Rapid urban development and increasing land use changes due to increasing population and economic growth in selected landscapes is being witnessed of late in India and other developing countries. The measurement and monitoring of these land use changes are crucial to understand land use cover dynamics over different spatial and temporal time scales for effective land management. Today, with rapid urbanization and industrialization, there is increasing pressure on land, water and environment, particularly in the big metropolitan cities. Urban sprawl may be defined as the scattering of new development on isolated tracts, separated from other areas by vacant land (Ottensmann,1977). It is also often described as leapfrog development (Gordon and Richardson, 1977) as observed in all the major cities across the world. Urban sprawl has been criticised for inefficient use of land resources and energy and large scale encroachment onto the agricultural lands. There are many problems associated with fragmented conversion of agricultural land into urban use. The cities are expanding in all directions resulting in large-scale urban sprawl and changes in urban land use. The spatial pattern of such changes is clearly noticed on the urban fringes or city peripheral rural areas, than in the city centre. Inadvertently this is resulting in increase in the built up area and associated changes in the spatial urban land use patterns causing loss of productive agricultural lands, forest cover, other forms of greenery, loss in surface water bodies, depletion in ground water aquifers and increasing levels of air and water pollution. Further, it is widely agreed that fragmentation of land use is also harmful to biological conservation. There have been lot of debates on how to confine urban sprawl and conserve agricultural land resources (Bryant et al., 1982;Ewing, 1997;Daniels, 1997). There is a demand to constantly monitor such changes and understand the processes for taking effective and corrective measures towards a planned and healthy development of urban areas. In the recent times, Remote sensing data is being widely used for mapping and monitoring of urban sprawl of cities. The spatial patterns of urban sprawl over different time periods, can be systematically mapped, monitored and accurately assessed from satellite data along with conventional ground data. In the present study ‘Entropy Approach’ for studying the urban sprawl patterns of Hyderabad over different time scales has been attempted in the present study. Further, the use the GIS for quantifying the urban sprawl trends at various land use sites, viz., commercial, industrial, residential sensitive and mixed zones is also attempted.
The study area of Hyderabad city and environs extend from 17010/-17050/N and 78010/-78050/ E. The Hyderabad Urban Development Area (HUDA) is around 1907 sq.km. The HUDA area is divided into 29 planning zones (11 zones inside municipal limits and 18 zones in the non-municipal limits or peripheral areas). The city is located around 580m above Mean Sea Level (MSL). It experiences a minimum temperature of 11.60C and a maximum of 40.50C with an average annual rainfall of 73.55 cms. The city is situated centrally between the other metropolises of Mumbai, Chennai and Bangalore and is well connected by road, rail and air.
Datasets and Methodology
In the present study, IRS-1C (LISS-III + PAN) merged data of 1999, Hyderabad area is used for studying the entropy characteristics of urban sprawl patterns and their areal estimates are derived using satellite and GIS techniques.
The satellite characteristics of IRS-1C (LISS-III +PAN) data is given in table1. Land Use/Land Cover estimates of the previous years obtained from the local district records for the periods of 1980 and 1992 (Mary and Raghavaswamy, 2000) were also referred. The zones selected correspond to different locations in the Hyderabad city dominated by Residential (Banjara Hills), Industrial (Balanagar), Commercial (Paradise, Panjagutta, Abids and Charminar) Sensitive (Zoo park) and Mixed zone (Uppal). In the present study, we use the methodology of Yeh and Li (2001) is adopted for studying the urban sprawl characteristics through Entropy approach.
Shannon’s entropy (Hn) is used to measure the degree of spatial concentration or dispersion of geophysical variable (Xi) among n zones (Theil, 1967; Thomas, 1981). It is calculated by
Where Pi is the probability or proportion of a phenomenon (variable) occurring in the ith zone , and xi is the observed value of phenomenon in the ith zone, and n is the total number of zones. The value of entropy ranges from zero to log (n). If the distribution is maximally concentrated in one zone, the lowest value, zero will be obtained. Conversely, an evenly dispersed distribution among the zones will give a maximum value of log (n). Relative entropy can be used to scale the entropy value into a value that ranges from 0 to 1.Relative entropy Hn’ is (Thomas, 1981)
Entropy can be used to indicate the degree of urban sprawl by examining whether land development in a city is dispersed or compact. If it has a large value, then it indicates occurrence of urban sprawl. The buffer function of a GIS can be used to define buffers of zone from city/town centers of roads and thus the density of land development in each of these buffer zones can be used to calculate the entropy.