Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-8, 709-716, 2014
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-8/709/2014/
doi:10.5194/isprsarchives-XL-8-709-2014
© Author(s) 2014. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
28 Nov 2014
Dynamics and forecasting of population growth and urban expansion in Srinagar City – A Geospatial Approach
M. Farooq1 and M. Muslim2 1Department of Ecology, Environment and Remote Sensing, SDA Colony Bemina, Srinagar, J&K, 190018, India
2Division of Environmental Sciences, SKUAST-K Shalimar, J&K, 191121, India
Keywords: Urban, Sprawl, Population, Regression, Temporal Abstract. The urban areas of developing countries are densely populated and need the use of sophisticated monitoring systems, such as remote sensing and geographical information systems (GIS). The urban sprawl of a city is best understood by studying the dynamics of LULC change which can be easily generated by using sequential satellite images, required for the prediction of urban growth. Multivariate statistical techniques and regression models have been used to establish the relationship between the urban growth and its causative factors and for forecast of the population growth and urban expansion. In Srinagar city, one of the fastest growing metropolitan cities situated in Jammu and Kashmir State of India, sprawl is taking its toll on the natural resources at an alarming pace. The present study was carried over a period of 40 years (1971–2011), to understand the dynamics of spatial and temporal variability of urban sprawl. The results reveal that built-up area has increased by 585.08 % while as the population has increased by 214.75 %. The forecast showed an increase of 246.84 km2 in built-up area which exceeds the overall carrying capacity of the city. The most common conversions were also evaluated.
Conference paper (PDF, 1255 KB)


Citation: Farooq, M. and Muslim, M.: Dynamics and forecasting of population growth and urban expansion in Srinagar City – A Geospatial Approach, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-8, 709-716, doi:10.5194/isprsarchives-XL-8-709-2014, 2014.

BibTeX EndNote Reference Manager XML