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This paper aims to reveal the shortcomings of the land use efficiency assessment formula presented in SDG 11.3.1 Indicator and develop a framework that can provide urban planners with a more accurate understanding of the variables influencing and/or influenced by urban expansion. Based on the mentioned formula, Tehran never experienced urban shrinkage between 1986 and 2021, as shown by the relationship between land consumption and population growth. However, the research findings indicate that land allocation patterns have not only decreased most urban services per capita, but have also undermined ecosystem services during this period. In this paper, we propose a new assessment framework by which a dual aspect of urban planning is addressed, namely providing sustainable urban services while protecting natural resources, and using ecosystem services sustainably to support cost–beneficial urbanization. For this purpose, a total of ten mainly repeated contributing variables were collected in the categories of environmental, physical-spatial, and economic–social effects of urban expansion. A questionnaire based on these variables was prepared, and 14 urban planning experts collaborated to classify the variables and identify causal relationships between them. In the following, data obtained from the questionnaires were analyzed using DEMATEL and Interpretive Structural Modeling (ISM) methods to determine which variables influence and/or are influenced by urban expansion (and to what extent). Third-level variables that directly influence urban expansion include transportation (A6), infill development (A7), and entrepreneurship (A10). Spatial justice (A8) and housing and population attraction (A9) were identified as middle-level variables that both affect and are affected by urban expansion. Finally, land surface temperature (A1), air pollution (A2), sewage and waste (A3), water resources (A4), and vegetation (A5) were identified as first-level variables that are mainly affected by urban expansion.

The upward trajectory of urbanization, coupled with the ever-growing demand for more water resources, has led to increased pressure on limited water resources, particularly in cities with dry climates such as Tehran. Since the balance of Tehran’s water ecosystems has been disturbed, and the quality and quantity of water resources have been affected in recent years, conducting an assessment of water environment carrying capacity (WECC) seemed vital for this city. WECC was used as the basis of water supply sustainability evaluation concerning Tehran’s land use and demographic characteristics on a neighborhood scale. Therefore, the effect size and correlation of 12 types of land use and six variables derived from the literature with water consumption patterns were examined in warm and cold seasons. The results show that land use, population density, percentage of deteriorated area, percentage of buildings over 30 years old, residential–commercial land use, and green spaces correlate significantly with water consumption. The percentage of deteriorated areas and buildings over 30 years old has a negative, and the rest has a positive impact on water consumption. It is also recommended to use the research findings to improve Tehran’s water environment carrying capacity and apply the proposed evaluation procedure to other cities. The results of this research can be used in planning large and densely populated cities with a neighborhood-oriented approach, in which local institutions play an essential role in attracting people’s participation and inclusive urban planning.

This study aimed to develop a balanced-based assessment framework to evaluate the effectiveness of Neighborhood Development Offices’ (NDOs) actions in improving the resilience of Tehran’s deteriorated neighborhoods against the COVID-19 pandemic. For this purpose, considering the main missions of NDOs, 20 indicators were extracted from the literature and delivered to the offices and residents of target neighborhoods to prioritize them. Next, using a combination of the K-means clustering method and the balance-based conceptual model, the degree of balance between the measures taken by NDOs and residents’ needs in each neighborhood was determined. Finally, short-term actions (such as teaching health protocols, providing neighborhood services, and providing walking and cycling infrastructures) and long-term actions (developing public spaces, facilitating access to healthcare, and reducing social inequality) are suggested, which simultaneously promote balanced resilience against the COVID-19 pandemic and possible future pandemics in all aspects of NDOs’ missions. The framework presented in this research can also be used to evaluate and boost the resilience of other deteriorated neighborhoods with similar conditions.