4.7 Article

Urbanization pressure and modeling of urban growth: example of the Tunis Metropolitan Area

期刊

REMOTE SENSING OF ENVIRONMENT
卷 86, 期 3, 页码 341-352

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ELSEVIER SCIENCE INC
DOI: 10.1016/S0034-4257(03)00077-4

关键词

urban growth; land cover changes; remote sensing data; potential model

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Urbanization process is a major factor of change in the Mediterranean region where pre-urban cities and new urban settlements have raised over the past decades. Several cities rapidly became regional centres or international nodes according to economic and political pressures. Urbanization (and informal settlement) causes land cover changes which can lead to deeper social, economic and environmental changes. The main objective of this paper is to provide time-series information to define and locate the evolution trends of the Tunis Metropolitan Area. In a first step, satellite imagery has been used (1986-1996 SPOT XS) to extract the land cover, identify the urbanization processes and estimate the changes. One of the main aspects is to locate informal settlement areas that grow significantly along the roadway networks in the Tunisian capital. Results show a global progression of the built-up areas of 13% in 10 years. In a second step, the urban growth evolution has been approached by using a potential model that provides general trends of feasible urban expansion, taking into account protection laws of natural and agricultural land. This type of model has not been tested on developing cities and as such it corresponds to a new planning contribution for planners who have no concept of spatially how their urban areas have changed over time and where the growth is occurring. In this case, it has been calibrated over the period of 1986-1996, and then applied to predict the location of the built-up growth over the next 10 years (19962006). These results can provide local authorities and other stakeholders with information towards decision support documents for future planning and monitoring plans. Moreover, they can be updated systematically through the integration of remote sensing data. (C) 2003 Elsevier Science Inc. All rights reserved.

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