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Urban Landscape analysis through Spatial Metrics
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Anindita Dasgupta1           Uttam Kumar1,2,3          T.V. Ramachandra1,3,4,*
1Energy and Wetlands Research Group, Centre for Ecological Sciences [CES], 2Department of Management Studies, 3Centre for Sustainable Technologies (astra),
4Centre for infrastructure, Sustainable Transportation and Urban Planning [CiSTUP], Indian Institute of Science, Bangalore – 560012, India.
*Corresponding author:
cestvr@ces.iisc.ernet.in

Study area and Data

Greater Bangalore is principal administrative, cultural, commercial, industrial, and knowledge capital of the state of Karnataka with an area of 741 sq. km. and lies between the latitudes 12°39’00’’ to 13°13’00’’N and longitude 77°22’00’’ to 77°52’00’’E. Bangalore city administrative jurisdiction was widened in 2006 by merging the existing area of Bangalore City spatial limits with 8 neighbouring Urban Local Bodies and 111 Villages of Bangalore Urban District to form Greater Bangalore. Now, Bangalore (figure 1) is the fifth largest metropolis in India currently with a population of about 7 million (Ramachandra and Kumar, 2008).


Figure 1: Study Area: Bangalore city, Greater Bangalore

Since, urbanisation and urban sprawl are more a local phenomenon and site specific than global, local urban sprawl tends to increase along ring roads, highways in a certain direction, around service facilities in another direction, which later become the urban centre hub and extends in all directions. Therefore, a better way to understand the spatio-temporal pattern of a city is to study the urban landscape in different directions from the central business district. Therefore, the city was divided into 8 zones [North (N), Northeast (NE), East (E), Southeast (SE), South (S), Southwest (SW), West (W), and Northwest (NW)] with their origin from the ‘city centre’ (figure 1).

The RS data used to study the temporal changes in landscape pattern were Landsat Multispectral Scanner (MSS) of 1973, Landsat Thematic Mapper (TM) of 1992, Landsat Enhance TM Plus (ETM+) of 2000 and 2010 and IRS LISS-III MSS for 2006. The data were georeferenced, rectified and cropped pertaining to the study area. Landsat ETM+ bands of 2010 were corrected for the SLC-off by using image enhancement techniques, followed by nearest-neighbour interpolation. All the images were resampled to 30m spatial resolution (1130 rows and 1170 columns) for consistency, easy analysis and interpretation. Layers of road network, drainage network, water bodies, etc. were obtained from the Survey of India (SOI) Topographical sheets of scale 1:250, 000 and 1: 50, 000. Handheld GPS (Global Positioning System) were used to collect ground information and Google Earth image (http://www.earth.google.com) were used for validating the classified outputs.

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Citation : Anindita Dasgupta, Uttam Kumar, and Ramachandra T. V., (2010), Urban landscape analysis through Spatial Metrics, Proceedings of International Conference on Infrastructure, Sustainable Transportation and Urban Planning, (CISTUP@CiSTUP), Indian Institute of Science, Bangalore, India, 18-20 October, 2009.
* Corresponding Author :
Dr. T.V. Ramachandra
Energy & Wetlands Research Group, Centre for Ecological Sciences, Indian Institute of Science, Bangalore – 560 012, India.
Tel : +91-80-2293 3099/2293 3503-extn 107,      Fax : 91-80-23601428 / 23600085 / 23600683 [CES-TVR]
E-mail : cestvr@ces.iisc.ernet.in, energy@ces.iisc.ernet.in,     Web : http://wgbis.ces.iisc.ernet.in/energy, http://ces.iisc.ernet.in/grass
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