Les villes sont le lieu d’installation privilégié des instances étatiques, des décideurs économiques et des entités scientifiques. Aucun gouvernement ne peut donc engendrer davantage de croissance économique, sans élaborer judicieusement au préalable des plans précis concernant le système urbain. Cependant dans les pays en voie de développement les gouvernements ne regardent que les aspects strictement économiques des villes et ils en oublient leurs autres responsabilités sociales et politiques face à la croissance urbaine.Ce travail s’inscrit dans une approche interdisciplinaire combinant l’économie spatiale et la macroéconomie. L’économie spatiale est l’analyse des comportements des individus économiques dans l’espace. Dans cette thèse, nous mettons en évidence la liaison entre géographie et économie.Dans le travail présent, après avoir présenté le phénomène de l’urbanisation et le système urbain, nous avons examiné la loi de Zipf, loi de Gibrat et le coefficient spatial de Gini pour le cas de l’Iran et de la France. Ensuite nous avons estimé le modèle de la croissance urbaine pour les deux pays, selon les travaux de Henderson. / Cities are the host of people as well as government officials, decision-makers, economic and academic elite institutions. Therefore, it is not possible to having any plan without understanding of urban systems can be made. Regardless of the importance of this matter, governments of developing countries often neglect their responsibilities and duties with regards to the city. This work is a combination of Spatial Economic and macroeconomics. Spatial Economic has been defined as identifying and analyzing the performance of the people in a same geographic location.In this paper, first step is introducing the phenomenon of urbanization and urban systems and then, next aim is estimating the Zipf and Gibrat’s laws and Spatial GINI Coefficient for the case of Iran and France. The urban growth model for Iran and France is measured based on the Henderson theories.In this paper, after introducing the phenomenon of urbanization and urban systems, we estimated the Zipf's and Gibrat lows and Spatial GINI' Coefficient for the case of Iran and France. By using the Henderson theories we measured the urban growth model for Iran and France

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Thesis (MSc (Geography and Environmental Studies))--Stellenbosch University, 2008. / Accelerating urban growth places increasing pressure not only on the efficiency of infrastructure and service provision, but also on the natural environment. City managers are delegated the task of identifying problem areas that arise from this phenomenon and planning the strategies with which to alleviate them. It is with this in mind that the research investigates the implementation of an urban growth model, SLEUTH, as a support tool in the planning and decision making process. These investigations are carried out on historical urban data for the region falling under the control of the Cape Metropolitan Authority. The primary aim of the research was to simulate future urban expansion of Cape Town based on past growth patterns by making use of cellular automata methodology in the SLEUTH modeling platform. The following objectives were explored, namely to: a) determine the impact of urbanization on the study area, b) identify strategies for managing urban growth from literature, c) apply cellular automata as a modeling tool and decision-making aid, d) formulate an urban growth policy based on strategies from literature, and e) justify SLEUTH as the desired modeling framework from literature. An extensive data base for the study area was acquired from the product of a joint initiative between the private and public sector, called “Urban Monitoring”. The data base included: a) five historical urban extent images (1977, 1988, 1993, 1996 and 1998); b) an official urban buffer zone or ‘urban edge’, c) a Metropolitan Open Space System (MOSS) database, d) two road networks, and d) a Digital Elevation Model (DEM). Each dataset was converted to raster format in ArcEdit and finally .gif images were created of each data layer for compliance with SLEUTH requirements. SLEUTH processed this historic data to calibrate the growth variables for best fit of observed historic growth. An urban growth forecast was run based on the calibration parameters. Findings suggest SLEUTH can be applied successfully and produce realistic projection of urban expansion. A comparison between modelled and real urban area revealed 76% model accuracy. The research then attempts to mimic urban growth policy in the modeling environment, with mixed results.