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.

1. Change Detection Analysis in Land Use / Land
Cover of Pune City Using Remotely Sensed Data
Nitin N. Mundhe1 and Ravindra G. Jaybhaye2
Department of Geography, S. P. College, Pune, India
2
Department of Geography, University of Pune, India
1
National Conference on “Monitoring Degraded Lands” jointly organized by Agasti Arts, Commerce and
Dadasaheb Rupwate Science College, Akole and Maharashtra Bhugolshastra Parishad Pune

2. 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.

3. Need of Study:
The no. of million cities and actual area under these cities are also
increasing .
This haphazardly increasing trend has been created problems like
environment 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.

4. 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)

5. 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
Toposheets No. 47F/14/1 to 47F/14/6
F/15/NE, F/15/NW and 47F/15/SE
Satellite Imagery –
Landsat 1(MSS), 5 (TM) and 7 (ETM+)
Sources
Survey of India, scale 1:25000
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)
Global Land Cover Facility (GLCF)
earthexplorer.usgs.gov web site

6. 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.

7. Flowchart of Methodology

8. Source: Global Land Cover Facility (GLCF) http://glcf.umiacs.umd.edu
False Colour Composite (FCC) Landsat imageries of Pune City:
(a) January1973, (b) December 1992, (c) November 2001, (d) February 2011.

9. Results:

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-up
ii. Agricultural land
iii. Scrub land
iv. Fallow land
v. Vegetation
vi. Rivers and Lakes
vii.Canal
o 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 Images
Total number
of pixels
Number of
correct pixels
Overall
Accuracy in %
Overall Kappa
Statistics
Landsat MSS (1973)
50
43
86.00
0.7580
Landsat TM (1992)
Landsat ETM+
(2001)
Landsat TM (2011)
50
42
84.00
0.7985
50
42
84.00
0.7898
50
38
76.00
0.6730

11. Land use/ land cover area of Pune city
1973 Area
in (Sq km)
1992 Area
in (Sq km)
2001Area
in (Sq km)
Built-up
28.50
62.13
130.03
155.99
+43.43%
Agricultural Land
14.42
13.27
20.11
16.82
-3.49%
Vegetation
11.30
11.13
17.98
15.62
-1.73%
Fallow Land
9.97
10.52
17.18
15.89
-0.67%
Scrub Land
67.69
45.60
54.26
35.30
-34.3%
Rivers and Lakes
4.29
1.82
2.72
2.66
-2%
Canal
Total Area
2.59
1.53
1.56
1.56
-1.23%
138.76
146.00
243.84
243.84
LU / LC Class
2011Area
in (Sq km)
 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.

12. Comparison of land use/land cover (LU/LC) changes

13. 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.

14. 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.