Remote Sensing Analysis for Urban Sprawl Monitoring

How GIS and remote sensing can be used to monitor urban growth or land use changes

Urban sprawl detection at zones level of Jaipur city for better monitoring and planning (2008-2013)


Urban Growth estimation and monitoring is important process for urban planning for future development. The current growth and past trends can help to predict future demand for urban planning. The urban growth can be assessed using data created through satellite images. Satellite data cover important aspect that is temporal information, one can map urban growth of current as well past. GIS is a versatile tool, in which mathematical and statistical concepts can be integrated very easily. Therefore, GIS tool can be used for simulation and prediction of urban patterns for future. 

To assess the urban sprawl, built-up area is quantified using temporal satellite data for 2008, 2011 and 2013. Built-up area, which refers to the residential and commercial areas, industrial complexes, roads and paved ways etc., is captured for the Jaipur city using satellite data and Image processing software

The standard image processing techniques, such as image extraction, rectification and classification have been used for the analysis of three satellite images. Supervised classification using maximum likelihood classification (MLC) algorithm has been performed for the classification of satellite images. The algorithm was trained by supervised training process, after collection of parametric and non-parametric signatures. 

The classification results obtained from supervised classification are re-checked with ground data and other secondary data to find out wrongly classified or missing pixel and these pixels were updated adequately.

Fig: Changes in built-up area (in Hectare) 

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