land use /land cover classification and change detection ...€¦ · and change detection analysis...

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International Journal of Civil Engineering and Technology (IJCIET)

Volume 7, Issue 3, May–June 2016, pp. 329–336, Article ID: IJCIET_07_03_032

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ISSN Print: 0976-6308 and ISSN Online: 0976-6316

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LAND USE /LAND COVER

CLASSIFICATION AND CHANGE

DETECTION USING GEOGRAPHICAL

INFORMATION SYSTEM: A CASE STUDY

S.D. Vikhe

Research Scholar, Govt. Engineering College,

Aurangabad, Maharashtra, India

Dr. K.A. Patil

Associate Professor of Civil Engineering,

Govt. Engineering College, Aurangabad, Maharashtra, India

ABSTRACT

Land use and land cover change has become a central component in

current strategies for managing natural resources and monitoring

environmental changes. Geographical information system and image

processing techniques used for the analysis of land use/land cover and change

detection of Sukhana Basin of Aurangabad District, Maharashtra state. The

tools used ArcGIS10.1 and ERDAS IMAGINE9.1, landsat images of 1996,

2003and 2014. From land use / land cover change detection it is found that

during 1996-2014, water bodies cover have loss of 4 Sq. Km. Barren land

have 146 Sq.Km. loss and forest area with 96 Sq.Km. loss. It is found that

urbanization area has gain of 51 Sq.Km. and agricultural land cover also

have gain of 195 Sq.Km.

Key words: GIS, Land Use, Land Cover, Supervised Classification, Change

Detection.

Cite this Article: S.D. Vikhe and. K.A. Patil, Land Use /Land Cover

Classification and Change Detection Using Geographical Information System:

A Case Study. International Journal of Civil Engineering and Technology,

7(3), 2016, pp.329–336.

http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=7&IType=3

S.D. Vikhe and K.A. Patil


1. INTRODUCTION

Land cover refers to the physical characteristics of Earth's surface, captured in the

distribution of vegetation, water, soil and other physical features. Land use refers to

the way in which land has been used by humans and their habitats. Although land use

is generally inferred based on the cover, yet both the terms land use and land cover

being closely related are interchangeable.

Land use/cover and its dynamics are important factors that affect ecosystem

conditions and functions. In the past 40 years, land use cover change dynamics has

been considerably changing the biogeochemical cycling leading to changes in surface

atmospheric energy exchanges, carbon and water cycling, soil quality, biodiversity,

ability of biological systems to support human needs and, ultimately the climate at all

scales (Amare Sewnet 2016).

Jayakumar S. and D.I. Arockiasamy (2003), attempted to map land use / land cover

and change detection analysis in Kolli hill, part of Eastern Ghats of Tamil Nadu, using

remote sensing and GIS. About 467 ha increase has been observed in single crop

category and about 434 ha decrease has been observed in land with or without scrub

category. Majority of the area (13639 ha) is under scrubland. Lesser changes could be

noticed in double crop, plantation and barren/rocky categories.

Sathees kumar P and Nisha Radhakrishnan (2010), have studied Remote Sensing

And Gis In Land Use Planning. The different land use categories and their spatial and

temporal variability in Tiruchirappalli city has been studied over a period of eight

years (1998-2006), from the analysis of topographical map, IRS 1D and IRS P6 for

the year 1973, 1998, 2002 and 2006 using Arc GIS and ERDAS Imagine 9.1. Based

on the results of classified images, the agricultural land coverage area was reduced

7.8% from the year 1998 to 2006, while the area under settlement increased 14.7%

from the year 1998 to 2006.

He-Bing Hu, et al. (2012), have analysed Land Use Change Characteristics Based On

Remote Sensing and Gis In The Jiuxiang River Watershed. Based on remote sensing

and GIS technology, the remote sensing images from 2003 to 2009 were used to the

basic data sources, to analyze the characteristics of land-use change in Jiuxiang River

watershed. Results showed that watershed land use structure were changed greatly

from 2003 to 2009; the proportion of arable land decreased from 34.86% to 19.52%,

whereas other types of land use increased. The area of construction land increased

most rapidly, from 17.80% to 25.80%.

Jeffry Swingly Frans Sumarauw and Koichiro Ohgushi (2012) have analysed On

Curve Number, Land Use and Land Cover Changes in the Jobaru River Basin, Japan.

Arc GIS tool to delineate river basin and sub-basin, and HEC-GeoHMS tool for

estimating the CN. The result shows that from 1948 to 2005 the CN of the Jobaru

River basin decreased from 53.29 to 52.03, which indicates that the land use changes

in Jobaru River basin makes the land capability for reducing flood becomes better

during this period.

Singh R B and Dilip Kumar (2012) have used Remote sensing and GIS for land

use/cover mapping and integrated land management: case from the middle Ganga

plain. Alternative land use systems and the integration of livestock enterprises with

the agricultural system have been suggested for land resources management.

Kotoky, P. M. et al. (2012), have studied, Changes in Land use and Land cover along

the Dhansiri River Channel, Assam by A Remote Sensing and GIS Approach.

Information on land use/ land cover change is a critical input for natural resource

Land Use /Land Cover Classification and Change Detection Using Geographical Information

System: A Case Study


management policy decisions. Remote sensing data under GIS domain were utilized

to evaluate the changes in land-use/land-cover (LU/LC) spanning a period of thirty

three years during 1975 to 2008 along the Dhansiri River channel, Assam, India.

Seven different types of LU/LC were categorized and out of them cropland was

evident as the most important land use /land cover practices followed by dense mixed

jungle in 1975 and the settlement in 2008.

Mani.N. and Rama Krishnan. (2013), have estimated the LU/LC changes in Tamil

Nadu State using remote sensed data and Geographic Information System (GIS) with

field verification for the objective of the study. Landsat 1973,1990 and IRS-P6 images

(2008) were used. The LU/LC of the study area were classified into 7 types as

followed respectively built-up, agricultural, forest, grazing land, aste land, wetland

and water bodies which adopting NRSC LU/LC classification. The research

concludes that the area under built-up and agriculture has increased while the area

extent of forest, grazing land, wasteland, wetland and water bodies has decreased in

the study area.

Wagner, P. D. S. Kumar, and K. Schneider (2013) have studied an assessment of

land use change impacts on the water resources of the Mula and Mutha Rivers

catchment upstream of Pune, India. Analyzed past land use changes between 1989

and 2009 and their impacts on the water balance in the Mula and Mutha Rivers

catchment upstream of Pune. Land use changes were identified from three Rivers

catchment multitemporal land use classifications for the cropping years 1989/1990,

2000/2001, and 2009/2010. The hydrologic model SWAT (Soil and Water

Assessment Tool) was used to assess impacts on runoff and evapotranspiration.

Praveen Kumar et al. (2013), have analyzed Land Use/Land Cover Changes Using

Remote Sensing Data and GIS at an Urban Area, Tirupati, India Land use/land cover

(LU/LC) changes were determined from 1976 to 2003 by using Geographical

Information Systems and remote sensing technology. These studies were employed by

using the Survey of India topographic map 57O/6 and the remote sensing data of LISS

III and PAN of IRS ID of 2003.The study area was classified into eight categories on

the basis of field study, geographical conditions, and remote sensing data. The

comparison of LU/LC in 1976 and 2003 derived from toposheet and satellite imagery

interpretation indicates that there is a significant increase in built-up area, open forest,

plantation, and other lands. It is also noted that substantial amount of agriculture land,

water spread area, and dense forest area vanished during the period of study which

may be due to rapid urbanization of the study area.

As maximum villages in the study area are selected for water conservation works

under Jalyukt Shiwar Yojana by state government of Maharashtra .To preserve the

natural resources and to understand the causes and its effect of over exploitation of

soil and water resources the land use and land cover analysis study was carried out.

2. METHODOLOGY

2.1. Study Area

Geographical information system and image processing techniques used for the

analysis of land use/land cover and change detection of Sukhana Basin of Aurangabad

District, Maharashtra state which is divided into 35 sub watersheds of Aurangabad

District, Maharashtra state are evaluated. Study area is located between 75.33°, 75.76°

E longitudes, and 19.66°, 19.98° N latitudes. Details of study area is given in table 1



Table 1 Summary of study area

Name of

watershed No of watershed

Area of watershed

In Sq Km

No .of villages

covered

AU/GP-10 09 351.75 52

AU/GP-17’ 06 172.25 32

AU/GP-17 02 66.00 09

Total---03 17 590.00 93

2.2. Data used

Details of Image information are shown in following table.

Table 2 Image information

Sr. No. Type Year Bands Path Row Resolution (m)

1. LT5 March-1996 5 146 46 30 x 30

2. LT 7 March-2003 7 146 46 30 x 30

3 LC 8 March-2014 8 146 46 30 x 30

Survey of India (SOI) Toposheets at 1:50,000 scales were used for the preparation

of the base maps and for remote sensing data interpretation.

2.3. Land Use and Land Cover

Different land use/land cover classes like urbanization Barren land, Settlement, Forest

land, Water body, Agricultural land. etc. which is shown in table 3. were then

identified using visual interpretation keys such as colour, tone, texture, pattern, size

and shape. Description of these land cover classes are shown in Table 3. In the

supervised classification technique, three images with different years are

independently classified. Av supervised classification method was carried out using 8

to 10 training sites were made by demarcating a polygon or an area of interest for all

the five land use and land cover types. Then for each class average signature was

developed. Data is also for accuracy assessment. Maximum Likelihood Algorithm

was employed to detect the land cover types in ERDAS Imagine9.1.

After ground truthing , Accuracy assessment was carried out. To determine the

accuracy of classification, a sample of pixels is selected on the classified image and




their class identity is compared with the ground reference data. The detailed

methodology is illustrated in flowchart in Figure 1

Table 3 Description of land use/land covers units.

S .No Land cover class Description

1 Urbanization Urban/Rural Settlement

2 Agricultural Land Crop Land, Fallow/Harvested Land, Plantation

3 Forest Dense Forest, Degraded / Open forest, Forest plantation

4 Water bodies River / Stream, Lake / Reservoir /Tank / canal

Tank with scrub / Plantation

5 Barren land Salt affected Land, Gullied / Ravinous, Land with / without

scrub, Sandy Area, Barren Rocky / Stony waste / Sheet Rock

Flowchart adopted for analysis of land use/ Land cover in Basin.

Figure 1 Methodology Flowchart

Define classes on Land

use/Land cover Data acquisition

GPS field survey and

toposheet information

Image processing registration

and study area clipping

Creation of signature for

each land class

Supervised

Classification

Post-classification

Processing

Accuracy assessment

Land use & land cover

change detection

Analyzing Land use & land

Cover changes using multitemporal

images



3. RESULTS AND DISCUSSION

Output after processing in shown figure.2, the water bodies extent and its proportion

for the year 1996, 2003 & 2004 in basin was 6 Sq.Km. which is 0.9% of the total area

in 1996. Its cover was decreased to 0.40% in year 2003 and 0.30% for the year 2014.

Land under forest cover in the year 1996, 2003 and 2014 in basin was 206 Sq.Km.

amounting 30.80% of the total area in 1996. It was found decreased to 29.00% and

16.40% in the year 2003 and 2014 respectively.

Urbanization extent and its proportion for the year 1996 was 13 Sq.Km.

accounting 1.9% of total area. Its cover was increased by 4.2% and 9.6% in the year

2003 and 2014 respectively. Urbanization found in increasing trend in the basin.

Agricultural land in basin was 68.00 Sq.Km. which is 10.20% of the total area in

1996. Agriculture land cover extent and its proportion decreased to 8.1% in 2003,

whereas it is increased 39.30% in 2014, it shows five times increased than which is in

1996.

Barren land in the basin was 376 Sq.Km. which is approximately half the total

area of the basin. In 2003 it decreased to 58.30% and 34.40% in 2014. This shows that

area Barren land area decreases from 1996 to 2014 decrease in barren land have

compensated by increase in urbanization and Agricultural land. Details are presented

in table 4 and also in graph.

Table 4 Land use/cover of Sukhana Basin from 1996-2014.

Land class 1996 2003 2014 1996 - 2014

Area

(sq.km) %

Area

(sqkm) %

Area

(sqkm) %

Total loss or gain

area (Sq. Km)

Water body 6 0.9 3 0.4 2 0.3 -4

Urbanization 13 1.9 28 4.2 64 9.6 51

Barren 376 56.2 390 58.3 230 34.4 -146

Agricultural 68 10.2 54 8.1 263 39.3 195

Forest 206 30.8 194 29 110 16.4 -96

Total 669 100 669 100 669 100




Figure 2 Land use/land cover maps of Sukhana Basin in 1996, 2003 and 2014.

The assessment of the accuracy of classification found by ratio of the mapped area

that has been correctly classified in comparison to reference data such as toposheet ,

reconnaissance survey ground truth to the total area mapped. The accuracy found to

be 85 %.

4. CONCLUSION

From study of land use / land cover change detection ,it is found that during 1996-

2014, water bodies cover have loss of 4 Sq. Km. Barren land have 146 Sq.Km. loss

and forest area with 96 Sq.Km. loss. It is found that urbanization area has gain of 51

Sq.Km. and agricultural land cover also have gain of 195 Sq.Km. Land use / land

cover must be improved with reference to resource management and application of

conservation treatment in the basin.

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