Abstract
Urban areas are most dynamic in terms of land use changes. The temporal changes can be monitored through satellite data and reflects the development taking place. Pattern recognition techniques are used to monitor the dynamics. In the present paper, Nagpur city urban sprawl has been studied using band ratioing techniques and fuzzy classification. The result shows an increase in the impervious layer which is the bench mark of urbanization and a corresponding decrease in the vegetation cover and the open spaces. This type of output can be used for planning of industries, garden, rejuvenation of water bodies and monitor the development activities.
Highlights
Urbanization refers to the change of rural lifestyles into urban ones (Antroo, 2003)
The Normalised Difference Built up Index (NDBI ) is used
It is clearly seen that the impervious layer consisting of mainly artificial surfaces and structures like pavements, parking lots, buildings etc. that are covered by impenetrable materials like asphalt, concrete, brick, stone and rooftops of houses and buildings are clearly delineated
Summary
Urbanization refers to the change of rural lifestyles into urban ones (Antroo, 2003). Remote sensing technology uses satellite imaging to retrieve information about the changes on Earth. These changes when properly recorded and monitored, give us an insight into the growth pattern, and the suggestive reasons for the drivers for such change. Sensed data provide synoptic view, spatial resolution in range of 30 cm and more, multi spectral data, revisit etc This data is an invaluable source of information for monitoring changes on earth surface and management of resources. Along with the image processing software, GIS software like ARC GIS 9.1 can be used for conversion of classified image to vector map, topology building and statistic generation Users can develop their own models using modeler icon and try new methods of feature extraction. For feature extraction heads up digitization is more useful due to enhanced spatial resolutions in high resolution satellite data
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