Due to the many complexities, housing planning, especially for vulnerable groups, in a city as large as Tehran, requires a model to simplify the process and speed up calculations, which does not currently exist. With the aim of solving this problem, the present study proposes a model with the following steps: 1) Explaining the objectives 2) Estimating the housing needs of the target community 3) Identifying expandable areas 4) Proposing construction patterns 5) Proposing dispersion patterns 6) Calculations and patterns Financial and 7) suggest operating patterns. The information required to implement the model was collected from two questionnaires and data from the Statistics Center. In this model, three housing models with minimum, optimal and average areas and three types of existing housing construction, 100% infrastructure and freeing up the yard space were used as public urban space. The proposed zoning was adapted to the 22 districts of Tehran Municipality due to compliance with the available data. Sales price and financial calculations were calculated based on the internal rate of return of 20% and contract subsidies, and finally 4 free transfer models, lifelong lease, lease on condition of ownership in the program areas were proposed. The results show that one of the problems in this sector is the lack of appropriate decision-making structure and planning tools that can provide a comprehensive and complete review of the current situation, comprehensive and comprehensive solutions. Therefore, according to the model and using the indicators used, regions 2, 6 and 13 have the lowest and regions 19 and 22 have the highest potential for housing development of low-income and vulnerable groups, and finally, the model has suggested the most housing in regions 22, 4, 19 and 11.

Gorgan Bay is considered a geological landscape and a coastal sedimentary environment in the southeast of the Caspian Sea. The hydrodynamics of the coasts of this region is subject to the general hydrodynamics of the Caspian Sea. Due to the low slope topography of these beaches, the slightest change in the sea level will lead to hundreds of meters from place to place in the coastline of this area. Changes in the water level of the Caspian Sea is an environmental and coastal management problem, and today the decreasing trend of the water level of the Caspian Sea during the last few decades has caused destructive effects such as land formation on the coasts of Gorgan Bay. In order to investigate the effect of changes in the level of the Caspian Sea on the southern shores of Gorgan Bay in a period of 66 years, existing reports and studies have been used and field surveys have been used, and the coastlines of the studied area have been monitored through the processing of aerial photos from 1955 and Landsat satellite images. MSS, TM, ETM and +ETM have been carried out in the years 1975-2021 in Arc GIS and ENVI software. Coastal changes were processed during 4 periods. During this period, the level of the Caspian Sea water level fluctuated between -26.5 and -28.7 . Based on the results obtained from satellite images and field visits of Gorgan Bay, 1 stage of water level increase in the period of 1995-1985 by the amount of 131 square kilometers and 3 stages of water level decrease in the years 1955, 1985-1975 and 2021-1995 by the amount of It has covered 246 square kilometers.

In the current situation, artificial intelligence can improve rural management performance through optimizing resource use, predicting environmental changes, and making intelligent decisions.The aim of the present study is to investigating the impact of artificial intelligence on rural management performance with the mediating role of environmental dynamics in rural areas of Kermanshah county. This research is descriptive in terms of method, applied-practical in terms of purpose, and correlational in terms of nature. The statistical population includes 1300 village heads and council members in the villages of Kermanshah city. The sample size using the Morgan table is 297 people and the sampling method is simple random. The research tools include standard questionnaires for artificial intelligence from Carl Albrecht (2003) with 21 items, for measuring environmental dynamics, the Vera and Crossan questionnaire (2009) with 5 items, and for measuring performance, the Patterson questionnaire (1970) with 15 questions. The validity was confirmed by face, content and construct methods and the reliability was confirmed by Cronbach's alpha at 0.861. The collected data were analyzed based on structural equation path analysis in PLS software. The results showed that artificial intelligence had a positive and significant effect on rural management performance with an impact coefficient of 0.889 and a T value of 217.42, artificial intelligence had a positive and significant effect on environmental dynamics with an impact coefficient of 0.876 and a T value of 0.044, and environmental dynamics had a positive and significant effect on rural management performance with an impact coefficient of 0.273 and a T value of 4.938. Also, the results of the Sobel test showed that artificial intelligence had an effect on rural management performance with a mediating role of environmental dynamics with a T value of 9.361. Therefore, artificial intelligence can play a very important role in rural management performance, especially in optimizing resources, improving public services, environmental management and increasing agricultural productivity.

Urban ecological resilience in the Tehran metropolis is one of the most important focuses of urban policy-making due to climatic and environmental challenges. The present research was conducted with the aim of analyzing Tehran's ecological resilience based on regulating ecosystem services and environmental and human variables. To this end, the Multiscale Geographically Weighted Regression (MGWR) model and the eleven-fold City Resilience Index (CLI) were employed.
The results showed that vegetation cover (NDVI), with a positive coefficient and small dispersion, has a uniform and determining effect on the CLI, confirming the importance of greenery in enhancing urban ecological resilience. The per capita green space showed a small positive coefficient, indicating a limited but significant impact on resilience, which suggests its unbalanced distribution across neighborhoods. Geomorphological variables, such as land slope and the rate of land subsidence, showed a consistently negative effect on the CLI. Transportation infrastructures, particularly the distance from the metro and BRT (Bus Rapid Transit), had a positive relationship with the CLI, although this relationship likely reflects population density and economic activities along high-traffic corridors.
In terms of air quality, showed a significant negative effect, while and had a slight positive effect on the CLI; showed no significant impact. Pearson's correlation results indicated no correlation higher than between the variables and the CLI, suggesting the complementary and multi-factorial role of environmental and physical indicators in shaping urban resilience.
In total, the findings suggest that enhancing Tehran’s urban ecological resilience requires a systemic and multi-dimensional approach. Policy-making in this area should focus on inclusive greenery development, redesigning compact urban fabrics, and developing green and sustainable transportation.

Teleconnection patterns play a crucial role in modulating large-scale atmospheric circulation and significantly influence regional climatic variables, including snow cover dynamics. This study aims to examine the impacts of 29 regional and extra-regional teleconnection indices on the spatial and temporal variability of snow cover in the Maroon River basin, a key water-supplying region in southwestern Iran that has experienced severe hydrological extremes in recent decades. Daily snow cover data derived from the MODIS sensor onboard the TERRA satellite for the period 2001–2022 were processed using the Google Earth Engine platform. Snow-covered areas were identified using the Normalized Difference Snow Index (NDSI) with a threshold of 0.4, and the data were aggregated at monthly and cold-season scales. Teleconnection indices—including ENSO-related indices, NAO, PDO, TSA, TNA, EPO, SCA, AAO, and SOLAR—were obtained from the NOAA database. The relationships between snow cover variability and teleconnection patterns were quantified using Pearson correlation analysis, considering both simultaneous and lagged effects.The results indicate that indices such as TSA, EPO, TNA, ESPI, PBO, and OSI exhibit strong negative correlations with snow cover, reflecting suppressed snow accumulation during their positive phases. In contrast, PDO, PNA, MEI.v2, and several Niño indices show significant positive correlations, particularly during the cold season, while the SCA pattern enhances snow cover during spring. Overall, snow cover variability in the Maroon Basin is governed by the combined influence of ocean–atmosphere oscillations and solar activity, with the strongest responses occurring in cold and transitional seasons.These findings highlight the value of integrating teleconnection-based climate signals into snowpack and hydrological forecasting, providing a practical framework for improving water resource management and climate risk assessment in mountainous regions.

“In recent years, the water crisis in Iran has gone beyond an environmental concern and has evolved into a multidimontion issue. Eastern Mazandaran, despite having relatively abundant surface water resources, faces local conflicts over access to and distribution of water between upstream and downstream villages. These conflicts, beyond the mere scarcity of resources, reflect perceived injustice, the breakdown of trust, and transformations in social bonds.This study aims to understand and interpret people’s lived experiences of social conflict over water in this region, using an interpretative phenomenological approach and seeks to analyze the effects of water conflict on perceptions of justice, security, and local identity. Data were collected through in-depth semi-structured interviews with 20 people (15 residents of the villages involved in the water dispute and five technical experts), and analyzed using a three-level thematic analysis. Thematic network analysis was employed, and through a six-step analytical process, a thematic network was constructed.Within this network, fifteen basic themes were condensed into three organizing themes-“Injustice in the flow of water and distrust in relationships,” “Environmental anxiety,” and “Social rupture and collapse of local solidarity”-and one overarching global theme, “Social conflict over water.”These themes indicate that conflict over water serves not only as a source of material disputes but also as a catalyst for profound transformations in the sense of belonging, coexistence ethics, and social trust. Accordingly, the findings highlight the necessity of rethinking water resource management policies, emphasizing perceived justice, inter-village dialogue, and the integration of Sociological and cultural dimensions in adaptation plans for water scarcity.
 

Space is socially produced, and the duality of urban space reflects the multidimensional duality of urban society, posing a major challenge to urban development and spatial justice in metropolitan areas. In Tehran, uneven growth and the concentration of development and urban amenities in specific areas have produced unequal quality of life and a socially stratified urban space. Accordingly, this study examines the spatial manifestations of urban duality in the Tehran metropolis and identifies spatial patterns of inequality across municipal districts. The study adopts a descriptive–analytical approach and covers the 22 municipal districts of Tehran. Data for 45 indicators were obtained from the 2016 National Population and Housing Census and the Statistical Yearbooks of Tehran Municipality (2019–2022). District-level development was evaluated using the CORASO multi-criteria decision-making method, while spatial relationships were analyzed through Moran’s I spatial autocorrelation index. The results reveal a pronounced north–south spatial divide in Tehran. Based on the CORASO scores, northern districts—particularly District 6 (0.25313), District 1 (0.17013), and District 3 (0.12703)—exhibit the highest levels of development, whereas southern districts, especially District 17 (−0.25313), District 10 (−0.23450), and District 18 (−0.22924), are among the least developed. Moran’s I value (0.433510) indicates significant spatial autocorrelation and a clustered spatial pattern, with developed districts forming clusters of prosperity and less developed districts forming clusters of deprivation in southern Tehran. This pattern reflects the historical concentration of resources, services, and investments in northern Tehran and the persistent relative deprivation of its southern districts.
 

This study investigates the impact of ideological cycles and changes in political discourses on the formation and spatial transformation of the Lalehzar–Ferdowsi neighborhood in Tehran during the pre-Constitutional and Constitutional periods. The main objective is to identify the contexts and processes through which traditional and modern discourses shaped the spatial and physical structure of this neighborhood. The research is qualitative and exploratory in nature and adopts a historical–analytical approach. Data were collected through documentary sources, including historical documents, maps, official reports, and written records, and were analyzed using a spatial discourse analysis framework. The findings suggest that the emergence and development of the Lalehzar–Ferdowsi neighborhood during the Qajar period were a result of the interaction between two dominant discourses: the traditional discourse of the pre-Constitutional era and the modern discourse of modernization during the Constitutional period. The spatial manifestations of these political discourses materialized through the establishment of various institutions and structures such as the Fārūs Printing House as a symbol of freedom of expression, the formation of the Nazmiyeh and the police as indicators of the rule of law, embassies and state institutions as expressions of state–nation relations, and facilities such as the telegraph office, bank, post, park, and modern streets as signs of modernization. Accordingly, the simultaneous and sometimes conflicting forces of tradition and modernity generated the initial physical form, functional structure, and modern urban identity of the Lalehzar–Ferdowsi neighborhood.