Modelling Urban Sprawl along Minna Western Bye-Pass Using Remotely Sensed Data.
No Thumbnail Available
Date
2010
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Maiduguri Journal of Art and Social Sciences (MAJASS)
Abstract
Many state capitals today in Nigeria are witnessing unprecedented populations 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 modeling urban sprawl along Minna Western Bye-pass. Data for the study were obtained through questionnaires and satellite imagery. The analysis of the field survey revealed that low price of land, lack f basic utility facilities in the area, low level of awareness of development control and low level of education of inhabitants were the major causal factors of sprawl in these areas. The analysis of the time series spatial data such GIS, SPOT HR image acquired in 1993 and Landsat ETM image acquired in 2007 shows that low density sprawl/ and ribbon sprawl patterns are the patterns identifiable and synonymous to this areas, comparison of data set for the two dates also revealed a change of 191,40 acres (77, 4571.14 sq. m.), representing 59% total landuse change over the 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 linear regression analysis conducted using key factors identified (independent variables) and percentage of built-SOM up (POBUILT) for each area along the Bye-Pass (dependent variable) and results s how’s that the percentage of those who relocated because of low in price of land in the study area (LOPLAND) and percentage of migrant in search for white-collar job (COLLARJOB) contribute more to the explanator power of the model. Multiple regression analysis was finally done by regressing LOPLAND, population of year 200)7 / Independent variable and POBUILT, dependent variable. to fashion out an equation that can forecast future sprawl, and it was established that built-up area for 2021 will be 3,888,23acres, which reveals excessive future spatial development along the bve- pass.
Description
Keywords
Urban sprawl, Remote Sensing /GIS and Spatial modeling
Citation
Mohammed, B.B. and Musa, Haruna D. (2010), Modelling Urban Sprawl along Minna Western Bye-Pass Using Remotely Sensed Data. Maiduguri Journal of Art and Social Sciences (MAJASS), Vol.8, No.1, pp.234-248.