Abstract
This paper addresses a model for evaluating land use suitability in the city of Qazvin, Iran. It considers greenbelt was an opportunity to increase the ecological performance and the quality of life in the city. Existing traditional orchards and a Forest Park that could be part of a sub-natural greenbelt, but the weak structure of the local management and poor applied information technologies are jeopardising any opportunity to create a greenbelt programme. In this regard, MICMAC and GIS techniques are considered to provide sounds arguments for a greenbelt planning in the city. This was carried out through a hybrid method with statistical and spatial analysis. The results revealed that a greenbelt would be spatially corresponded to the existing traditional orchards and the Forest Park with an overlapping of 40%. Hence, Qazvin has a good opportunity to plan a suitable greenbelt, as a measure to control the course of a rapid urban sprawl. Based on the evidences gathered in Qazvin, a conceptual model for planning greenbelts is proposed.
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Notes
The SLEUTH is a modified Cellular Automata (CA) model for urban growth modelling and the name comes from the abbreviation of its data input requirements which are slope, land use, exclusion zone, urban, transportation and Hill shade. In SLEUTH, the dynamic urban growth is expressed by four rules: spontaneous, new spreading center (diffusive), edge (organic) and road-influenced growth (Candau 2002).
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We thank anonymous reviewers for technical suggestions on data interpretations.
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This work is partially based on the thesis “Opportunities of urban development based on greenbelt concept (Case study of Qazvin, Iran)” submitted for a PhD degree at the Department of Architecture and Urban Planning, Lusófona University—Lisbon (Portugal).
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Madanian, S., Costa, C.S. A model for evaluating a greenbelt planning in the city of Qazvin (Iran) using MICMAC method. Model. Earth Syst. Environ. 3, 1503–1513 (2017). https://doi.org/10.1007/s40808-017-0373-1
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DOI: https://doi.org/10.1007/s40808-017-0373-1