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INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES

Volume 5, No 4, 2015

© Copyright by the authors - Licensee IPA- Under Creative Commons license 3.0

Research article ISSN 0976 – 4380

Submitted on January 2015 published on May 2015 579

Land use and land cover dynamic analysis using satellite Remote Sensing

and GIS techniques -A case study of Girudhumal river sub basin,

Tamilnadu, India Dhanasekarapandian M1, Selvan P1, Chandran S2, Chandramohan K3

1-Research Scholar, Department of Civil Engineering, Thiagarajar College of

Engineering, Madurai -625015, Tamilnadu, India.

2-Associate Professor, Department of Civil Engineering, Thiagarajar College of

Engineering, Madurai -625015, Tamilnadu, India.

3- Research Scholar, School of Earth and Atmospheric Sciences, Madurai kamaraj

University, Madurai-625021, Tamilnadu, India.

[email protected]

ABSTRACT

The study aims to affect of land use and land cover changes is the quantitative method to

expound the impact of land use and land cover in Girudhumal river sub basin, Tamilnadu,

India over twenty years period(1990 to 2010). The study has been done through Remote

Sensing approach using Survey of India(1982) toposheet and Land sat imageries of May

1990, June 2000 and May 2010 MSS. Land use changes have been detected by image

processing method in ERDAS imagine 8.5 and Arc GIS 9.3. Thirteen land use classes have

been identified and Ground truth observation was also performed to check the accuracy of the

classification. The present study has brought to light that the agricultural land that occupied

about 29.86% of basin area in 1990 and was decreased to 18.13% of basin area in 2010 and

settlement increased 9.8% of total area of basin in 2010. This paper highlights the land

use/land cover types, the change over the years and the causes for the change. The

importance of remote sensing and GIS technique in mapping and change detection was also

highlighted.

Keywords: Digital image Processing, GIS, Remote sensing, Change detection, Land use and

Land Cover.

1. Introduction

Land use refers to man’s activities and varied uses which are carried on overland and land

cover refers to natural vegetation, water bodies, rock/soil artificial cover and other noticed on

land. Land cover, defined as the assemblage of biotic and abiotic components on the earth

surface is one of the most crucial properties of the earth system. Land cover is that which

covers the surface of the earth and land use describes how the land cover is modified. Land

cover includes water, snow, grassland, forest and bare soil. Land use includes agricultural

land, build up land, recreation area, wildlife management area etc.,(Natural Resources Census,

2006, Maryna,2007, Prakasam,2010). Land use and Land Cover (LU/LC) mapping and

detection of change using remote sensing and GIS technique is of paramount importance to

planners, geographers, environmentalist and policy makers, in fact to everybody who cares

sustainable development (Abbas et al.,2010). Urban growth, land use and land cover change

Land use and land cover dynamic analysis using satellite Remote Sensing and GIS techniques -A case study

of Girudhumal river sub basin, Tamilnadu, India

Dhanasekarapandian M et al.,

International Journal of Geomatics and Geosciences

Volume 5 Issue 4, 2015 580

study is very useful for urban planners. Land use/Land Cover change is scalar

dynamic.( Bhagat Rimal, 2011) Land use Land Cover pattern of a region is an outcome of

natural and socio-economic factors and their utilization by man in time and space. Land is

becoming a scalar resource due to immense agricultural and demographic usage. (Chetan and

Tukaram,2011). LU/LC change, as on the main driving forces of global environmental

changes, is central to the sustainable development debate. It affects a wide range of

environmental and landscape attribute including the quality of water, land and air resources,

ecosystems process and function and climate system. (Lambin et al.,2000 and Sylla et

al.,2012).

The ability to achieve significant improvement of land use and land cover classification

accuracies through interpretation and image processing technique indicating the potential for

continued progress in classification of remotely sensed data and the need for the facilitates

more detailed, precise land use and land cover classes. Although intended for crop

assessment, the resulting “leaf on” imagerely will facilitate delineation of vegetative from

impervious cover for Lu/Lc purposes (Lillesand and Ralph,1994). The in-depth knowledge

gained through the categorization and case studies of land use change will become handy in

developing regional and global Lu/Lc changes models. Land use studies and analysis has

become a prerequisite for proposing for development an activity is an area. The growing

demands on land have resulted in a crisis of land mismanagement. Land resources are the

foundation for the socio-economic development at the national, regional and local levels in

many of the developing countries such as India. Land degradation results mainly due to

population pressure which leads to intense land use without proper management practices.

The impact of changing land uses relies on the prevailing surface and subsurface hydrologic

process governed particularly by the temporal and outputs and land use conditions (Nagarajan

and Poongothai, 2011). Land is a fundamental factor of production and through much of

course of human history, it has been tightly coupled with economic growth. Often improper

land use is causing various forms of environmental degradation.

During the past millennium, human have taken an increasingly large role in the modification

of the global environment with increasingly numbers and developing technologies, man has

emerged as the major, most powerful and in India, land cover today is altered primarily by

direct human usage of land (Tiwari and Khanduri,2011).The drastic growth of urban areas

has resulted in sharp land use and land cover changes.(Suribabu et al.,2012), The land use

change due to urban expansion and the loss of agriculture land, changes in river regimes, the

affects of shifting cultivation, the spread of erosion desertification and so, on. This therefore

requires not only the identification of features, but also the comparison of subsequent data in

order to recognize when valid change has taken place (Vemu and Pinnamaneni,2010). The

remote sensing techniques are used to measures the land cover from which land use can be

inferred particularly with ancillary data or priority knowledge (Nobi et al.,2009). Geographic

Information Systems and Remote Sensing techniques provide effective tools for analyzing

the land use dynamics of the region as well as for monitoring, mapping and management of

natural resources. Many studies have demonstrated the effectiveness of using remotely sensed

data as a powerful tool to detect land use change for critical environmental areas, vegetation

dynamics and urban expansion breakthrough in the method of acquiring information on land

resources, agriculture, forestry, ocean resources and other studies (Yasodharan et al., 2011).






2. Study area

The Gundar Basin has been divided into 9 sub basins and Girudhumal is one of the sub

basins. The Girudhumal river originates from Thuvariman tank about 7 km west of Madurai

city and it runs for a distance of 15 km in Madurai South taluk, 20 km in Manamadurai taluk,

30 km in Thiruchuli taluk and about 23 km in Kamuthi taluk. It brings down the surplus

water of Madakulam big tank, drainage from the city through Avaniyapuram and

Chinthamani supply channel running in the middle of the city and other Vaigai fed tanks on

its way before joining river Gundar near Keelavalasai village. Total length of river is about

83 km. Girudhumal River also gets supply from Vaigai River through a flood carrier off

taking above Viraganur regulator. The study area extending over as much as 566.851Sq. km,

and it is location extended from 9°50′N, 78°00′E to78.20°E 9.20’N. It has an average

elevation of 100 meters above mean sea level. The climate is dry and hot, with rains during

October to December. Temperatures during summer reach a maximum of 40 and a minimum

of 26.3 degrees Celsius. Winter temperatures range between 29.6 and 18 degrees Celsius.

Girudhumal sub basin has to cover northwest parts of Madurai, northeast part of, Sivagangai,

southwest part of Viruthunagar and southeast and end of the sub basin in Ramanathapuram

District as shown figure 1.

Figure 1: Image showing the location of study area

2.1 Objective

The basic objectives of the study involved to produce a land use and land cover map for

Girudhumal river sub basin at three different part of time in order to detect the changes that

have taken place,

1. To Creation of land use/land cover map

2. To analyze the dynamic nature, location and magnitude of changes within the land use

classes for the period 1990 to2010.

3. Methodology

The study has made use of various primary and secondary data. These includes survey of

India (SOI) topographic sheets (year-1982, 58k/1, 58k/6, 58k/11) of 1:25,000 scale and Land

sat images LISS III (for the year 1990, 2000) and IRS P6 data(for the year 2010) as shown in

Table 1 and figure 2. These IRS data were visually and digitally interpreted by using ERDAS

8.5 for classify the image and Arc GIS 9.3.software for processing, analysis and integration






of spatial data to reach the objective of the study. Adequate field checks were made before

finalization of the thematic map. The main goal of the study is to extract land use /land cover

changes using multi-temporal satellite data.

Figure 2: Land Sat-LISS III map of Girudhumal River Sub basin, 1990 ,-(A), Land Sat-LISS

III map of Girudhumal River Sub basin, 2000-(B), IRS P6 map of Girudhumal River Sub

basin, 2010-( C)

Table1: Spatial Data Sources

Data Month of

observation

Spatial

Resolution/Scale

Land Sat-LISS III May,1990 30 m

Land Sat-LISS III June,2000 30 m

IRS P6 May,2010 30 m

SOI 1982, 58k/1,

58k/6, 58k/11 1:25,000

4. Results and discussion

4.1 Digital image processing

The study depends on the use of ERDAS imagine interpretation of Landsat imageries. Field

survey was performed throughout the study area using Ground Truth Verification (GTV).

This survey was performed in order to obtain accurate location point data for each LULC

class included in the classification scheme as well as for the creation of training sites and for

signature generation. In order to obtain the required information from satellite image data,

The standard image processing techniques such as, image extraction, rectification, restoration,

and classification were applied in the current study and the interpretation were made

systematically the land use characters extracted is given in figure 3.






Figure 3: Land use land cover map of Girudhumal River Sub basin, 1990 ,-(A), Land use

land cover map of Girudhumal River Sub basin, 2000-(B), Land use land cover map of

Girudhumal River Sub basin, 2010-( C)

There is no suspicion that human activities have profoundly changed land cover in the study

area during the last half centuries. Land is one of the most important natural resources. All

agricultural, animal and forestry productions depend on the productivity of the land. The

entire eco-system of the land, which comprises of soil, water and plant, meets the community

demand for food, energy and other needs of livelihood. The land-use and land cover pattern

of a region is an outcome of natural and socio-economic factors and their utilization by man

in time and space. Viewing the Earth from space is now crucial to the understanding of the

influence of man’s activities on his natural resource base over time. In situations of rapid and

often undocumented and unrecorded land use change, observations of the earth from space

provide objective information of human activities and utilization of the landscape (Bhagat

Rimal,2011). Most urban land cover/land use change studies utilized Landsat data due to the

uniqueness of the dataset as the only long term digital archive with medium spatial resolution

(Limin et al.,2003). Land cover mapping serves as a basic inventory of land resources for all

levels of government, environmental agencies and private industry throughout the world

(Nobi et al.,2009). The findings of the present investigation are presented in table.2. The land

use land covers identified by this study were of thirteen categories and they were assessed

and found to be as follows.

Table 2: Girudhumal River Sub Basin, Area under land use land cover

Land use covered area by Hectares

Class Name 1990 % 2000 % 2010 %

Agricultural land 21523 29.86 17632 24.46 13068 18.13

Dense scrub 8759 12.15 16232 22.52 12064 16.74

Open scrub 11902 16.51 6784 9.41 19657 27.27






Fallow land 10856 15.06 11943 16.57 6299 8.74

Water spread

area 1397 1.94 2026 2.81 3046 4.23

Villages 1441 2 1560 2.16 1848 2.56

Sub urban 357 0.5 560 0.78 665 0.92

Barren rocky

exposer 285 0.4 283 0.36 281 0.39

River 1338 1.86 1255 1.74 1425 1.98

Dry tank 10860 15.07 10180 14.12 9987 13.86

Major roads 1983 2.75 2159 3 2399 3.33

Railway line 61 0.08 67 0.09 68 0.09

Streams 1313 1.82 1395 1.94 1267 1.76

Total 72075 100 72075 100 72075 100

4.1.1 Agricultural land

This encompasses both cultivated and irrigated lands. Agricultural lands are represented by

sandal color and constituted 21523 Ha, with percentage of about 29.86 of the total area in

1990. In 2000, the area found to be covered by agricultural land areas became 17632 Ha and

about 24.86% of the total area. In 2010, further it decreased to 13068 Ha and about 18.13%.

Because of human interaction, the agricultural lands have transformed to forest plantation,

settlement and roads.

4.1.2 Dense scrub

This covers forest plantation in the study area represents by dark green color and constituted

8759 Ha, with percentage of about 12.15% of the total area in 1990. In 2000, the area found

to be covered by dense scrub became 16232 Ha, about 22.52% of the total area. While in

2010 the land occupied for dense scrub decreased to 12064 Ha, about 16.74% of the total area.

4.1.3 Open scrub

The open scrub in the study area represents by light green color. In Girudhumal river sub

basin areas facing acute water shortage for agricultural in the sub basin areas, many parts of

the areas having prosopis Juliflora, it looks like open scrub. It constituted 11902 Ha, with

percentage of about 16.51% of the total area in 1990. In 2000, it found to be 6784 Ha, about

9.41% of the total area and while in 2010, the land occupied for open scrub increased to

19657 Ha, about 27.27% of the total area.

4.1.4 Fallow land

The fallow land represents in the study area by light yellow color. Due to failure of rainfall

most of the agricultural land became fallow land in this sub basin area and it covered 10856

Ha, about 15.06% of the total area in 1990. In 2000, it increased to 11943 Ha, likewise the






percentage increased to about 16.57% of the total area. In 2010, it decreased to 6299 Ha,

about 8.74% of the total area.

4.1.5 Water bodies

It includes lakes and ponds. It represented by dark blue in color on the map, and it covers

1397 Ha 1990 with an area percentage of 1.94 % of the total area. In, 2000, it increased to

2026 Ha, about 2.81 % of the total area and in 2010, further it increased to 3046 Ha, likewise

the percentage increased to about 4.23 % of the total study area. This fluctuation may be due

to the rain fall in the month of May and June in the consecutive year in the study area.

4.1.5 Villages

Includes educational, health and dwelling places in the village area. This areas are represents

the pink color in the map and constituted 14.41 Ha, with percentage of 2% of the total area in

1990. In 2000, 1560 Ha, about 2.16 % of the total area and in 2010, further it increased to

1848 Ha, about 2.56 % of the total area.

4.1.6 Sub urban

Madurai, Thirupparankundram is a famous tourist places in South India and it gives more job

opportunities, educational, health and socio-economic facilities like, games/sport viewing

centres. It represents dark brown color in the map. It covers 357 Ha of the land area and

constituting 0.5% in 1990. While in 2000, the land used for sub urban uses increased to 560

Ha, about 0.78 % of the total area. In 2010, the land for sub urban further increased to 665 Ha,

about 0.92 % of the total study area.

4.1.7 Barren rocky exposure, river, dry tanks and railway line

Represents light green, light blue, violet and black in colors in the map. These values remain

constant and slight variance due to developmental and climatic conditions.

4.1.8 Major roads

Includes main road, footpath, un-tarred roads on the map. It represents dark brown in color on

the map. It covered 1983 Ha in 1990 with 2.75 % of total area and in 2000, it covered 2159

Ha with 3.00% of the total area, further it increased to 2399 Ha in 2010, with 3.33% of the

total area.

4.1.9 Streams

It is represented by light blue in color on the map. It covers 1313Ha in 1990 with an area

percentage of 1.82% of the total area. In 2000, it increased to about 1395 Ha, likewise the

percentage increased to about 1.94 % of the total area. Similarly in 2010, it decreased to 1267

Ha, with an area percentage of 1.76 % of the total area. These variances were because of

uneven settlement in the stream area. Figure 4 represents the distribution of land use land

cover distribution during the three periods in the study area.






Figure 4: Distribution of land use land cover during the periods of study area.

4.2 Change detection analysis

Change detection is an important process in monitoring and mapping natural resources and

urban development because it provides quantitative analysis of the spatial distribution of the

population of interest.( Muthusamy et al., 2010). The most common approach to change

detection is bi-temporal change analysis, the direct comparison of pairs of images or

characterization (Coppin et al.,2004). In many remote sensing change section studies, land

use land cover change often are used interchangeably.(Green, 1994). In the figures below

(Figure.5) the land use areas represent the features increased and decreased areas in 1990-

2010. This is because in the Change Detection Analysis, Dry tank and fallow land areas have

high increased values than any other land cover/ land-use category because of the vegetation

like dense scrub and agriculture feature degreased compare with 1990 to 2000. Dry tanks and

fallow land were again highly increased and agriculture land degreased compare with years

of 2000 to 2010 and 1990 to 2010 other features were gradually changed it could be clearly

explained in table 3 and 4.

In remote sensing, many researchers utilize digital image change detection techniques to

monitor LULC. Change detection is the process of identifying differences in land cover

among multiple-temporal remotely sensed data of an area of interest (Chamaporn,2004).

Although different sprawl types were identified and defined there has been an inadequacy

with respect to developing mathematical relationships to define those (Tamilenthi and

Baskaran,2011). Accordingly, Table 3 show that the features increased and decreased area

covered with high area of 15431 Ha and 8745 Ha respectively in 1990 to 2010, compare with

other two decades of 1990 to 2000 and 2000 to 2010, land use and land cover changes is

more possible in 1990 to 2010 because of temporal variation is more than other decades. As

many researchers indicated in Nigeria, several factors have been modifying the original form

of land cover. These include human activities such as agricultural colonization. Land use land

cover mapping and detection of changes may not provide the ultimate explanation for all

problems related to land use land cover changes but it serves as a base to understand the

patterns and possible causes and consequences of land use land cover changes in the area

(Abbas et al., 2010). The pattern of the changes between 1990 and 2010 are presented in

Tables 3and 4. Within the period, more land was brought under fallow land /agricultural land,

at the same time settlement (sub urban and village) expanded at the expense of other land

cover types. Water bodies were irregular variations of the study area because of the rainfall

could not being in regular.






Figure 5: Land Use Land Cover Changes (1990-2000)-(A), Land Use Land Cover Changes

(1990-2010)-(B) , Land Use Land Cover Changes (2000-2010)-(C)

Table 3: Land use Land cover Changed area by Hectares (1990-2010)

Landuse/Landcover Changed area by Hectares

Class name 1990 - 2000 2000 - 2010 1990 - 2010

Increased Decreased Increased Decreased Increased Decreased

Agricultural

land Non 2458 Non 3256 Non 8288

Dense scrub 26 2020 31 3202 29 2712

Open scrub 124 304 217 877 7606 1164

Fallow land 1063 404 3240 863 2149 307

Water spread

area 305 602 450 659 1131 1169

Villages 46 Non 309 Non 738 Non

Sub urban 9 Non 72 Non 290 Non






Barren rocky

exposés Non Non 3 8 3 9

River 39 Non 94 10 219 4

Try tank 1866 Non 3121 5 2300 21

Major roads 37 Non 442 6 583 103

Railway line 2 Non 19 Non 24 Non

Streems 84 Non 491 Non 359 Non

Total 3601 5788 8489 13918 15431 8745

Table 4: Magnitude of land use land cover change 1990-2010

Classes/year 1990 2010 Change Area

Ha % Ha % Ha %

Agricultural Land 21523 29.86 13068 18.13 -8455 -11.13

Dense Scrub 8759 12.15 12064 16.74 3305 4.49

Open Srub 11902 16.51 19657 27.27 7755 10.76

Fallow Land 10856 15.06 6299 8.74 -4557 -6.32

Water spread area 1397 1.94 3046 4.23 1649 2.29

Villages 1441 2 1848 2.56 407 0.56

Sub Urban 357 0.5 665 0.92 308 0.42

Barren Rocky

Exposure

285 0.4 281 0.39 -4 -0.01

River 1338 1.86 1425 1.98 87 0.12

Dry tank 10860 15.07 9987 13.86 -873 -1.2

Major Roads 1983 2.75 2399 3.33 416 0.58

Railway Line 61 0.08 68 0.09 7 0.01

Streams 1313 1.82 1267 1.76 -46 -0.06

5. Conclusion

Land cover is a critical element in change studies, affecting many aspects of the

environmental systems. Accurate and updated land cover change information is necessary for

understanding main factors causes and environmental consequences of such changes.

Understanding the land use and land cover and evaluating changes upon the environment

involve procedures of modeling and simulation, which require robust methodology and

techniques. While remote sensing and GIS technique has the capability of monitoring such

changes, extracting the change information from satellite data relies on effective and accurate

change detection technique. During the period of analysis, the generous land use and land

cover changes has been observed in Girudhumal sub basin. The present study has brought to

light that the agricultural land that occupied about 29.86% of basin area in 1990 and it was

decreased to 18.13% of basin area in 2010 and settlement (villages and sub urban) increased

to 9.8% of total area. The settlement changes of 9.8 % land would be occupied on the

agricultural land. However agriculture and fallow land had decreased by 17.45%. The






agricultural land affected by the irregular of irrigation work in study area so that the

agricultural land gradually modified in to settlement activities. Thus spatial and temporal

analysis techniques were very useful in generating scientifically based statistical spatial data

for understanding the land ecosystem dynamics. This change is a result of poor irrigation

facility and could not be regular monitoring of land activities. The satellite images of study

area acquired during 1990 to 2010 periods have offered a rich source of information about

land use and land cover change detecting and assessing. Hence, the information obtained

from change detection of land use and land cover aids is used to implement and monitor of

any development schemes to meet the increasing demands of human needs for better land

management.

Acknowledgement

Authors highly thankful to Laboratory facilities provided by Thiagarajar college of

Engineering for completion of this work, The Director, National Remote Sensing Agency,

Hyderabad, and the PWD Officials, Madurai, Tamilnadu, India for their kind help in

providing reference data and valuable suggestions.

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