery of sediments eroded from agricultural areas is also responsible for the supply of nutrients, pesticides, and heavy metal contaminants to river channels (Rokityanskiy, 2007; Roy, 2002; Running, 2008) which can have an impact on the water quality of rivers and coastal areas. Sediment delivery also impacts on

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Research article ISSN 0976 – 4380 channel and floodplain morphology (Sala, 2000; Sarma, 2009) the ecological functioning of floodplains and sediment deposition rates in reservoirs and ponds (Schlamadinger, 2007). Comparison of this landuse with the decadal change in the groundwater conditions helps to identify the threat and its region of salinity impact (Mueller-Dombois, 1974).

Figure 7: Spatial distribution of Electrical conductivity level for the year 2000

Figure 8: Spatial distribution of Electrical conductivity level for the year 2009

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Research article ISSN 0976 – 4380 The Modern scientific technologies of remote sensing and digital image processing are extremely useful in periodic assessment of the coastal landuse and land cover changes and analyze them to formulate better management. Land cover mapping serves as a basic inventory of land resources for all levels of government, environmental agencies and private industry throughout the world (Schuck, 2003). The classification was done under the following heads (table1) as crop, forest, saltpan, mud, settlements, water bodies (dry & wet) and others (figures 10 and 11).

Table 1: Identified landuse / landcover in satellite image

Area in sq.kms Area in % Land use 2000 2009 2000 2009 Crop 747.8 + 919.57 25.10 + 30.87 Others 1712.81 - 1544.16 57.50 - 51.84 Settlement 64.23 + 92.86 2.16 + 3.12 Forest 18.55 -18.52 0.62 - 0.62 Water body 9.42 - 5.62 0.32 - 0.19 River dry 28.83 +31.21 0.97 + 1.05 River wet 117.15 -98.64 3.93 - 3.31 Salt 24.27 + 28.8 0.81 + 0.97 Mud 255.64 -239.32 8.58 - 8.03

Figure 9: Landuse map of the study area for the year 2000

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Figure 10: Landuse map of the study area for the year 2009

The plain terrain (others) is converted into crop land and Built-up area (settlement) is increase compared with year 2000 to 2009. The study area has an Agricultural land (crop) of 747.8(25.10%) sq.kms during 2000 and 919.57 (30.87%) sq.kms during 2009.Settlement covers 64.23sq.kms (2.16%) during the year 2009and 92.86 (3.12%) Sq.Km during 2000.Water body covers an area of about 9.42 Sq.Km (0.32%) in year 2000 and 5.62(0.19%) Sq.Km during 2009 because the area is dry condition. Mud area and others have decreased (Table2).

3.1 Crop land There is an increase of cropland during August 2009, from 747 sq.km to 919 sq.km. This is because the imagery of 2000 was a scene captured during May 2000 (i.e. summer) and the imagery captured for 2009 was during august (i.e.) after the onset of the SW monsoon, when the agricultural activities gets initiated. Others include the grass lands and dry lands they show higher area occupied during May 2000 and becomes lesser during august 2009 this is mainly due to the increase of agricultural activities along the river channels after the onset of monsoon. It is observed that when the surrounding landscape patterns change, the environmental conditions (e.g. microclimate) produced along these edges (the boundaries between surrounding forests and the cool temperate forest) may be modified and it influences the interior regions(Shailesh nayak & Anjali Bahuguna., 2001; Smith,2008).In Settlement there is a drastic increase in population in a decade and hence it is reflected in the settlement area from 2000 to 2009. There is just 1%

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Research article ISSN 0976 – 4380 increase in the area occupied by the settlements. There is no much variation in the area covered by mud, salt pan, Forest and water body. Forest cover change detection has been done, through visual interpretation of satellite data (Squeo, 2001; Stresemann, 2008; Thompson, 1996; Trochain, 1961; UNEP/FAO, 1993).

Table 2: Land use/ Land cover classification

Land use/ Land cover

Descriptions

Settlement Urban land, rural residential land and other build-up land, such as industrial and transportation land

Crop Paddy fields. Forest land Forest land, bush forest,

open forest and other forestlands, such as slash, nursery land

Others Dry lands, high coverage grasslands, mangroves, moderate coverage grasslands and low coverage grasslands

Water body Rivers, lakes, reservoirs Muddy area Bare land, barren land

and other unused land such as tundra

Saltpan saline land, swampy and marsh land

The river wet region shows a significant decrease during 2009 as it may be due to the increase in the agricultural land. It is also noted that the both the monsoon were prevalent dominantly during 2000 and only NE monsoon was more prominent during 2009. A slight decrease in mud may be due to the increase in the salt marsh regions in the southern part of the study area at the swampy mangroves. This may be due to siltation’s along the in the swampy mangroves. Swamp forest is a particular type of wetland, classified by the Ramsar Convention as “freshwater, tree-dominated wetlands” in category (Xf)( UNESCO, 1973). These ecosystems maintain a rich diversity of species and also contribute to regulate river flows, thus helping to slow erosion processes and control floods (Van Minnen, 2008; Verstraeten, 1999).Wetland areas have been recognised internationally for their highbiological and environmental value, and as providers of ecosystem services. Swamp forests have often been threatened by the destruction of their habitat by clearing for agricultural land, grazing and firewood extraction. These, leave remnant patches following

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Research article ISSN 0976 – 4380 human land conversion activities due to the fact that swamp forests occupy land of lower agricultural value (Vijith, 2007). It must be considered that wetlands are sensitive to interventions in their river basins and surrounding landscape, so that any alteration in the territory may affect both physical-biological interactions with the wetland and the quality and flow of water (Watson, 2000; White, 2000; Wickham, 2000).

The decrease in wetlands with shrubs/grass is due to rapid urbanization and industrialization along the coast line. These anthropogenic activities had limited the entery of high tides and backwaters on to the main land, which are main source of wetlands along Vedaranniyam coast. Similarly, decrease in woody vegetation (Mangroves and Coconut trees) is also due to the above anthropogenic activities. Fallow lands have been increased because most of the wetlands have been converted to fallow lands due to non availability of tidal water/backwater and moisture (Yule, 2010).

The comparison of the land use changes during the study period and the electrical conductivity of groundwater show that the conductivity has increased during the recent years and the crops land in this region has reduced due to the saline nature of the ground water and the settlement has increased in this regions. The major variation on the land use pattern is noted along the central part of the study area where the groundwater conductivity has increased. Hence it is clear that the groundwater quality plays a major role in the land use pattern change in the study area. Detection and characterization of change in measurements or strategic deployment of more expensive resources for monitoring or management (Zomer, 2008). 4. Conclusion The present study shows that satellite remote sensing based land cover mapping is very effective for coastal land use/land cover Changes. The study has been conducted with the high resolution satellite data IRS P6 LISS III data the study area falling in the coastal region of the Tamilnadu shows minor changes in the land use pattern for the periods from 2000 to 2009. There is an increase in the settlement and swampy region and there is a decrease in the others. The major variation on the land use pattern is noted along the central part of the study area where the groundwater conductivity has increased. Hence it’s clear that the groundwater quality plays a major role in the land use pattern change in the study area. Hence, this is an essential tool for future planning and management of coastal regions by the virtue of their fragile ecosystem it has been observed that important coastal land use types like Agricultural (crop), settlement increased. Acknowledgements The authors to thank for the funding agency for BRNS Project and NRSC for the providing satellite data to carry out this work.

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