Abstract | Full Paper | PDF | Printer Friendly Format

Abstract
In India, unprecedented population growth coupled with unplanned developmental activities has resulted in urbanization, which lack infrastructure facilities. This also has posed serious implications on the resource base of the region. The urbanization takes place either in radial direction around a well-established city or linearly along the highways. This dispersed development along highways, or surrounding the city and in rural countryside is often referred as sprawl. Some of the causes of the sprawl include – population growth, economy and proximity to resources and basic amenities. Patterns of infrastructure initiatives like the construction of roads and service facilities (such as hotels, tea shops, etc.) also often encourage the regional development, which eventually lead to urbanization. Identification and analyses of the patterns of sprawl in advance would help in effective infrastructure planning in urban area. In order to estimate and understand the behaviour of such urban sprawls, which is crucial for sound environmental planning and resource management, current study was undertaken along the Mangalore – Udupi National Highway (NH 17).

The pattern of urban sprawl is identified and modeled using remotely sensed data. This helped in identifying the linear and radial pattern of growth and its rate. The analyses involved were land cover, land use, spatial and temporal changes and urbanization growth pattern recognition in a buffer zone of 4 km wide on either side of the highway. The spatial and temporal analyses techniques such as Geographic Information Systems (GIS) and Remote Sensing are used to analyze and interpret the changes in the study region. The cadastral data comprises of the characteristics of land use / land cover, drainage network, roads and railway network and the administrative boundaries of 1972 from the toposheets of scale 1:50,000. Each character was digitized separately as vector layers. The remote sensing data was classified for land use, based on themes - built up, transportation (road and rail network), water bodies (sea, rivers, streams, etc.), agriculture and barren (uncultivable and waste land). For the change detection, temporal data between 1972 and 1999 (IRS platform) were used. This helped to identify the patterns of the change with respect to time.

The entropy approach was applied for quantifying the urban sprawl. Modeling of the sprawl was done considering both spatial and statistical parameters - land use, built-up, watershed, transportation and population. Sensitivity analysis was carried out considering the causal factors and their growth rates. The population growth rate and population density increase, are based on the demographic data for the period 1951- 2001, which is incorporated in the Decision Support System. The decisions were based on various alternatives arising under a given set of criterion for a given objective. These also help to predict the sprawl in the subsequent years.