Approach to Model House Rent for Cities

The factors or criteria associated with the sustainable and economically potential planning for housing are often ignored in the contemporary planning practices like zoning. House rent is depended on several criteria or facilities surrounded or related with it. It has been tried to explore those criteria and to develop a linear regression model that can explain the house rent for Khulna city. Vector base GIS software ArcGIS as well as statistical software SPSS has been used to build this spatial decision support model. The major finding of the study is a linear regression equation: Y = 881.06 X1 + 1290.24 X2+ 0.005 X3+ 9.211 X4 - 0.047 X5 - 0.174 X6 + 0.054 X7 . In the equation, Y represent house rent (In Taka) and X1, X2, X3, X4, X5, X6 and X7 represent number of room, building material (roof), land value, width of access road, distance of shopping center, distance of elementary school, distance of railway station respectively. With this model, the development authority as well as other public or private organizations can chose their site for housing considering the cost recovery and desired profit. The model could be used to predict the future house rent structure for a city.