Change detection analysis in land use / land cover of Pune city using remotely sensed data
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The document analyzes land use and land cover changes in Pune City using remotely sensed data from various Landsat satellites. It highlights a significant increase in built-up areas by 43.37% from 1973 to 2011, while agricultural and natural land cover have decreased. The study emphasizes the need for sustainable environmental planning and monitoring of land use changes to address urban challenges like pollution and unauthorized developments.
Change detection analysis in land use / land cover of Pune city using remotely sensed data
- 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.
- 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.