Analysis of the scale effect on urban green structures with landscape planning approach; A case study on districts 1 and 3 in Tehran

Document Type : Research Article


1 Assistant Professor of Geography and Urban Planning, University of Tehran, Tehran, Iran

2 PhD student in Environmental Planning, University of Tehran, Tehran, Iran

3 Assistant Professor of Environmental Planning and Management, University of Tehran, Tehran, Iran



Understanding the problems of cities and also their physical pattern and form at different scales are very important. In addition, urban structure planning requires the use of localized data at the appropriate scale. Choicing of the optimal scale in studies is one of the principles that can make the results of studies more accurate and practical. The purpose of this study is investigating the effect of scale on urban spatial and environmental studies of 1 and 3-district in Tehran. The present research approach describes the effects of scale on urban land scape by using ecological land scape pattern and satellite images in meso-scale (Landsat satellite) and micro-scale (Quickbird satellite). Comparing the results of land scape quantification in the meso and micro scales in 1 and 3-district in Tehran, indicates the difference in the results. In the first scale 1747 green patches and in the second scale, 36516 green patches were distinguished, which both of them are used. Also some differences are in the size and density of the edge as well as the shape of the patches in the two study scales. In addition, the results show that the characteristics of patches in micro-scale of 1 and 3-district in Tehran are closer to the natural state of green space of these deistricts and more applicable in urban and local planning but they arrangements are less. This less order has nothing to do with the destruction of such space. The importance of arrangement of patches is important in regional studies. At this level, mid-scale images survey are recommended. In general, by guiding studies based on the principles of scale, the uncertainty of the results can be minimized and the quality of decisions will be improved.


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