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Urban Growth Dynamics and Modelling Using Remote Sensing Data and Multivariate Statistical Techniques


Affiliations
1 Department of Geography, Kalindi College, University of Delhi, Delhi 110 008, India
2 Delhi School of Economics, Department of Geography, University of Delhi, Delhi 110 008, India
3 Department of Geography, Kumaun University, SSJ Campus, Almora 263 601, India
4 Department of Geography, Kamla Nehru Institute of Physical and Social Sciences, Sultanpur 228 118, India
 

In this article, sprawl area of impervious surfaces and their spatial and temporal variability have been studied for Pune city over a period of 19 years, i.e. 1992–2011. Statistical techniques and image classification approach have been adopted to quantify the urban sprawl and its spatial and temporal characteristics. For this purpose, satellite images were obtained from various sensors, viz. Landsat Thematic Mapper and Landsat Enhanced Thematic Mapper Plus. To establish the relationship between urban sprawl and its causative factors, multivariate statistical technique has been used. The determinants of causal factors of urban sprawl such as population, α-population density, β-population density, workforce engaged in secondary and tertiary sectors, road density, and gender gap in literacy collectively explain the 93.09% variation in urban growth. The result also depicts that incessant growth in the built-up area in Pune city has surpassed the rate of population growth. From 1992 to 2011, population in the region grew by 75.40% while the amount of built-up land grew by 227.3%, i.e. more than three times the rate of population growth. To understand the future urban growth of Pune city, a foresight approach is being developed that allows long-term projections. This depicts that by the year 2051, the built-up area in the municipal limits would rise to 212.27 sq. km, which may be nearly 50.0% more than that in 2011 (141.50 sq. km). The vegetative areas, open spaces and areas around the highways are expected to become major targets for urban sprawl due to further increase in the pressure on land.

Keywords

Remote Sensing, Statistical Techniques, Spatial and Temporal Variability, Urban Sprawl.
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  • Urban Growth Dynamics and Modelling Using Remote Sensing Data and Multivariate Statistical Techniques

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Authors

Manish Kumar
Department of Geography, Kalindi College, University of Delhi, Delhi 110 008, India
R. B. Singh
Delhi School of Economics, Department of Geography, University of Delhi, Delhi 110 008, India
Ram Pravesh
Department of Geography, Kumaun University, SSJ Campus, Almora 263 601, India
Pankaj Kumar
Delhi School of Economics, Department of Geography, University of Delhi, Delhi 110 008, India
Dinesh Kumar Tripathi
Department of Geography, Kamla Nehru Institute of Physical and Social Sciences, Sultanpur 228 118, India
Netrananda Sahu
Delhi School of Economics, Department of Geography, University of Delhi, Delhi 110 008, India

Abstract


In this article, sprawl area of impervious surfaces and their spatial and temporal variability have been studied for Pune city over a period of 19 years, i.e. 1992–2011. Statistical techniques and image classification approach have been adopted to quantify the urban sprawl and its spatial and temporal characteristics. For this purpose, satellite images were obtained from various sensors, viz. Landsat Thematic Mapper and Landsat Enhanced Thematic Mapper Plus. To establish the relationship between urban sprawl and its causative factors, multivariate statistical technique has been used. The determinants of causal factors of urban sprawl such as population, α-population density, β-population density, workforce engaged in secondary and tertiary sectors, road density, and gender gap in literacy collectively explain the 93.09% variation in urban growth. The result also depicts that incessant growth in the built-up area in Pune city has surpassed the rate of population growth. From 1992 to 2011, population in the region grew by 75.40% while the amount of built-up land grew by 227.3%, i.e. more than three times the rate of population growth. To understand the future urban growth of Pune city, a foresight approach is being developed that allows long-term projections. This depicts that by the year 2051, the built-up area in the municipal limits would rise to 212.27 sq. km, which may be nearly 50.0% more than that in 2011 (141.50 sq. km). The vegetative areas, open spaces and areas around the highways are expected to become major targets for urban sprawl due to further increase in the pressure on land.

Keywords


Remote Sensing, Statistical Techniques, Spatial and Temporal Variability, Urban Sprawl.

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DOI: https://doi.org/10.18520/cs%2Fv114%2Fi10%2F2080-2091