Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/5144
Title: Modelling Urban Sprawl Along Minna Western Bye-Pass Using Remotely Sensed Data
Authors: Mohammed, Bala Banki
Musa, Haruina Danladi
Keywords: Urban sprawl
Remote sensing/GIS
Spatial modelling
Issue Date: 2010
Abstract: Many state capitals today in Nigeria are witnessing unprecedented population growth and increasing rate of urbanization that are deficient in indispensable infrastructural facilities, urban planners who are meant to have the knowledge of future urban growth and the multi-dimensional factors which has hitherto influence the growth of towns and cities are unaware of them because of the inefficiency of the traditional surveying method. In view of this prevailing scenario in Nigeria, this paper presents the capability of using Remote Sensing, GIS and spatial statistics in modelling urban sprawl along Minna Western Bye-pass. Data for the study were obtained through questionnaires and satellite imageries. The analysis of field survey revealed that low price of land, lack of basic utilities, facilities in the area, low level of awareness of development control, and low level of education of inhabitants were the causal factors of sprawl in these areas. The analysis of the time series spatial data such as: SPOT HRV image acquired in 1993 and Landsat ETM acquired in 2007 shows that low density sprawl and ribbon sprawl pattern are the two patterns identifiable and synonymous to this area. Comparison of data set for the two dates also revealed a change of 191.40 acres (77.4571.14 sqm), representing 59% of total landuse change over same period, where the population grew by 111.61%. Spatial regression analysis was carried out to model the extent of sprawl in the area. First, a simple regression analysis was conducted using key factors identified (independent variables) and percentage of built-up (POBUILT) for each area along the Bye-pass (independent variable) and the results shows that the percentage of those who relocated because of low price of land in the study area (LOPLAND) and percentage of migrant in search for white-collar job (COLLARJOB) contribute more to the explanatory power of the model. Multiple regression analysis was finally done by regressing LOPLAND, population of year 2007 (independent variables) and POBUILT (dependent variables) to fashion out an equation that forecast future sprawl and it was established that built-up area for 2021 will be 3,888.23 acres, which reveals excessive future spatial development along the bye-pass.
URI: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/5144
Appears in Collections:Urban & Regional Planning

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