Housing is a fundamental human necessity, shaping health, security and socio-economic well-being. The government of Iran has implemented various policies, plans and projects to ensure housing provision, but significant challenges remain, particularly in social housing. This study aims to identify and analyse the obstacles affecting the future development of social housing in Iran. Utilising a mixed-method approach, we conducted both quantitative and qualitative research, gathering expert insights through the Delphi method and analysing the data using cross-impact analysis via MICMAC software. The results revealed four critical challenges: limited loan repayment ability, currency instability, social issues within low-income communities, and policy isolation. These findings underscore the need for policymakers to adopt a comprehensive strategy that addresses financial, social and political fragmentation to ensure sustainable and equitable access to social housing for low-income residents.

Although numerous studies have been conducted to discover the spatial patterns of road crashes, relatively few have focused on the patterns of road crashes suffered by socially disadvantaged groups, while simultaneously accounting for urban environmental features. This study used advanced econometric (negative binomial regression) and spatial (geographically weighted Poisson regression) approaches to capture latent geographical diversity in crash patterns. The police-reported crash data for the over-65 population in metropolitan Adelaide, Australia, were investigated for two periods: before and after COVID-19. Using both spatial and nonspatial models, the effects of land use mix, population density, road network design, distance to the central business district, and accessibility of public transit on crash frequency, and location at the neighborhood level were investigated. The findings revealed that, in addition to sociodemographic factors, the aforementioned components had nonlinear effects in varied geographical contexts. Although the number of crashes fell by 20% during the periods studied, the fundamental reasons for such incidents did not change. The results of the study could assist academics and policy makers in Australia to better understand the multidimensional implications of the built environment on the road safety of the elderly—a vulnerable group in society who were disproportionately affected by the global pandemic. The hybrid technique presented in this research has the potential to be useful in other scenarios experiencing varying crash patterns.

Urban sprawl poses a significant and escalating challenge in developing countries, including Iran, leading to substantial transformations in urban areas. Despite efforts to manage urban spatial development, uncontrolled urban sprawl exerts considerable pressure on resources, infrastructure, and the environment. This study aims to identify and quantify the drivers of urban sprawl and investigate their interrelationships within Iranian metropolises. To achieve this objective, the study employs a mixed-method approach, commencing with a review of the existing literature and expert surveys based on PESTEL analysis and the Delphi method. This stage identified and categorized 40 key drivers (sub-factors) into six main categories (factors): political, economic, social, technological, environmental, and legal. Subsequently, the DEMATEL-based Analytic Network Process (DANP) method is utilized to explore the internal interrelationships among factors and sub-factors and to determine their relative weights, offering deeper insights into their relationships and relative importance. The findings reveal a complex interplay of political, economic, social, technological, environmental, and legal factors driving urban sprawl in Iran. Key drivers include political fragmentation, economic competition, social preferences for suburban living, rural-to-urban migration, increasing housing demand, weak legal regulations, natural constraints, inadequate transportation infrastructure, and the impact of technological advancements. Based on these findings, the study recommends a holistic approach to sustainable urban development in Iran, emphasizing the need for stakeholder engagement, participatory decision making, legal reforms, and significant investments in public transportation infrastructure.

The rapid expansion of urban areas has led to significant land use changes, affecting local climate systems, particularly through an increase in Land Surface Temperature. This study investigates the spatio-temporal dynamics of Urban Land Use Changes, and its impact on temperature patterns, using Landsat imagry and advanced GIS techniques to analyze changes in LST over 10 years in Sari, Iran. The results indicate 3 °C increase in average LST over 10 years, with maximum temperatures rising from 53 °C to 56 °C. A clear gradient in LST was observed, with areas closer to the spots with land use change experiencing more temperature increase in the temperature. The further distance to transportation infrastructure showed the strongest cooling effect, with proximity reducing LST significantly. Conversely, increased distance to gardens and green infrastructure were associated with higher LST. These findings emphasize the critical role of land use transformation in mitigating or worsening urban surface tempreature.