عنوان مقاله [English]
Morphology examines the cities as the human resorts, which contain form. The morphologists study the process of urban development as well the progression of the morphologic element. The buildings, land development, streets, and texture structures are considered as the main elements of urban morphology. The main question is whether changes in morphology will lead to improvement in structural function. So, the aim of present study is to develop a unified model for morphological studies to explain the structural-morphologic components. Using a method called ad hoc scrutiny and diagrams analysis, the author has found three main structural-morphologic components (streets pattern, blocs pattern and zone pattern). In this regard, the technique of Urban Network Analysis (UNA) and the test of t-pair samples were chosen as the main tool. For this, Gheytarieh in Tehran was chosen as the study zone. It has planned, organic and semi-organic texture. The centrality indices which include accessibility, intermediacy, proximity, attraction and straightforwardness were evaluated in terms bloc, zone (area, shape, location), and roads network (the length and width of the route). It is worth to note that there was a huge building bloc in Gheytarieh (Sobhan Housing Complex) which distracted the whole location, since it obstructs the inter-textural accesses. Thus, in order to measure the effect of the morphological changes, the body modification was performed. The test of t-pair samples was carried out to measure the level of modification effects. The test results show that desired modifications in the form will lead to improvement in zone performance.
Introduction: Morphology is the appearance study of the city, its gradual texture formation, and interactions between different components of textures affecting urban spaces such as streets, squares, buildings, and other public spaces (Zhouv & Gao, 2018:185-193). Due to the multiplicity of studies, this article simultaneously uses two methods and has been directed toward content analysis and explanatory purposes. To evaluate the concept of urban morphology, indices such as compaction, complexity (Makido et al, 2012:55-67), porosity-permeability (Silva et al, 2014:366-376), building plan area fraction, road area fraction, distance of first-row building to road, width-to-height ratio, building surface area to plan area ratio, height-to-width ratio (Hao et al, 2015:510-519), building height, road width, road area percentage to total area (Tang & Wang, 2007:1750-1764), occupancy coefficient, landscape, and outdoor and street (Wang & Kang, 2011:556-568) have been used. The application of these concepts and indices in areas of traffic smoothing, air (and noise) pollution reduction, and such areas will be reflected especially in metropolitan areas (Parilla and Trujillo, 2014:226-239). Physically, the three factors of road, passage network, and area, form and shape of the buildings have the highest impact level. (Karami et al., 2016:74). Therefore, understanding related morphological indices to the physical components are essential, since the main issue is that theoretical foundations are lacking all-encompassing concepts of urban morphology and not only the urban space bodies haven’t defined, but also no component explaining the urban physical-morphological space has been defined. So, by establishing a scientific link between the components of urban space and extracting the physical components and obtaining the main morphological indices, explaining the physical-morphological components can be set as the main goal of this research.
Methodology: Using case study and diagrammatic analysis, researchers in this study elucidated three main physical-morphological components (street pattern, block pattern, fragment pattern) and in this regard, urban network analysis technique for direct block and fragment analyzing capability selected as the superior method, and the paired t-sample test selected as the main tool of assessing the changes effects in the tissue. UNA technique has been used as an add-on in the ArcGIS software and the paired t-sample test in SPSS software has been used to validate the range of the performance enhancement. By calculating five centralized indices (accessibility, interconnection, proximity, gravity, and directness), UNA software uses spatial analysis of space networks. The data used were spatial data (at block and fragment level) in the form of indices such as area, shape, orientation (polygon data), and network length and width (path). To this end, the multivariant Gheytariyeh neighborhood was selected as the study context.
Results and discussion: Findings from the urban network analysis method showed street (access) is the most influential physical-morphological component. Therefore, making changes in access will have the highest impact on the physical structure. The block pattern is the second priority and block variety has a significant size-wise (area) effect on the morphology of the block. The fragment pattern is the third most influential component whose size (area) and their relationship to the access network, have significant effects on the texture. Also, the focus and centralized indices are higher in the central texture and the border of Kaveh Blvd. and Ghalandari Ave., in which the presence of a coarse block (Sobhan complex) due to lack of direct function (lack of access) has led to high traffic throughout its texture. Therefore, in the proposal, new access to the urban network was created by providing access from the eastern entrance on Kaveh Blvd. to the western entrance on Ghalandari Ave. The output maps also showed the overall improvement of the texture performance. Finally, the paired t-sample test was used to measure the improvement of tissue function.
Conclusion: The results showed that with the mean four accessibility indices changes, the Interstitial, the directness, and the proximity decreased, but the levels of standard and the mean deviation decreased significantly. That is, lower levels of traffic conceivable by reducing overall levels of indices and optimizing their distribution throughout the neighborhood. Also, in the paired t-sample test, a correlation test was performed that resulted positive for all indices, meaning that changes were more focused on blocks with the highest levels of the five indices. The results of the correlation test show a positive relationship and a reduction in the network cramming and traffic level in all ranges, which was the aim of the present study. The overall result of the assumptions and the urban network analysis techniques shows that if the average area of blocks and fragments be medium and the accesses be less obstructed in length, the texture performance is better and the scientific morphological changes in each part of the texture will improve the physical quality and reduce traffic cramming throughout the tissue.
Keywords: Urban Morphology, Urban Space, Urban Network Analysis, Block and Fragment Analysis, Centralized Indices.