MAPPING OF LAND USE AND LAND COVER CHANGES IN … · The analysis shows that the major changes in present area of chennai due to the rapid population and industrial growth. Land use

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MAPPING OF LAND USE AND LAND COVER CHANGES IN

CHENNAI USING GIS AND REMOTE SENSING

Dr. S. Vidhya Lakshmi1, S.Thomas2

1Associate Professor, 2Final year, B.E., Civil Engineering

Department of Civil Engineering, Saveetha School of Engineering

Saveetha Institute of Medical and Technical Science, Chennai - 602 105, India

[email protected], [email protected]

ABSTRACT:

Chennai district are very valuable in view of human beings and land use /land cover

changes due to urban areas and industrial. The chennai city is located in latitude 13⁰4'2.7804"N

and longitude 80 ⁰14'15.4212"E southern part of India and fifth populated metro Politian city in

India. A computer program for capturing and show the data collection related to positions on

surface of earth. The land use map and download the shape file of chennai. Initially download

Tamilnadu shape file and clipped chennai district shape file from it using QGIS 2.6.0. The

satellite image data for year 2000, 2005, 2010, 2015, 2017. It data was collected in Earth

explorer.usgs.gov. Then the satellite image was layer staking and gap filling using ENVI 4.5.

after that using SUPPORT VECTOR MACHINE to classified the five years of satellite image.

The land use classification system we are using in the present study is the more generalized

level. Result shows the process in five year of buildup area, water bodies, agricultural area, sand,

dense vegetation in change detection.

KEYWORDS: land use /land cover, remote sensing, geographical information system,

ENVI 4.5, Earth explorer, QGIS2.6.0, change detection, support vector machine.

International Journal of Pure and Applied MathematicsVolume 119 No. 17 2018, 11-21ISSN: 1314-3395 (on-line version)url: http://www.acadpubl.eu/hub/Special Issue http://www.acadpubl.eu/hub/

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1. INTRODUCTION:

The Land cover of any metropolitan

city is changing a space as a result of speedy

increment and urban areas. Dense vegetation

,agricultural land, forest land ,water body sq

uare measure being become settled house, th

e demand of infrastructure and trade for the

extraordinarily growing population. Remote

sensing could be a vital technique for learnin

g land cover changes. The resources are inte

nsive pressure, changes square measure one

in every of the very important aspects of wo

rld changes (Li Xiubin, 1995). Land use cha

nge is that the modification with in the limit

and purpose and usage of the land, that may

not primarily entirely the change in theland

cover but additionally changes in intensity a

nd management (Verburg, et al,2000). Data

relating to land use change is important to

update land cover maps and for effective

management and springing up with of the pr

ocess resources for property development( A

lphan2003; MuttitanonandTrpathy2005). Th

e city is found in southern a section of Asian

nation and it is the fourth largest, fifth most

haunted metropolitan city. Town zone pollu

tion is increased as a result of the increasing

population and industrial activities etc. This

study is based on the detection of change ins

ide the urban land cover around urban center

mistreatment temporal data of Landsat numb

er sixty nine 5 (Thematic mapper 5). Image

of 2000 and 2017 are thought of to investiga

te the change during this house Detection of

change by pattern footage of twenty years is

extraordinarily plenteous effective as a resul

t of it's protrusive the variation inside the lan

dscape. Analysis of the landscape change fro

m 2000 to 2017 can supply very important d

ata on higher cognitive operation processes r

esult of it'll indicate the increase in reduction

in vegetated space, with necessary impact on

the environment. The land use/land cover c

hanges of town environmental conditions we

re assessed pattern temporal satellite data pat

tern GIS techniques.

2. STUDY AREA:

The chennai city is located in latitude

13⁰4'2.7804"N and longitude 80 ⁰14'15.4212

"E southern part of India and fifth populated

metro Politian city in India. On the alternativ

e hand, they confluence in salt water bodies,

mangroves placed at the fringes of Ennore.T

his mangroves setting is attracting giant rang

e of life creatures and therefore. Chennai dis

trict are very valuable in view of human

beings and land use /land cover changes. It's

the second largest beach of the world. the

realm is delimited by canal flows from north

ern to southern direction and stream flows to

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wards the east direction. Major soil varieties

area unit too drained sandy soils, in North

coast clayey soils area unit found close Pulic

atLake.

Fig.1 Study area of chennai map

3. DATABASE:

In the present study to satellite imageries ar

downloaded from the USGS website (http:/

/glovis.usgs.gov)over the seventeen years o

f your time amount (2000 to 2017). Each th

e information sets square measure projected

in UTM projection with zone range forty

four and WGS eighty four information.Sate

llite image of 2000 has been thought about

because the base knowledge and image of 2

017 is coregistered using 1st order polynom

ial model thereupon base knowledge with z

ero.5 component (RMSE) accuracy.There s

quare measure many remotesensing knowle

dge sources obtainable for the extraction of

impermeable surfaces together with sets of

lower medium or higherresolution knowled

ge.Medium abstraction resolution pictures s

quare measure provided by Landsat satellit

es.Higher abstraction resolution satellite pic

tures can give a lot of correct results, these

ought to purchase. The satellite pictures fr

om four totally different years employed in

the study were procured from the free USG

S information (USGS,2014) so as to observ

e changes in land cover that occurred over t

ime. therefore to observe the changes withi

n the growth of the studied urban center spa

ce within the amount from 2000 to 2017.lan

d use/land cover amendment from 2000 to

2017 by means that of remote sensing, Lan

dsat Thematic clerk (TM) pictures (2000,20

05,2010,2015,2017)and 5 SPOT4 High Res

olution Visible Infrared (HRVIR) pictures

square measure collected for the case study.

All the abstraction knowledge layers were r

egistered to constant Universal cross wise

geographer (UTM) system and sampled to

constant component resolution of 30 m.


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Fig.2 Landsat ETM+(2000) satellite

image

4. METHODOLOGY

The Indian Remote Sensing Satellite inform

ation (LISS III) for the years 2000 and 2017

and Survey of India geo graphics map 66D/1

,66C/8, 66C/7 (2000) on 1:50,000 scales wer

e used for the local area network use mappin

g plus intensive ground truth verifications. T

he satellite information were geometrically c

orrected and georeferenced with Surveyof In

dia(SOI) topographical maps victimization g

round management purpose (UTM and WG

S eighty four datum). The land use map and

transfer the from file of Chennai.abinitio tra

nsfer Tamilnadu form file and clipped Chen

nai district formfile from it victimization QG

IS a pair of.6.0. The satellite image informat

ion for year 2000, 2005, 2010, 2015, 2017.

It information was collected in Earth mortal.

usgs.gov. Then the satellite image was layer

staking and gap filling victimization ENVI4.

5 after that using SUPPORT VECTOR MA

CHINE to classified the 5 years of satellite i

mage. The land use organisation we tend to

area unit victimization within the current stu

dy is that the a lot of generalized level.

Fig.3 methodology flow chart

Landsat TM 2000 Land sat TM 2017

IMAGE PRE

PROCESSING

SUPERVISED

CLASSIFICATION

CLASSIFIED IMAGE

2000

CLASSIFIED IMAGE

2017

Accuracy assessment

Land use cover map

Analysis

DATA


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4.1 LAND COVER CLASSIFICATION:

Image analysis techniques square me

asure quick evolving, It needs distinct land

surface info from satellite image classificati

on based mostly techniques (Prenzel and

Treitz, 2005). Within the present study, 30m

resolution Tm knowledge is employed for t

he estimation of land cover within the geogr

aphic region. however high resolution knowl

edge may be a lot of helpful to spot the com

plicated land cover of Old chennai.Major lan

d cover sorts square measure thought about

and following categories are chosen

1. Building

2.forest

3.dense vegetation

4.shallow water

5.deep water

6.sand

7.lake water

Satellite knowledge with sensible spectral an

d radiometric resolution is extremely abunda

nt essential for correct land use and land cov

er classification. Digital classification has re

ceived attention within the previous two dec

ades to excessive growth in computing syste

m. (Jain and Dubes (1988). Automatic classi

fication ways squaremeasure primarily supp

orted multi spectral classification techniques

(per pixel classifiers).These processes assign

a picture element to acategory when determ

ination of its applied mathematics similaritie

s, with relation to a collection of categories i

terms of reflectivity (Gong et al., 1992).Sup

port vector machine methodology of classifi

cation has been employed in this study for

classification.

Fig.4 classified image 2000



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\


5. RESULTS AND DISCUSSION:

5.1 Evaluation of land use - land

cover map

The analysis shows that the major changes

in present area of chennai due to the rapid

population and industrial growth. Land use

and land cover classified satellite image

classes in 2000 to 2017 are buildup area,

agricultural land, sand, dense vegetation,

deep water, shallow water. The

classification shows that the major changes

are the buildup areas of chennai district. It is

observed that buildup area increased from

2000-2005 in 79.06%, 2005-2010 in

62.02%,and 2010-2015in 62.55%, 2015-

2017in 74.87% and 2000-2017 in 95.33%.

Average change 75.54%. The chennai city

more populated and educational business

will be increase. So it has been observed the

buildup area increased in the chennai

district. Deep water was decreased in

the district. Deep water 49.7% in 2000 and

22.40% in 2005, 33.33% in 2010,4.68% in

2015, and 29.53% in 2017.the total

percentage 139.64% and average change

40.24%. shallow water increased in the

2000-2017 years of chennai. Shallow water

2000 in 0.69% and 2005 in 0.0%, 2010

in2.83%, 2015 in 12.37%, 2017 in 36.15%.


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Table.1 Land use and land cover analysis in 2000 to 2017

The total percentage 52.08% and

average change in 50.66% .then we are

noticed sand in 2000 in 77.19%, 2005 in

96.87%, and 2010 in 6.47% ,2015 in 0.25%

and 2017 in 59.38% total average in

240.14% and average change is 85.78%.

then observed that the agricultural land in

chennai city compared the last seventeen

years is decreased. Because population

growth and development city. so these

agricultural land (2000-2005) in 0.97%

,(2005-2010) in 8.51%, and (2010-2015) in

0.26%, (2015-2017) in 3.74%.the

agricultural land total percentage was 13.534

and average percentage is 11.59%.

Dense vegetation also decreased in the

chennai city 2000 in 57.56%, and 2005 in

50.53% .these (2000-2005) in 5 decades

comparing with 7 % decreased in

vegetation. then (2010-2015) in 17.61% and

(2015-2017) in 42.41%,(2000-2017) in

33.97%. these dense vegetation was total

percentage is 59.00% and average change

86.99%. it all observed in the lake water is

covered from the 2000 in 45.49 % and 2005

in 53.15%, 2010 in 0.0% and 2015 in

0.002%, 2017 in 42.85%.average change in

50.53%. decreased the lake water from 2000

to 2017,because most of the lake have been

covered to buildings, flats and industries.

The human being are doing like kitchen

wastage, human wastage and industrial

wastage are the reason for changes the

nature of lake water.

Land cover

type

2000-

2005

2005-

2010

2010-

2015

2015-

2017

2000-

2017

Total

Percentage

sq.km Per % sq.k

m

per % sq.k

m

per % sq.k

m

per % sq.k

m

per% average

change

Deep water 691.4

7

49.70 550.8

9

22.40

%

0.36 33.33

%

0.27 4.68

%

410.7

6

29.53

%

89.64 40.24%

Shallow

water

0.36 0.69 0 0.00

%

5.76 2.83

%

22.68 12.37

%

18.9 36.15

%

52.08 50.66%

Lake water 164.6

1

45.49 93.6 53.15

%

0.02 0.00

%

0.02 0.02

%

155.0

7

42.85

%

41.4 50.53%

Building 91.08 79.06 84.51 62.02

%

6370.

47

62.55

%

2326.

41

74.87

%

8339.

31

95.33

%

73.82 65.71%

Agricultura

l land

7.74 0.97 15.75 8.51

%

0.03 0.26

%

3.6 0.05

%

29.7 3.74

%

13.534 11.59%

Sand 6,752.

25

77.19 7.254 96.87

%

0.36 6.47

%

0.02 0.25

%

68.4 59.38

%

40.14 85.78%

Dense

vegetation

794.2

5

57.56 1211.

85

50.53

%

151.3

8

17.61

%

1114.

83

42.41

%

468.9

9

33.97

%

59.00 86.99%


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No year overall

accuracy

kappa co-

efficient

1 2000 82.91% 0.634

2 2005 86.40% 0.456

3 2010 81.92% 0.599

4 2015 88.44% 0.817

5 2017 92.53% 0.810

Table.2 Kappa statistics for individual

class for the 2000 to2017 images

6. CONCLUSIONS:

Remote sensing and GIS could be a powerfu

l tool for mapping and evaluating the landus/

land cover changes in Chennai.The present s

tudy shows that satellite remote sensing lan

d cover mapping is extremely effective.The

high resolution satellite information like LIS

SIII information and Landsat Tm are smart s

upply to produce info accurately.The Chenn

ai zone changes throughout the past sevente

en years chiefly because of the increase, busi

ness and industrial activities.The mashows t

he most important changes within the coasta

l landforms i.e.increase in buildup land,indu

stries and in alternative agricultural,forest sp

ace is decreased. The general accuracy of th

e current land cover studyis 92.53%.Chennai

space and if this trend of growth continues t

hen most of the vegetated areas ar occupied

by enginered up in close to future which can

produce a threatto setting.

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MAPPING OF LAND USE AND LAND COVER CHANGES IN … · The analysis shows that the major changes in present area of chennai due to the rapid population and industrial growth. Land use