During the last three decades, the expansion of the Tabriz Metropolitan Area (TMA) to the surrounding areas has caused the destruction of environmental resources and problems such as disturbing ecological balance, increasing service costs, construction over unsuitable lands, exacerbation of air pollution, and lack of consideration of existing deteriorated textures and previous ongoing trends, reducing the environmental quality of the TMA. The goal of this study was to perform ecological modeling of urban development in the TMA with respect to the preservation of environmental resources, prevention of urban sprawl, and the management of the physical expansion of the TMA in an eco-friendly manner. In this research, to investigate the previous pattern of growth of the TMA, Landsat satellite imagers from 1984 to 2018 were used to discover the non-ecological and sprawl development of the TMA, and artificial neural networks and logistic regression techniques were applied to simulate future development up to 2038. According to information from the Iranian Statistical Center and 34 year of satellite imagery analysis, the population of the TMA increased from 1,007,992 to 1,961,560 during this period. Additionally, urban and rural land area increased from 7220.34 hectares to 27,640.57 hectares. A lack of coordination between population and urban expansion, as well as a decrease of 8513.61 hectares of agricultural and garden lands was inferred from the Holdern model. Detailed Calculations of the Holdern index (sprawl tendency) showed a lack of consideration of urban development capacity with population growth rate, and the Holdern index is equal to 0.6 in Tabriz. For future ecologic development of the TMA, hexagonal blocking of the urbanization probability map was used alongside environmental development policies in the form of using 30 percent of infill development capacities of inefficient land uses to prevent sprawl growth in Tabriz. Additionally, to preserve ecological landscapes, ecological networks in the form of green belts and bows with a length of 91 km were designed that may be effective in preventing the merging of small cities and nearby villages in the Tabriz metropolis.

This study utilised multi-year data from 5354 incidents to predict pedestrian–road traffic accidents (PTAs) based on twelve socioeconomic and built-environment factors. The research employed the logistic regression model (LRM) and the fuzzy-analytical hierarchy process (FAHP) techniques to evaluate and assign weights to each factor. The susceptibility map for PTAs is generated using the “Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)”. Subsequently, the probability of accidents in 2020 was predicted using real multi-year accident data and the Markov chain (MC) and cellular automata Markov chain (CA-MC) models, with the prediction accuracy assessed using the Kappa index. Building upon promising results, the model was extrapolated to forecast the probability of accidents in 2023. The findings of the LRM demonstrated the significance of the selected variables as predictors of accident likelihood. The prediction approaches identified areas prone to high-risk accidents. Additionally, the Kappa for no information (KNO) statistical value was calculated for both the MC and CA-MC models, which yielded values of 0.94 and 0.88, respectively, signifying a high level of accuracy. The proposed methodology is generalizable, and the identification of high-risk locations can aid urban planners in devising appropriate preventive measures.

Landscape fragmentation and the elimination of urban green spaces are the results of human activities which put significant pressure on urban sustainability. The planning and developing of urban ecological networks and corridors as an effective approach is a response to rapid urbanization and fragmentation of natural areas. The Tabriz metropolitan as the fourth-largest city in Iran was selected as a case study that has grown rapidly over the past few decades. This study presents a practical approach and framework for assessing and enhancing ecological connectivity of landscape. The framework was developed based on the landscape metrics, graph theory, least-cost modeling, and geographic information system tools during three different periods (1984-2000-2020). The results using the values of landscape metrics such as CA, Edge Distance, Mean Patch Size, Mean Shape Index, large patch index, NP, Landscape shape index, and COHESION indicate that the urban landscape of Tabriz has been more fragmented over the past 3 decades and has lost its connectivity. To reduce the effects of fragmentation and enhance landscape connectivity in study area, we proposed a network of ecological corridors that passes through the core ecological patches. Our results also indicate that the core patches and the least-cost created corridors are mainly located in the suburbs of Tabriz and the central part of the city cannot be suitable for ecological development. Therefore, using the above-mentioned methods could be an effective approach to develop ecological networks and improve landscape connectivity that can encourage urban planners and managers to protect and develop green networks.

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