change detection analysis in land use / land cover of pune city using remotely sensed data
DESCRIPTION
Lecture delivered in the National Conference entitled “Monitoring Degraded Lands” jointly organized by Agasti Arts, Commerce and Dadasaheb Rupwate Science College, Akole and Maharashtra Bhugolshastra Parishad Pune to be held on 4 to 6 February 2014.TRANSCRIPT
Change Detection Analysis in Land Use / Land Cover of Pune City Using
Remotely Sensed DataNitin N. Mundhe1 and Ravindra G. Jaybhaye2
1Department of Geography, S. P. College, Pune, India2 Department of Geography, University of Pune, India
National Conference on “Monitoring Degraded Lands” jointly organized by Agasti Arts, Commerce and Dadasaheb Rupwate Science College, Akole and Maharashtra Bhugolshastra Parishad Pune
Introduction:
Change detection is the process of identifying differences in the state of an object or phenomenon by observing it at different times (Singh 1989).
Land use referred to as man’s activities and the various uses which are carried on land includes agricultural land, built up land, recreation area, wildlife management area etc.
Land cover, defined as the assemblage of biotic and a biotic components on the earth’s surface is one of the most crucial properties of the earth system. Land cover is referred to as natural vegetation, water bodies, artificial cover, rock/soil and others resulting due to land transformation.
The over exploitation and mismanagement of these natural resources are exerting detrimental impact on geo-environment.
The no. of million cities and actual area under these cities are
also increasing .
This haphazardly increasing trend has been created problems likeenvironment pollution, loss of agriculture land, encroachment of hills and riverbanks and unauthorized slum development etc.
So, there is need to accurately describe land use/land cover
changes for sustainable environmental planning of Pune city using
Geospatial technology.
Need of Study:
Study Area:
Latitude Extent:
18°25’N to 18°37’N
Longitude Extent:
73°44’E to73° 57’E
Total Area:
243.84 sq.km.
Total Population:
31,15,431 (2011)
Density in person per sq. km.
12,777 (2011)
Objectives:The main objectives of the study are:
1.To analyze the land use/ land cover changes in study area over
period of time.
2.To assess the implications of the changes observed in study area
and make appropriate recommendation.
Database:
Segment : Pune City SourcesToposheets No. 47F/14/1 to 47F/14/6 F/15/NE, F/15/NW and 47F/15/SE
Survey of India, scale 1:25000
Satellite Imagery – Landsat 1(MSS), 5 (TM) and 7 (ETM+)
Global Land Cover Facility (GLCF)earthexplorer.usgs.gov web site
Demographic details from Primary Census abstracts for, 1991 , 2001 and 2011
Directorate of census operations, Census of India
All Secondary data(Demographic, Land use/ Land cover etc.)
City Development Plan (CDP)(2006-2012)
Ward map and Administrative Boundary Pune Municipal Corporation (PMC)
Methodology:
The research was carried out following steps in methodology.
Procurement of Satellite data and related attribute data.
Applied Standard Image Processing techniques to the remotely sensed data.
Applied hybrid classification approach to assess the spatial changes in land use
and land cover over the period of time
Fieldwork and survey conducted by using GPS.
Generation of base maps from toposheets and satellite images.
Flowchart of Methodology
False Colour Composite (FCC) Landsat imageries of Pune City: (a) January1973, (b) December 1992, (c) November 2001, (d) February 2011.
Source: Global Land Cover Facility (GLCF) http://glcf.umiacs.umd.edu
Four different LU/LC maps have been produced from the classified image deriving from the classification of Landsat images.
Using the Hybrid Image Classification Approach, seven classes have been defined: i. Built-upii. Agricultural landiii. Scrub landiv. Fallow land v. Vegetationvi. Rivers and Lakesvii.Canalo In addition to the Google Images , Topographical maps and GPS survey data
have been used as a reference material for the classification procedures. To evaluate the user’s and the producer’s accuracy, a confusion matrix was applied to the classified images.
Accuracy assessment of remote sensing analysis
Classified ImagesTotal number of pixels
Number of correct pixels
OverallAccuracy in %
Overall Kappa Statistics
Landsat MSS (1973)
50 43 86.00 0.7580
Landsat TM (1992)
50 42 84.00 0.7985
Landsat ETM+ (2001)
50 42 84.00 0.7898
Landsat TM (2011)
50 38 76.00 0.6730
Results:
LU / LC Class1973 Area in (Sq km)
1992 Area in (Sq km)
2001Area in (Sq km)
2011Area in (Sq km)
Built-up 28.50 62.13 130.03 155.99
Agricultural Land 14.42 13.27 20.11 16.82
Vegetation 11.30 11.13 17.98 15.62
Fallow Land 9.97 10.52 17.18 15.89
Scrub Land 67.69 45.60 54.26 35.30
Rivers and Lakes 4.29 1.82 2.72 2.66
Canal 2.59 1.53 1.56 1.56
Total Area 138.76 146.00 243.84 243.84
+43.43%
-3.49%
-1.73%
-0.67%
-34.3%
-2%
-1.23%
Land use/ land cover area of Pune city
The built-up area of Pune city increased between 1973 and 2011 by 43.37% from 28.50 km² to 155.99 km². Also, the areas with water bodies, vegetation, agriculture land and fallow land have been decreased.
Comparison of land use/land cover (LU/LC) changes
Suggestions:
As the satellite imageries help to maintain truthful record of terrain during that period, it can be used
To check the deviations in the land uses.
To monitor the changes in “Hot Spots” and to take appropriate action.
To identify illegal encroachments along the hill slopes and the riverbanks.
To maintain the green cover.
Fertile land around the city to be protected.
Population growth of the city is controlled.
Land use/land cover pattern of the study area would be of immense help in formulation of policies and programmes required for developmental planning.
This would subsequently help the corporation authorities to extend services and amenities.
Applications:
The accuracy and the information content can be considerably enhanced for various planning purposes.
To provide the necessary input and intelligence for preparation of base maps, formulation of Planning proposals and act as a monitoring tool during the implementation phase.
To improve land management policies and decisions.
To provide accurate and cost-effective tools to understand LULC changes.
Forecast future development.