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Subway stations are one of the most popular public spaces in the Iranian big cities, which is accompanied by urban design low qualities. The urban design of knowledge, art, and profession is the organization of the environmental qualities of the urban and public domain of the subject. Considering low qualities in these modern spaces that are used by everyday people, the most important issue of the present research is constructed without reference to indigenous fields. Emphasis on indigenous patterns, in the construction of underground spaces, especially subway stations, can lead to the sustainability and desirability of these spaces. The development of urban-rural spaces can play an important role in the sustainability of contemporary large and populated cities. Construction and construction of these spaces is a new phenomenon in Iran that can weaken or strengthen the natural, human, social, cultural, and economic characteristics of cities such as Tehran. In this paper, the purpose of this paper is to explain the status of the design of urban design in metro station spaces, with emphasis on indigenous patterns. The present study is conducted using the descriptive-analytical methodology and studies between the three areas of urban design and related qualities; subsurface development and metro station spaces; native architectural and urban design patterns. Therefore, after the design of the problem and terminology, the study of definitions and urban design qualities from the point of view of the experts and the addition and extraction of comprehensive urban design qualities was done with the article approach. Subsequently, in order to study Imam Khomeini, Seventh, and Revolution Square subway stations, they were studied and analyzed. The results of the study indicate that the planning and design of metro station spaces should pay attention to the comprehensive design quality of the city. These qualities include identity recognition, environmental sustainability, socioeconomic and economic sustainability, safety and security, efficiency and diversity, accessibility and accessibility, continuity and integrity, proportions and human scale, freedom, flexibility, Vitality, intuition and sensual richness, justice. The analysis of case examples, both in terms of both generic and indigenous patterns, has a low status and poor quality of urban design and indigenous patterns. In general, paying attention to the design qualities of a design based on native patterns can enhance their sustainability, utility, and humanity. Introduction Urban design is a science, art, and profession dealing with organizing the environmental qualities of urban and public areas. Paying attention to the vacuum of urban design qualities in these modern spaces that are used daily by people is the most important issue of the present study, which has been constructed without any connection with local contexts. By presenting this issue, the purpose of this study is to explain the position of urban design qualities in metro station spaces with an emphasis on local patterns. In the process of urban development, all aspects of environmental quality must be considered. In other words, strengthening or meeting one or more (private and public) needs and environmental quality should not lead to the weakening or loss of other environmental qualities. This is an issue common in contemporary projects. One-dimensional views of urban projects, such as a purely economic or traffic approach, will neglect the underlying features, undermine identity, and move in the opposite direction of sustainable development. The theme of this research is that, on the one hand, the development of urban infrastructures such as metro stations, especially in large cities and their centers, is a matter of certainty and these infrastructures in the dimensions of transportation, space, play an important role in the life of urban centers. But on the other hand, the construction of these spaces is often devoid of environmental qualities and less attention is paid to local patterns. The research hypothesis is that by accompanying and using local models in the planning and development of subsurface spaces, both goals can be achieved, namely the development of urban infrastructure, strengthening urban identity, and improving environmental qualities. Therefore, this study seeks solutions to use local patterns in the development of subsurface spaces and subway stations. Research Methods This study aims to analyze the position of urban design qualities in the design of metro stations. The study is conducted using a combined research approach (i.e. quantitative and qualitative methods). In this regard, the most important research question is: What is the position of urban design qualities in the design of metro stations? Also, the research sub-questions are: What are the qualities of urban design effective in the design of metro stations? What are the ways to apply these qualities with emphasis on indigenous patterns in subway stations? In this research, while analyzing the features and qualities of native patterns, the application of these patterns, related features, and qualities in the planning and design of contemporary underground spaces in our country are discussed and solutions and suggestions are presented. Therefore, while defining these concepts from the theorists’ point of view, we summarize and conclude these definitions, and then search for native patterns of architecture and urban planning for use in the planning and design of metro stations. Research Findings The results of the study show that in planning and designing metro station spaces, comprehensive qualities of urban design should be considered. These qualities include identity, legibility, environmental sustainability, social, cultural and economic sustainability, safety and security, efficiency and diversity, pedestrianism and ease of access, cohesion and integration, human proportions and scale, freedom, flexibility, vitality, attractiveness and sensory richness, and justice. The analysis of case studies, both in terms of general qualities and indigenous patterns, indicates the low and weak position of urban design qualities and indigenous patterns. In general, paying attention to urban-design qualities with a focus on indigenous patterns can promote their sustainability, desirability, and humanity. Emphasis on indigenous patterns in the construction of underground spaces, especially subway stations, can lead to the stability and desirability of these spaces. The development of suburban urban spaces can play an important role in the sustainability of large and densely populated contemporary cities. The construction of these spaces is a new phenomenon in Iran that can weaken or strengthen the natural, human, social, cultural, and economic characteristics of cities like Tehran. From all these issues, it can be concluded that the role of subsurface spaces, including metro stations, in the sustainable development of cities, should be taken seriously and the comprehensive realization of environmental qualities should be considered by avoiding one-dimensional approaches in planning and designing these spaces. It can also be said that traditional Iranian indigenous buildings and collections such as Gudal Baghcheh, Shovadan, Cistern, the historical bazaar have valuable structural features (in terms of the form and function on architectural and urban scales) and can be a local model for the development of metro station spaces. Given that our country is on the verge of developing such spaces, paying attention to these points can play an important role in stabilizing cities and strengthening urban identity, and improving environmental qualities. These templates and design guides can be used in the planning and design of metro station complexes. Since the metro network is one of the most widely used underground spaces in large cities, the subsurface development in relation to metro stations and using the native patterns studied in this research can be useful and effective. [ABSTRACT FROM AUTHOR]

This paper introduces an improved convolutional neural network based on the conventional U-Net for simulating built-up land expansion. The proposed method hires a pixel-wise semantic segmentation approach considering the spatial drivers affecting urbanization as data cubes. Independent variables including altitude, slope, and distance from barren, crop, greenery, roads, and urban areas for 1998, 2008, and 2018 were considered as covariates for the simulation of built-up land expansion in Tehran and Karaj regions in Iran. The proposed method was compared with the random forest (RF) algorithm as the baseline model. Evaluation using the area under the total operating characteristic indicated the superiority of our modified U-Net (0.87) over the RF (0.82) algorithm. Furthermore, evaluation using the percent correct metric indicated that our proposed model is capable of learning neighborhood effects effectively leading to simulate built-up land expansion accurately, independent from applying a cellular automata (CA) model. Therefore, the modified U-Net independent from the CA which can consider the neighborhood effects is recommended for the simulation of built-up land expansion precisely. [ABSTRACT FROM AUTHOR]

This paper aims to improve the spatial accuracy of urban growth simulation models and clarify any associated uncertainties. Artificial Neural Networks (ANNs), Random Forest (RF), and Logistic Regression (LR) were implemented to simulate urban growth in the megacity of Tehran, Iran, as a case study. Model calibration was performed using data between 1985 and 1999 whereas the data between 1999 and 2014 was used for model validation. First of all, Transition Index Maps (TIMs) were computed by means of each model to assess the potential of urban growth for each cell. Using the standard deviation, consensus between the TIMs was evaluated. Because the TIMs of the individual models manifested discrepancies, they were combined using a number of ensemble forecasting approaches including median, mathematical average, principle component analysis, and weighted area under the total operating characteristic. The individual and combined TIMs were then put into Cellular Automata (CA) to simulate the future pattern of urban growth in Tehran. The results were evaluated in two stages. At first, the TIMs were evaluated by means of Total Operating Characteristics (TOC), and then a set of statistical indices was used to evaluate the spatial accuracy of the simulated urban growth maps. The best result was obtained by median ensemble forecasting, whereas the LR model showed the lowest level of accuracy. In similar studies, it is recommended to implement and compare different ensemble methods when integrating individual models. • We compared the effectiveness of ANNs, RF and LR for urban growth modelling. • Standard error map indicated discrepancy among the results of individual models. • Various ensemble forecasting approaches were proposed to combine individual models. • Mean ensemble forecasting created more accurate simulated maps. [ABSTRACT FROM AUTHOR]

Urbanization, growth of urban areas, is a process that has been growing rapidly during the last two decades. This phenomenon affects aerobiological, economical, industrial, ecological processes, social control, and the family. Hence, the prediction of the urban area extent has an important role in the future decision of the municipality. Multi-Agent System (MAS) is a proper tool for simulation and modeling process, which has been used for solving different types of spatial and non-spatial problems. In this article, we use MAS for urban simulation in the rural area around Tehran, which is the most populated and the fastest-growing city of Iran. In this paper, the behavior of three groups of agents: environmentalist, industrialist, and resident are simulated. These three groups are the dominant and influential population in the formation of urban texture. In this research, the behavior of these three groups of agents is specified, according to a series of map layers, such as slope, aspect, soil type, distance of urban areas, roads, and so on. The Belief-Desire-Intention (BDI) architecture of agents is used for the simulation, which is defined based on some variables, functions, and coefficients. The simulation is carried out based on two different interaction scenarios: Rational and Nash- Equilibria. The future urban area is predicted by a combination of MAS and spatial urban area. To evaluate the proposed model, the comparison of the predicted area is made at different times and scenarios. The results of implementation in different scenarios show that the residents of the study area follow the Nash-Equilibria interaction with Kappa Coefficient accuracy of 0.8104. [ABSTRACT FROM AUTHOR]

This paper couples a Forward Feature Selection algorithm with Random Forest (FFS-RF) to create a transition index map, which then guides the spatial allocation for the extrapolation of urban growth using a Cellular Automata model. We used Landsat imagery to generate land cover maps at the years 1998, 2008, and 2018 for the Tehran-Karaj Region (TKR) in Iran. The FFS-RF considered the independent variables of slope, altitude, and distances from urban, crop, greenery, barren, and roads. The FFS-RF revealed temporal non-stationary of drivers from 1998–2008 to 2008–2018. The FFS-RF detected that altitude and distance from greenery were the most important drivers of urban growth during 1998–2008, then distances from crop and barren were the most important drivers during 2008–2018. We used the Total Operating Characteristic to evaluate the transition index maps. Validation during 2008–2018 showed that FFS-RF produced a transition index map that had predictive power no better than an allocation of urban growth near existing urban. Simulation to 2060 extrapolated that Tehran, Karaj, and their adjacent cities will interconnect spatially to form a gigantic city-region. [Display omitted] • A Forward Feature Selection - Random Forest (FFS-RF) model describes urban growth. • FFS-RF found temporal non-stationarity of drivers in Iran's Tehran-Karaj region. • The Total Operating Characteristic evaluated the transition index map (TIM). • FFS-RF produced a TIM that has predictive power no better than a baseline TIM. • FFS-RF and Cellular Automata extrapolated urban growth to the year 2060. [ABSTRACT FROM AUTHOR]