Residential development pattern of Peri-Urban areas : a case of Pune city

Abstract

Urbanisation is increasing at a much higher rate. Due to the high rate of urbanisation and industrial growth every city is expanding in terms of urban sprawl, which led to a certain shift of city from the core to the periphery. This changes the land use pattern of the periphery. In every metropolitan city land value of core is high, in which there is very little or no space to build. This is forcing developers shift to the periphery. There is a sudden increase in construction at the periphery in the last few years to cater to the demand for housing but still, there is large unmet demand and empty stock. While the housing supply has been increased in numbers, the affordability gap has also increased as policies usually do not focus on market segmentation. There is a need is to identify the residential location choice preferences, to locate different patches in the peri-urban areas for different socio-economic groups. According to the report on the Estimation of Urban Housing Shortage (2012), there has been an immense gap between demand and supply of urban housing in India. The economically weaker sections (EWS) and low-income group (LIG) accounted for about 96 percent of the total housing shortage in India. This shows that there is a need for affordable housing which can bridge the gap between demand and supply in consideration with the on-ground situation of different cities. The research attempts to find the preferences of the people of different socioeconomic groups to attract the appropriate residential development at the periphery and bridge the demand-supply gap. It identifies the factors that influence the type of residential development at the urban periphery and generate future scenarios of development responding to the demand. This result to identify certain development pattern in case of different socio-economic groups at the periphery of the Pune city. Methods used for analysis is Ordinary Least Square Regression taking property price as a dependent variable and Distance from Airport, Bus Stop, Railway Station, Hospitals, College, Schools, and Buffer distance from Business Districts were taken as independent variables. This method has been done in three stages,v first for all the residential projects marked, secondly according to the different socio-economic groups and third according to the spatial classification. By the end of the research we will be able to identify the preference of parameters for different socio-economic groups. It also predicts the location pattern for future residential development in peri-urban areas. So that it could bridge the demand and supply gap with minimum empty stock which can further lead to proper utilization of land and other resources.