Ema Corodescu, Cătălin Cîmpianu


The urban expansion process has become a major challenge for the scientists and urban planners, mainly due to its various spatial and functional expressions. The present study aims to identify the spatial patterns of several driving forces of this phenomenon in Constanta metropolitan area. In order to reach our purpose, multi-temporal remote sensing data was employed; by image processing, we obtained the built-up area for 2001 and 2013. Subsequently, a Geographically Weighted Regression model was employed to explore the relationship between the newly-built-up area and four driving forces related to accessibility: distance to the shoreline, distance to the existing built-up area, distance to the road network and distance to Constanta city center. By studying the spatial distribution of the regression coefficients for the explanatory variables we mapped the relevance of each driving force, leading to the general conclusion that the strongest driving forces are the distance to the built-up area and the distance to the road network. At the same time, the spatial distribution of the correlation coefficient and of the residuals revealed that the model best fits the axial and suburban areas, while the internal, consolidated areas record highly deviated residuals.


urban expansion, supervised classification, built-up area, driving forces, Geographically Weighted Regression

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