https://geoplanning.tabrizu.ac.ir/ Journal of Geography and Planning en daily 1 Sat, 19 Jul 2025 00:00:00 +0330 Sat, 19 Jul 2025 00:00:00 +0330 https://geoplanning.tabrizu.ac.ir/article_20100.html Objective: This study was conducted to forecast precipitation at 5 synoptic meteorological stations located in the Caspian region of Iran in the next three decades. Research Method: Data from three AOGCM models (INM-CM5-0, CMCC-CM2-SR5, BCC-CSM2-MR) from the CMIP6 series of models were used under two scenarios SSP2-4.5 (moderate) and SSP5-8.5 (pessimistic). The observation period was 1985-2014 and the future period was 2030-2059. The raw precipitation output was downscaled by CMHyd software. To reduce uncertainty with the weighted averaging method (based on rank), the ensemble model was calculated. Resultss: The results showed that the generated ensemble model has better performance than the best single model of each station. In January, March, May, June, July and August, the average amount of precipitation changes in the average and pessimistic scenarios will be decreasing compared to the base period. In February, the average amount of precipitation changes in the moderate and pessimistic scenarios will be increasing compared to the observation period. In April, the average amount of precipitation changes in the two scenarios will be increasing compared to the base period in the moderate scenario and unchanged in the pessimistic scenario. Based on the uncertainty diagram drawn for the Rasht synoptic station under the two scenarios SSP245 and SSP585, in both scenarios, the amount of uncertainty has increased with distance from the observation period, and the increase in the uncertainty range has intensified from the 2040s onwards. Conclusion: The results showed that the maximum change in monthly precipitation decrease in the future period compared to the previous period will occur in June with a value of 35%. Except for February, in all months, the amount of precipitation changes in the future period compared to the past is greater in the average scenario than in the pessimistic scenario. https://geoplanning.tabrizu.ac.ir/article_20315.html Objective: The aim of the present study is to investigate the changes in different land uses and evaluate the effects of land use changes on landslides in Namin County.Methods: . In order to achieve the objectives of this research, first a land use map was prepared using the object-oriented method for the two periods of 2002 and 2024. In the next step, information layers of other effective factors for landslides in the city were prepared in the GIS environment. The evaluation and standardization of the layers were carried out using the fuzzy membership function and weighting of the criteria, using the CRITIC method. The final analysis and modeling was performed using the ARAS multi-criteria algorithm.Results: .The results of this study showed that the largest area in 2002 was related to poor pastures and rainfed agriculture, with 493.71 and 209.91 square kilometers, respectively, and in 2024, it was related to poor pastures and rainfed pastures with 422.62 and 271.93 square kilometers, respectively. According to the 2002 landslide zoning map, 15.15 and 22.46 percent of the county's area are in the very high and high-risk categories, respectively, and according to the 2024 landslide zoning, 15.92 and 26.04 percent of the county's area are in the very high-risk and high-risk categories, respectively.Conclusions: .In general, it can be said that the main reasons for the increase in the number of landslides in Namin Shib County are slope, land use change and human intervention through land use change, vegetation destruction, overgrazing, release of irrigation water at the end of agricultural lands, and road construction . https://geoplanning.tabrizu.ac.ir/article_20353.html Mazandaran Province, due to its unique climatic conditions and extensive agricultural and industrial activities, is considered one of the potential hotspots for methane (CH₄) emissions in Iran. This study aims to examine the correlation between various atmospheric climatic elements—including temperature, relative humidity, wind speed and direction, precipitation, and air pressure—and the temporal distribution of methane pollution in the province. To achieve this, Sentinel-5P satellite data and meteorological observations from regional stations were collected and analyzed over the period from 2018 to 2024. Pearson correlation and multiple regression methods were employed to assess the relationships among variables. The linear trend analysis of methane concentrations from 2019 to 2024 across different cities in Mazandaran revealed a general upward trend in methane levels, indicating a gradual increase over time. The findings highlight that climatic factors such as aerosols, temperature, and solar radiation play a central role in the variation of atmospheric methane concentrations, whereas parameters like wind speed, atmospheric pressure, and heat flux exert relatively minor influences. Moreover, results from the multivariate regression analysis identified aerosols, longwave radiation, and wind as significant predictors of methane concentrations in the province. These insights can contribute to identifying spatial and temporal patterns of methane distribution and support the development of strategic management approaches aimed at reducing methane emissions in Mazandaran Province. https://geoplanning.tabrizu.ac.ir/article_20374.html Flood frequency analysis and statistical modeling of peak discharge are essential for water resource management, hydraulic structure design, and flood hazard mitigation in semi-arid regions. This study analyzes the peak flood discharge of the Qareh-Aghaj River in the Tang-e-Karzin catchment, employing multiple probability distributions, including Gumbel Type 1, 2-parameter Gamma, 2- and 3-parameter Log-Normal, Generalized Pareto, Generalized Extreme Value (GEV), and Pearson Type 3. Parameters were estimated using methods of moments (MOM), maximum likelihood (MML), probability-weighted moments (PWM), and maximum entropy (ENT). To assess uncertainty in peak discharge predictions for return periods of 2 to 1,000 years, non-parametric bootstrapping with 1,000 random samples was applied. Peak discharge data were evaluated using foundational statistical tests: the runs test (z=0.025), Grubbs-Beck test (indicating an extreme flood event), Wald-Wolfowitz test (u=0.896), and Mann-Whitney test (p-value=0.6625), confirming data randomness, independence, and homogeneity. The Kolmogorov-Smirnov (K-S) test assessed goodness-of-fit, with the 2-parameter Log-Normal (K-S=0.089) and GEV (K-S=0.063, peak discharge 11,044.6 m³/s for a 1,000-year return period) distributions demonstrating superior performance. Bootstrapping generated 95% confidence intervals, reducing prediction uncertainty, particularly for these distributions. Comparisons using K-S and Anderson-Darling (A-D) criteria further confirmed their superiority. The findings validate bootstrapping as an effective tool for enhancing hydrological predictions and provide recommendations for designing flood-resilient structures and optimizing water resource management in the Tang-e-Karzin catchment. These results offer a foundation for flood management, hydraulic structure design, and water resource planning in this catchment and similar semi-arid regions. https://geoplanning.tabrizu.ac.ir/article_20375.html This research aimed to conduct a critical analysis of the regional planning system in East Azerbaijan Province with a future-oriented approach. In terms of its objective, the research is applied, and in terms of its nature and method, it is a combination of quantitative and qualitative models, conducted using the cross-impact analysis and scenario planning methods with the help of the MICMAC and Scenario Wizard software. This research sought to identify key drivers and analyze the interactions of various variables in the regional planning system of the province, and using qualitative data collected through open-ended questionnaires and expert interviews, it conducted structural analysis and future-oriented analysis. In the analysis process, 43 variables were identified as key factors and were examined using the MICMAC software. The results indicate complex interactions and cross-impacts among these factors, with high and significant impacts observed in some cases, especially in direct and indirect effects. The analyses also showed that a number of factors have strong and significant impacts in the system, which can play a pivotal role in strategic planning processes and scenario development. Based on these analyses, key drivers and factors influencing the development of regional planning in East Azerbaijan Province have been identified, which can be effective in policy-making and strategic interventions to improve the regional planning system. In total, eight key drivers were identified for the regional planning approach, and according to the matrix of direct and indirect potential impact and dependence, the variable "non-use and exploitation of local capacities for local, regional, and national development" ranked first in terms of direct and indirect impact and had the greatest share in their failure. These results can serve as a basis for future decision-making in optimizing the regional planning structure. https://geoplanning.tabrizu.ac.ir/article_20502.html This study investigates temporal trends and projects future electricity consumption patterns across diverse urban sectors (residential, industrial, agricultural, public, street lighting, and miscellaneous) in Tabriz, a city characterized by a cold semi-arid climate. Biannual electricity consumption data, spanning 2008–2023, were sourced from the Tabriz Electricity Distribution Company and disaggregated by sector. Trend analysis was performed using the Mann-Kendall test, with inter-sectoral relationships evaluated via Spearman’s rank correlation coefficient. Forecasting until 2031 was conducted using a Neural Network Autoregressive (NNAR) model. Time-series analyses incorporated Augmented Dickey-Fuller (ADF) and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) stationarity tests, Seasonal-Trend decomposition using Loess (STL), Box-Cox transformation, and model accuracy assessment through Root Mean Square Error (RMSE), Mean Squared Error (MSE), and Mean Absolute Error (MAE). All sectors exhibited statistically significant upward trends in electricity consumption. The most pronounced trends were observed in the miscellaneous (τ=0.572) and aggregate (τ=0.570) categories, with substantial increases in residential (τ=0.496) and industrial (τ=0.500) sectors. Spearman’s correlation revealed strong associations between residential, industrial, and miscellaneous sectors with total consumption (ρ≥0.91). Residential consumption displayed marked seasonal variability, with peak demand during July–August and January–February, indicative of climatic influences. The NNAR model demonstrated robust predictive accuracy across all sectors (RMSE<6%). Despite consistent consumption growth across sectors from 2008 to 2023, projections indicate relative declines by 2031 in residential (2.3%), agricultural (2.14%), and street lighting (5.61%) sectors, potentially attributable to recurrent power outages impacting model inputs. These findings advocate for energy policies in Tabriz prioritizing suppressed demand management, grid resilience enhancement, and tailored seasonal and sectoral strategies. The integration of the NNAR model, Mann-Kendall test, and a data-driven framework for energy policy formulation in semi-arid climates constitutes a novel contribution, offering actionable insights for sustainable urban energy management. https://geoplanning.tabrizu.ac.ir/article_20527.html In recent years, the vulnerability of Iran's big cities has increased against unexpected incidents and accidents, and in contrast to the low level of resilience, human life has been endangered in these cities. Based on this, the aim of this article is to analyze urban resilience using a combination of fuzzy model and machine learning in Tabriz city as a metropolis in the northwestern region of the country. This research is applied-developmental in terms of purpose, descriptive-analytical in terms of method. which are three physical, social and natural components with 41 effective indicators in urban resilience, which were compiled and compiled based on questioning and examining various sources. Then, preparing the maps of each variable and creating fuzzy layers using the fuzzy neural network model in the Idris Terrset software environment, the resilience of Tabriz city was determined. Validation with the help of ROC curve is equal to 0.856, which shows a very good result. According to the obtained results, About 10 percent of the area of Tabriz city is in dangerous conditions in terms of resilience, while 36 percent of the total city area has a high level of flexibility. Ultimately, separate recommendations were presented based on the resilience conditions and land uses.Key words: urban resilience - fuzzy model - learning machine - Tabriz https://geoplanning.tabrizu.ac.ir/article_20563.html Historical urban fabrics, as an essential part of the cultural identity of any society,represent valuable architectural and urban heritage. These fabrics not only reflect the history and pest civilizations but also play a crucial role in sustainable urban development and the preservation of cultural values. However, the gradual deterioration of these fabrics over. different historical periods has raised an alam for urban authorities and planners, highlighting the need for their sustainable regeneration and preservation. Therefore. integrated and sustainable regeneration of historical urban fabrics has become one of the main priorities in urban policy-making in many metropolises, particularly in Tabriz. This study was designed and conducted with the goal of identifying the challenges and obstacles in achieving this important objective, as well as proposing appropriate strategies to improve the current condition of Tabrizs historical fabric. To this end, a mixed-method research approach (quantitative-qualitativej, of a developmental-applied nature with an exploratory. analysis, was employed to carefully examine various dimensions of the issue. The data were analyzed using the Q factor analysis model and the one-sample t-test in SPSS software. The statistical population included urben managers, experts, and academic elites, from which a sample of 20 individuals was selected using the Delphi method. The research findings reveal that five main factors play a critical role in the failure of historical fabric regeneration inTabriz: Lack of integrated management, Ineffectiveness of plans, Lack of coordination and effective participation, Weakness in institutional capacity-building and Neglect of knowledge-based approaches. A significant portion of the problems stems from these key factors. Furthermore, an analysis of the sustainability and integration indicators of the regeneration system shows an unfavorable condition that requires serious revision. These finding highlight the importance of developing practical strategies to improve the management and planning of historical fabric regeneration https://geoplanning.tabrizu.ac.ir/article_20617.html This study examines the impact of adaptive capacity on the livability of rural households in drought conditions. The statistical population comprises rural households in Bavi County, Khuzestan Province. Based on the Krejcie and Morgan table, a sample size of 347 household heads was selected using systematic random sampling. The primary research instrument was a structured questionnaire, whose reliability was confirmed by Cronbach's alpha coefficient and validity by a panel of experts. Data analysis was conducted using SPSS, GIS, and Smart PLS software. The findings reveal that 83.27% of households exhibit low to moderate levels of adaptation, with the rural districts of Mollasani and Weis demonstrating the highest adaptive capacity under drought conditions. Additionally, results indicate that the studied rural households do not possess an adequate level of livability, as 75.51% fall within the medium-to-low livability range. Structural equation modeling further demonstrates that the dimensions of the sustainable livelihood model—human, financial, social, natural, and physical capitals—have a significant positive effect on household livability, collectively explaining 59.7% of the variance. These insights highlight the essential role of adaptive capacity in enhancing the resilience and sustainability of rural communities affected by drought. The study underscores the necessity of targeted interventions aimed at strengthening livelihood assets to improve the living conditions of vulnerable households. https://geoplanning.tabrizu.ac.ir/article_20734.html Urban sustainability, as one of the fundamental concepts in urban planning, plays a key role in improving the quality of life of citizens and is directly related to social, economic, physical, cultural and technological dimensions. Therefore, the present study was conducted with the aim of analyzing the sustainability of Behbahan's urban space from the perspective of creative city indicators.The research type is applied in terms of purpose and descriptive-analytical in terms of method. The data collection tool included library and field studies (questionnaires). The statistical population of the research consisted of citizens of Behbahan city, and based on the Cochran formula, 400 people were selected as the sample size by simple random sampling. Data analysis was performed using SPSS and AMOS software and using statistical tests such as one-sample T, Pearson correlation, and structural equation modeling.The results of the data showed that the status of Behbahan's urban space is at an undesirable level from the perspective of creative city indicators. In particular, the urban diversity, efficiency and effectiveness, and participation indicators have achieved the lowest average. Also, based on the findings of structural equation modeling, the efficiency and effectiveness index with a factor load of 0.91 and participation with a factor load of 0.74 have had the greatest impact on the sustainability of urban space.Therefore, the results of this study indicate that weakness in participatory planning, lack of smart communication infrastructure, and lack of attention to socio-cultural needs, etc. are among the factors affecting the decrease in the sustainability of Behbahan's urban spaces. As a result, it is essential for urban managers and planners to adopt comprehensive and sustainable policies in cultural, physical, and managerial dimensions in order to promote the indicators of the creative city in order to move towards the sustainability of Behbahan's urban space. https://geoplanning.tabrizu.ac.ir/article_20767.html Objective: This study investigated the spatial distribution of hot and dry weather events across Iran from 1986 to 2023. Methods: Hourly temperature and relative humidity data from 31 synoptic stations were analyzed. Synoptic patterns associated with hot and dry conditions were identified using NCEP/NCAR reanalysis data at four pressure levels (surface, 850, 700, and 500 hPa). To validate the observational findings, land surface temperature (LST) products derived from the MODIS sensor onboard the Aqua satellite were employed. The HYSPLIT model was also applied to trace the source and trajectory of the air masses contributing to the hot and dry conditions. Moreover, factor analysis and principal component analysis (PCA) were conducted to determine the underlying drivers and dominant components influencing the intensity and frequency of hot and dry weather events in this region. Results: The analysis showed that hot and dry weather events (HDWEs) were most intense in the eastern and southwestern regions of Iran, especially Khuzestan Province, whereas coastal and mountainous areas experienced milder conditions owing to the moderating effects of the Caspian Sea and Persian Gulf. The highest temperatures and lowest relative humidity occurred at approximately 12:00 UTC. Synoptic and trajectory analyses indicated that the subtropical high-pressure ridge dominated most of Iran, and hot and dry air masses originated from both domestic and external sources. Conclusions: Overall, HDWEs in Iran are primarily controlled by the interactions among topography, surface moisture, and large-scale circulation patterns. Factor and principal component analyses confirmed that thermal and moisture gradients, geographical position, and seasonal variability are key drivers of Iran’s hot and dry climate regime. These findings enhance our understanding of the atmospheric dynamics influencing HDWEs and provide a foundation for improving regional climate prediction and adaptation planning. https://geoplanning.tabrizu.ac.ir/article_20768.html In the 1987 Brundtland Commission Report, the concept of "sustainability" was introduced, which has since become the cornerstone of international and national efforts in the field of the environment. While this idea is not new, it highlights growing concerns about the effects of urbanization. This research addresses the question of what norms can guide the studied urban space toward sustainable development. The goal is to identify the norms influencing sustainable development in Amol city, with a focus on endogenous development, and to propose strategies for improving local development.Initially, 60 factors influencing sustainable urban spaces were identified through library resources. These factors were then presented to 10 experts for evaluating their face and content validity. In the next stage, a questionnaire based on a fuzzy cognitive map approach, including 30 key influential factors, was designed and presented to 18 other experts. Finally, the data were analyzed using FCMAPPER software and Excel.The findings indicate that three main concepts have the greatest impact: attention to environmental balance, the government-led nature of urban policy and planning processes, and the traditional budgeting of municipalities. Additionally, three other concepts—attention to environmental balance, appropriate building density in plots, and appropriate density relative to street width—showed the greatest influence. The conclusion is that attention to environmental balance holds the highest centrality among the key factors for sustainable urban spaces in the city of Amol. https://geoplanning.tabrizu.ac.ir/article_20769.html This research was conducted with the aim of investigating and analyzing the climatic factors affecting architectural design in mountainous regions, focusing on the city of Sanandaj. In this study, standard EnergyPlus Weather (EPW) climate data were utilized over a 14-year period (2009 to 2023). The research methodology was based on the parametric analysis of hourly climate data in accordance with ASHRAE Standard 55 and the utilization of the Predicted Mean Vote (PMV) model for thermal comfort assessment. Meteorological parameters (air temperature, soil temperature, dew point temperature, humidity, wind speed and direction, and solar radiation) were analyzed using Climate Consultant software, and the results were presented in the form of bar, line, and scatter plots. The results indicated that the climate of Sanandaj, with its hot summers and cold winters, necessitates specific strategies in architectural design. The cold months of the year (January, February, November, and December) require heating systems, while the hot months (July and August) require cooling systems. Additionally, the months of March, April, and October, with the highest wind speeds, have the potential for natural ventilation. Based on the research findings, strategies such as the use of high thermal mass materials, passive solar systems, proper insulation, night ventilation, and adjustable shading devices are proposed. These strategies can help optimize energy consumption and provide thermal comfort for residents in the mountainous climate of Sanandaj. https://geoplanning.tabrizu.ac.ir/article_20784.html Objective: Considering the negative effects of tourism, a large part of which is related to tourists, slow tourism can be used to reduce some of these effects. In this regard, the present study examines the willingness of the local community to develop slow tourism in the villages of Sangar district of Rasht. Methods: This study was conducted based on the applied objective, in terms of descriptive survey method and using the field study method with a researcher-made questionnaire. The statistical population is the residents and also the village heads of the villages of Sangar district of Rasht , . After collecting the data, they were analyzed using the relevant tests.Results: The results of this study showed that the attitude of the host community towards the development of slow tourism is positive. The results of the chi-square test for the indicators under study showed that it has an above-average status at a 95% confidence level. Also, according to the binomial test, the majority of respondents had a tendency to be more than average in all indicators.Conclusions:The results of this study show that by addressing existing barriers and improving the quality of services, there is a possibility of developing slow tourism in the villages of Sangar district. However, there is a need to improve public infrastructure, waste management, and also develop educational programs for local residents and tourists. https://geoplanning.tabrizu.ac.ir/article_20872.html Landslides are one of the natural hazards in the world . Landslides are the displacement of rocks, debris, or soil due to the Earth's gravity . The current research is is of an applied type and its research method is an analysis based on the integration of data analysis, geographic information system (GIS) and the use of MARCOS multi-criteria analysis techniques. According to the weights of each criterion obtained from the critical method and also the scores obtained from the output of the Marcus method, among the various factors affecting the landslide of the Onarchay-Meshkinshahr watershed, the slope, land use, lithology and geology factors were ranked first to fourth with higher scores. In addition, the altitude classes, precipitation, vegetation cover, distance from the river, soil type, distance from roads, slope direction and distance from fault were assigned scores between 5 and 12, respectively. Therefore, the final map was arranged in 5 classes: very low, low, medium, high and very high. The central, western and eastern parts of the region have a high potential for landslide occurrence. The northern side of the map had the least landslides due to the plain and low and flat lands. https://geoplanning.tabrizu.ac.ir/article_20912.html The geographical location of Ardabil province is between 37 and 45 to 39 and 49 north latitude and 47 degrees and 30 minutes to 48 and 55 east longitude. The purpose of this research is to identify and analyze the geotourism potentials of Ardabil province for economic development. The study method is descriptive, analytical, and comparative, and in order to evaluate geosites, three evaluation methods of Kobalikova, Hadzik, and Violett geotourism have been used. In Kobalikova's method, the criteria are placed in five groups. It covers almost all the features of geotourism. The value of each criterion in this model varies between zero and one (0-1). In the Violet method, geomorphosites and landforms were selected for study and evaluation based on four criteria: origin of formation, geographical distribution, tourism, and general accessibility of this national park. The overall assessment of geotourism and geomorphosites in this method is based on two main rates. In the Hadzik model, the value and importance of each geotourism site is estimated by the scientific value indices and the surplus values of that geotourism site. A study of the geotourism indicators of the regions shows that the Sarein region, with a score of 14.7 in terms of the Kobalikwa model, has the highest score in terms of scientific and educational value indicators and other indicators studied. The results of the Hadzik model also showed that the Sarein city, with a score of 44.91, has a higher rank than other studied regions in terms of surplus value indicators. The results of the Feyolt model calculations also show that Sarein County has obtained the highest score of 7.51 according to the evaluation of tourist value indicators, followed by Meshginshahr with a score of 7.23 and Hir with a score of 12.6, in second and third place, respectively. https://geoplanning.tabrizu.ac.ir/article_20913.html Objective: Geomorphosites are defined as parts of the Earth that have special geological or geomorphological significance that have acquired scientific, cultural-historical, aesthetic, or socio-economic value due to human understanding or exploitation. The aim of the present study is to identify and evaluate karst geomorphosites in Zanjan province using the Nicholas and Facilus models.Methods: The method of this study is descriptive-analytical-applied and to evaluate the study areas, the Nickolas model, which examines geomorphosites in three criteria: scientific and educational value, potential threats, and conservation needs and usability, and the Fassoulas model, which evaluates geosites using scientific, tourism, and conservation value criteria, were used.Results: The results show that in the Nickolas model, the karst geomorphosite of Katalekhor Cave has the highest score and has the highest geotourism value with a total score of 5.67; the geosites of Mount Panjeh Ali and Cheshmeh Karsef are in the next ranks with a score of 5.54 and 5.52, respectively. Also, according to the results of the fassoulas model, Katalekhor Cave has the highest geotourism potential in the region with a score of 5.147, and Dodkash Jen is in the second place with a score of 5.127 and Cheshmeh Karsef is in the next place with a score of 120.Conclusions: Therefore, it is concluded that among the studied karst areas, the geomorphosites of Katalekhor Cave, Cheshmeh Karsef and Dodkash Jen and Mount Panjeh Ali are introduced as the top geomorphosites of the region with potential geotourism potential. Finally, it is suggested that future studies use artificial intelligence tools and modern geotourism models to identify the geotourism potential of regions and attract domestic and foreign tourists. https://geoplanning.tabrizu.ac.ir/article_20914.html هدف برق خورشیدی کاملاً بر انرژی تابشی خورشید متکی است که یک منبع بی‌پایان و تجدیدپذیر محسوب می‌شود. پنل‌های خورشیدی از سلول‌های فتوولتائیک تشکیل شده‌اند که انرژی تابشی خورشید را به جریان برق مستقیم تبدیل می‌کنند. این سلول‌ها معمولاً از موادی مانند سیلیکون ساخته می‌شوند که دارای خواص الکتریکی خاصی هستند. زمانی که نور خورشید به سلول‌های خورشیدی می‌تابد، فوتون‌های نور باعث ایجاد جریان الکتریکی در سلول‌ها می‌شوند و این جریان به برق مستقیم تبدیل می‌شود. روش پژوهش جهت پردازش از تصاویر ماهواره لندست در سال 2024 و روش کار بر پایه مدل بسیار دقیق سبال صورت گرفت. و تمامی پردازش‌ها در نرم‌افزار ENVI انجام شد. نتایج حاصل نشان می‌دهد که میانگین بیشترین تابش موج کوتاه ورودی به میزان 846 وات بر مترمربع در ماه آگوست و کمترین مقدار در ماه فوریه به میزان 313 وات بر مترمربع بوده است. تفاوت در مقدار تابش خالص رسیده به زمین در منطقه مورد مطالعه، ناشی از تفاوت زاویه تابش خورشید و تعداد ساعات آفتابی در ماه‌های مختلف سال است. در نهایت می‌توان نتیجه گرفت که تابش خورشیدی در منطقه، در سال مورد بررسی پتانسیل لازم برای اجرای طرح‌های فتوولتائیک خورشیدی را دارا می‌باشد.نتیجه‌گیری توزیع متفاوت تابش خورشیدی در محدوده 313 تا 846 وات بر متر مربع متغیر بوده است، از میزان تابش دریافتی و بازتابی که علاوه بر قابلیت بسیار زیاد برای تامین برق شهرستان رامسر یک منبع بسیاد مناسبی برای تغذیه توزیع برق در استان مازنداران باشد. نوآوری در این تحقیق استفاده از تصاویر ماهواره‌ای به صورت دوره‌ای و فصلی که این موضوع باعث می‌شود از مطالعاتی مشابه که پتانسیل‌سنجی را فقط براساس پارامترها وزن‌ها می ستنجند، هم به لحاظ دقت و هم صحت بسیار دقیق و قابل استناد باشد. https://geoplanning.tabrizu.ac.ir/article_20991.html One of the hazards that has occurred in many regions in recent years is landslide hazards. Identifying areas prone to landslides and estimating their rates plays an important role in managing and controlling this hazard. Radar interferometry is an efficient method for measuring ground surface displacement. This technology allows continuous monitoring of small ground surface movements with high accuracy and over a wide range. This technology has become very popular in the study of natural ground hazards, including landslides, subsidence, earthquakes, and volcanic activity. This technique compares the phase taken from two radar data sets at two different times and, by creating an interferogram, is able to measure changes in the ground surface over time. In this study, Sentinel 1 radar images from 2016 and 2024 were used to estimate and identify the amplitude movements. And the SARSCAPE software was used to process the information. During the study period, the maximum amount of slope material displacement was 34 cm, indicating that the region is active in terms of slope movements. The results of this study showed that radar images have good potential for detecting slope instability and calculating their displacement. https://geoplanning.tabrizu.ac.ir/article_21053.html Objective:The present study was to investigate the variables of desirable urban management in the Tehran metropolis using the cognitive mapping approach. It is applied in terms of purpose and descriptive in terms of data collection.Research Method: In this study, 15 professors, experts, and specialists in the field of urban management in the Tehran metropolis were considered as research samples, and the sample selection method was purposeful and snowball.To identify the factors, first, theoretical foundations and backgrounds were examined, then interviews were conducted with experts, and content analysis was used. The average of experts' opinions on fuzzy logic was used to screen the data. A questionnaire with a matrix structure was prepared to discover causal relationships between factors, and the result led to a model.Findings: The findings of nonparametric correlation tests showed that since the significance of the tests is greater than 0.05, there is no significant relationship with a probability of 95% between the experts' expertise indices and the complexity indices of the cognitive maps. Also, based on the results of the correlation method of the second-order assignment procedure, it was found that at this level of confidence between the cognitive maps, in addition to the analysis result of the significance level of 0.05, there is a significant linear correlation between the experts. A cluster based on the specified similarity data is created; that is, the personal characteristics of the experts' membership in different organizations could not create a significant difference between the maps of the experts.Conclusion: Based on the research, it was determined that strong relationships are seen between variables such as "urban future planning", citizen participation", "informal relations" and "intra-urban spatial justice", while "quality of civil society" and "citizen satisfaction" (in some cases) as well as "integrated management" (with some variables) show less relationships. https://geoplanning.tabrizu.ac.ir/article_21054.html The aim of the present study is to analyze the relationship between vegetation indices and soil erosion using the RUSLE model in the Firozabad watershed, Ardabil Province. For this purpose, Sentinel-2 satellite images from 2024 were employed, and six vegetation indices, including NDVI, SAVI, MSAVI, EVI, GNDVI, and VARI, were extracted. These indices were calculated using Google Earth Engine and ArcGIS, and their spatial maps were generated. At the same time, the RUSLE model was applied to estimate soil erosion intensity. Subsequently, by overlaying the layers, a soil erosion map at the watershed scale was prepared. Furthermore, in order to analyze the correlation between vegetation indices and soil erosion intensity, Pearson’s correlation and linear regression analysis were conducted in SPSS software. The results showed that soil erosion values across the watershed ranged between 2.46 and 98.73 tons per hectare per year. Pearson’s correlation analysis indicated that soil erosion had the highest positive and significant correlation with NDVI and EVI (0.38). The MSAVI and VARI indices also showed positive and significant correlations with values of 0.29 and 0.26, respectively, while SAVI demonstrated a negative and significant correlation with a value of –0.22. This pattern suggests that increasing greenness, as measured by NDVI and EVI, contrary to initial expectations, was associated with increased soil erosion. In contrast, the SAVI index, which accounts for the soil effect, reflected the protective role of vegetation cover in sparsely vegetated areas. The linear regression analysis also confirmed the correlation results; the highest coefficients of determination (R²) between soil erosion and NDVI and EVI were 0.148 and 0.146, respectively, indicating that these two indices explained soil erosion variations. The VARI and MSAVI indices, with values of 0.13 and 0.08, and the GNDVI and SAVI indices, with values of 0.070 and 0.074, showed lower explanatory power. https://geoplanning.tabrizu.ac.ir/article_21158.html Objective: The rapid growth of population and private vehicle ownership in Urmia, combined with the concentration of commercial activities, has caused severe challenges including parking shortages, traffic congestion, air pollution, and citizen dissatisfaction. This study aims to identify optimal locations for multi-story parking facilities in District 5 of Urmia city using an advanced multi-criteria decision-making framework.Methods: Spatial and functional data, including existing parking facilities, trip-attracting land uses, land prices, vacant lands, slope, traffic nodes, road networks, and hourly vehicle entries, were collected from official sources and field surveys. The data layers were prepared and processed in a GIS environment. A hybrid Fuzzy Analytic Network Process (Fuzzy ANP)–MultiMOORA approach was then applied to calculate criteria weights and rank alternative locations. Data analysis involved simulating interactions among criteria, ranking options, and determining the most suitable sites for parking development.Results: The findings indicated that the “distance from trip-attracting centers” criterion, with a weight of 0.3245, was the most influential factor. Four final options located on Hassani and Varzesh streets were identified as the best locations. The proposed model demonstrated higher accuracy and efficiency in spatial analysis compared to conventional methods.Conclusions: The integrated Fuzzy ANP–MultiMOORA framework provides a reliable and replicable approach for spatial decision-making in urban parking planning. It can support traffic demand management and guide infrastructure development in other high-traffic areas of Urmia. Urban managers are recommended to prioritize parking facility expansion using this framework. https://geoplanning.tabrizu.ac.ir/article_21168.html Migration plays a crucial role in demographic studies because, alongside fertility and mortality rates, it influences the size, structure, and characteristics of the population and has a decisive impact on population distribution and labor force growth. Accordingly, the present study designed to analyze intra and extra provincial migration flows of East Azerbaijan Province. The research is applied and descriptive-analytical. The geographical scope of the study encompasses the counties of East Azerbaijan and their interactions with all other provinces across the country. Data were collected through documentary method, fundamentally based on secondary data from the 2016 census regarding the number of county migrants, covering the period from 2011 to 2016 years. For data analysis, network analysis techniques were employed using softwares such as Excel, ArcGIS, and UCINET. The findings revealed that the highest level of immigration occurred in Osko County, primarily due to population overflow from the city of Tabriz toward the newly established city of Sahand. The immigration connections of this county were also evident with most other counties in the province, though to a lesser extent—particularly with the counties of Ahar, Kaleibar, Herris, and Varzgan. Regarding out-of-province emigration, the highest proportions were directed toward the provinces of Tehran, West Azerbaijan, Ardabil, and Qom, reflecting East Azerbaijan’s strong demographic ties with these regions. Among them, Tehran exhibited the highest absorption, largely driven by the emigration from the counties of Tabriz, Sarab, Miyaneh, Maragheh, Shabestar, Bostanabad, and Marand. https://geoplanning.tabrizu.ac.ir/article_21169.html Objective: Urbanization and the rising demand for energy have positioned urban renewable energy as a central theme in global scientific research. This study aims to conduct a comprehensive scientometric analysis of research on urban renewable energy, with a particular focus on solar technologies and building-integrated photovoltaics (BIPV), spanning the years 2000 to 2025. The goal is to identify dominant research themes, key contributors, emerging trends, and gaps in the literature, particularly in the context of developing countries such as Iran. Methods: Data were extracted from the Web of Science database and analyzed using VOSviewer 1.6.20 to visualize keyword co-occurrence, author collaboration networks, and institutional contributions. The scientometric approach enabled the mapping of global research production and collaboration patterns over the specified period. Results:The analysis revealed that dominant research themes include sustainability, solar energy, BIPV systems, energy policy, green urbanism, and climate change mitigation. In Iran, there is additional focus on energy infrastructure resilience, optimization of building energy consumption, and strategic urban energy planning. The study also identified key contributors, mapped the global flow of knowledge, and highlighted gaps in interdisciplinary collaboration, as well as underrepresented topics such as socio-cultural dimensions of energy transition and localized policy frameworks. Conclusions: By synthesizing these findings, the study provides a roadmap for future research directions and policy development aimed at enhancing urban energy resilience and sustainability. The proposed framework can assist researchers, planners, and policymakers in aligning scientific inquiry with practical urban energy challenges, particularly in semi-arid and rapidly urbanizing regions. https://geoplanning.tabrizu.ac.ir/article_21189.html The study, which is applied in terms of purpose and descriptive-survey in terms of data collection, was conducted with the aim of designing a socio-economic resilience model with an emphasis on local governance and participatory planning; its statistical population included 857 people living in the villages of Sur and Tote Khaneh in Bonab County, and the sample size was determined as 265 people using the Cochran formula. The sampling method was based on the stratified random method, and sampling was carried out from each village in proportion to its population share in the entire community. Exploratory factor analysis and multiple regression analysis were used to analyze the research findings. The results of the factor analysis showed that the factors of local governance, participatory planning, social capital, livelihood diversity, social resilience, and economic resilience were ranked first to sixth, respectively. The results of regression analysis from modeling the factors affecting economic resilience in the villages of Sur and Tote Khaneh showed that the greatest impact is related to local governance with a standard beta coefficient of 0.340, which indicates that improving the state of local governance has a significant impact on increasing economic resilience. After that, social capital with a beta coefficient of 0.255, livelihood diversity with a beta coefficient of 0.215, and participatory planning with a beta coefficient of 0.145 are in the next ranks. the results of regression analysis from modeling the factors affecting social resilience in the villages of Sur and Tote Khaneh showed that local governance with a standard coefficient of 0.385 is the strongest predictor for social resilience, which indicates that improving local governance has the greatest impact on strengthening social cohesion. participatory planning with a coefficient of 0.250, social capital with a coefficient of 0.195, and livelihood diversity with a coefficient of 0.135 are ranked. https://geoplanning.tabrizu.ac.ir/article_21197.html Objective: Tourism has gained significant momentum in international societies. With economic growth and changes in consumer behavior, the tourism industry has transformed from a luxury product to a necessary product. Tourism development is rapidly improving, and the role of the local community as the main supporter of tourism in the destination has increased more than ever. Therefore, this study, focusing on the role of the local community in tourism, seeks to examine the role of social attachment and perceived risk on the emotional solidarity of the host community towards tourism with the role of mediating the perceived social effects of tourism.Methods: The present study is applied in terms of purpose, descriptive survey in terms of nature and method and was conducted cross-sectionally. The study population in this study is the residents of Tabriz city, 314 people were selected as a sample. A standard questionnaire was used to collect data, whose reliability was confirmed using Cronbach's alpha and its composite reliability and validity were confirmed using legal validity, face validity and construct validity. Structural equation modeling and pls software were used to analyze the data.Results: The results of the study showed that the effect of perceived risk, social attachment and perceived social effects on emotional solidarity was confirmed. On the other hand, the mediating role of perceived social effects of tourism in the relationship between perceived risk and emotional solidarity was confirmed. However, the role of perceived risk on social attachment was not confirmed.Conclusions: Overall, the findings of this study show that the local community, based on the perceived social effects of tourism, existing risks and their social attachment, feels solidarity and support for the development of tourism in their community. This solidarity is important in tourism development and their cooperation and participation in this process. https://geoplanning.tabrizu.ac.ir/article_21225.html This research, conducted in 2025, is a qualitative, applied study based on library and documentary research. It was carried out using a descriptive-survey method with a scientometric approach, incorporating citation analysis, systematic reviews, bibliometric analysis, and lexical co-occurrence analysis of studies related to artificial intelligence and urban development. The study utilized VOSViewer software to identify the most influential vocabulary in the research topic. A systematic review of articles revealed nine thematic clusters that directly influenced the role of artificial intelligence in urban development. The most frequently examined keywords in these clusters, ranked by importance, included "artificial intelligence," "machine learning," and others. The study identified three main clusters: 1) Sustainable energy management (red), 2) Smart traffic and transportation (green), and 3) Sustainable urban planning (navy blue). Additionally, researchers such as Yigitcanlar and journals like Sustainable Cities and Society were prominent in the reviewed studies. The findings indicated that artificial intelligence in urban development emphasizes data-driven solutions, but issues such as sustainability, ethics, and privacy have received less attention. Furthermore, the limited number of studies on developing countries suggests that the application of artificial intelligence in urban development in these regions is overlooked compared to leading countries like China and the United States. The results demonstrated that artificial intelligence, with its significant performance benefits, is one of the best options for urban management to support sustainable urban development. AI can optimize infrastructure, reduce energy consumption, and enhance urban sustainability. However, the scattered nature of research and the lack of comprehensive analysis in this field highlight the need for scientometric studies https://geoplanning.tabrizu.ac.ir/article_21226.html This study is applied in nature and follows a descriptive–analytical approach. The data analyzed includes spatial information and statistics related to housing prices and the distribution of six categories of urban services, primarily obtained from the Municipality of Karaj and the Statistical Center of Iran. To produce digital layers, the Spatial and Spatial Analyst tools within the GIS environment were employed. The analytical models used in this research include Geographically Weighted Regression (GWR) anReclassify tool were applied. Subsequently, the Raster Calculator was used to combine service-related components. To calculate the correlation between urban services and housing prices, the Fuzzy Overlay tool within the Spatial Analyst extension was utilized. In addition, the Band Collection Statistics tool was used to compute correlation coefficients and covariances between the dependent and independent variables.Findings:The highest level of access to urban services is observed in the eastern and northeastern areas of Karaj. The central areas of the city have moderate to low levels of access, while the western, southwestern, and parts of the northern regions exhibit medium levels. The northern and northwestern zones show the lowest levels of urban services. The highest housing prices are found in the northeastern and eastern parts of the city, while the western and southern peripheral areas have lower prices. The strongest correlations between housing prices and urban services are associated with health–medical services (0.58) and administrative–security services (0.52), while the weakest correlation pertains to cultural–religious services (0.36).Conclusion:The uneven distribution of urban services in Karaj plays a significant role in shaping spatial inequalities in housing prices. Areas characterized by a high diversity and density of essential services—such as healthcare, administrative, transportation, and educational services—tend to have higher land and housing values. This, in turn, contributes to the reproduction of privileged and disadvantaged urban spaces across the city. https://geoplanning.tabrizu.ac.ir/article_21249.html The aim of this study is to estimate the amount of soil erosion and analyze its changes over a twenty-year period (2004–2024) in the Quri-Chay watershed in Ardabil Province using the Revised Universal Soil Loss Equation (RUSLE).Methods: n this regard, the five main factors of the model, including rainfall erosivity, soil erodibility, slope length and steepness, vegetation cover, and management practices, were calculated and integrated within the ArcGIS environment. The data used included Sentinel-2 satellite images for 2024, Landsat 5 TM images for 2004, a 12.5 m digital elevation model (ALOS PALSAR), twenty years of rainfall statistics, and the soil texture map of Iran. To examine land use changes, supervised classification with the Random Forest algorithm was performed in the Google Earth Engine environment, and classification accuracy was evaluated using the Kappa coefficient.Results: The results indicated that during the 2004–2024 period, significant changes occurred in the land use of the watershed. Rain-fed croplands, irrigated lands, and residential areas increased considerably, while rangelands, forests, and water bodies experienced a decline in area. These changes reflect human pressure and unsustainable exploitation of natural resources. The implementation of the RUSLE model showed that the average annual soil erosion increased from 26.65 tons per hectare in 2004 to 37.18 tons per hectare in 2024. In addition to the increase in the maximum amount of erosion, the erosion risk classes also changed. The areas with low and moderate risk expanded, while zones with high and very high risk, though relatively small, spread sporadically in steep and mountainous regions.Conclusions: These findings reveal that the conversion of natural lands into human land uses, the reduction in vegetation density, and the intensification of rainfall patterns have been the most influential factors in increasing soil erosion in the watershed. T https://geoplanning.tabrizu.ac.ir/article_21250.html Objective: The aim of this study is to evaluate and optimize a Convolutional Neural Network (CNN) model for predicting gully erosion susceptibility in the Sheshtamad region, using a feature selection approach and hyperparameter optimization.Methodology: In this research, a total of 600 points were identified through field surveys and satellite imagery, comprising 300 gully and 300 non-gully locations. Of these, 70% of the data were used for model training and 30% for validation. Twenty-one environmental factors including topographic, geological, hydrological, and land-use characteristics were selected as predictive variables. Subsequently, the Mutual Information (MI) criterion and the Random Forest algorithm were applied to identify the most influential factors contributing to gully erosion occurrence.Next, the CNN model was developed, and hyperparameter optimization was performed to enhance model performance. The optimized model output was then used to generate a gully erosion susceptibility map, which was evaluated in terms of both accuracy and predictive performance.Given that the study area (Sheshtamad County, western Razavi Khorasan Province) is highly prone to gully erosion, conducting such susceptibility assessments prior to any infrastructural development is essential.Results: The variable importance analysis revealed that rainfall, distance from rivers, distance from faults, and elevation are the most critical factors influencing gully erosion development. The optimized CNN model, after hyperparameter tuning using the Optuna algorithm, achieved a high prediction accuracy (Accuracy = 0.9338). The resulting susceptibility map indicated that the eastern part of the study area possesses the highest potential for gully erosion occurrence.Conclusion: The findings demonstrate that the integration of deep learning techniques, particularly the CNN model, with optimal feature selection and hyperparameter tuning provides a powerful framework for accurately predicting gully erosion-prone areas. This approach can support effective soil and water conservation planning and guide sustainable land management policies. https://geoplanning.tabrizu.ac.ir/article_21251.html Situated within the global arid and semi-arid belt, Iran faces significant climatic challenges characterized by precipitation regime instability, heavy reliance on seasonal rainfall, and uneven spatial distribution of precipitation. Although intense and widespread precipitation events account for a modest proportion of the annual rainfall total, their importance is magnified by their dual role in water resource provision and the generation of destructive floods - constituting a hydrological paradox of equal measures of risk and resource. Research demonstrates that these extreme precipitation phenomena are primarily governed by cyclonic systems originating from diverse sources, including Mediterranean disturbances, Sudanese low-pressure systems, and Persian Gulf cyclones, which interact synergistically with dynamic atmospheric mechanisms and thermodynamic processes. Recent climate transformations have substantially altered the behavioral patterns of these meteorological systems, resulting in marked increases in both the intensity and frequency of extreme precipitation events. This research undertakes a comprehensive analysis of the spatiotemporal distributions and dynamic characteristics of cyclones influencing heavy precipitation events across Iran in recent decades, thereby addressing critical knowledge gaps and advancing the current understanding of extreme precipitation mechanisms in this vulnerable region. https://geoplanning.tabrizu.ac.ir/article_21253.html Purpose: Given the increasing competition among health tourism destinations at both global and national levels, identifying and managing the factors that influence the image and reputation of these destinations' brands has become a critical issue. This research aims to design a model of factors affecting the indicators of the health tourism destination brand of Kerman City. Research Method: This study is descriptive-analytical in nature and falls under applied research. Data collection methods included library research and surveying (questionnaires). The data collection approach was determined to be interactive and expert-oriented. Data analysis was designed using a mixed-methods (quantitative-qualitative) approach, with the geographical scope of the research being Kerman City. The sample from the statistical population consisted of approximately 50 experts, specialists, professionals, and faculty members, selected through snowball sampling. Data were collected using Instant Delphi, and Smart PLS 3 was used for data analysis. Results: The results indicate that at a 95% confidence level, based on the path coefficient (Beta), the construct of Perceived Value of the Health Tourism Destination had the greatest impact on loyalty to the health tourism destination brand of Kerman City (β = 0.643). This was followed by the Health Tourism Destination Brand Image construct, which had a positive impact (β = 0.484) on loyalty to the brand. The least impact belonged to the Health Tourism Destination Brand Awareness construct (β = 0.322) on loyalty. Furthermore, according to the evaluation of the indices (SRMR, NFI, and RMS Theta), it can be claimed that the research model enjoys appropriate overall fit and is confirmable. https://geoplanning.tabrizu.ac.ir/article_21320.html Integrated planning and resilience-based approaches play a fundamental role in reducing urban vulnerability to natural hazards and accelerating post-disaster recovery. Accordingly, this study aims to assess and enhance spatial resilience at the neighborhood scale, focusing on the Roshdieh neighborhood of Tabriz, which is located along the North Tabriz Fault and is exposed to high seismic risk. A descriptive–analytical methodology is adopted, and three key components influencing spatial resilience are examined: access to medical and emergency services, distribution and accessibility of open and shelter spaces, and the spatial configuration of the street network. The study integrates spatial and configurational analysis techniques based on Space Syntax with a network-based analytical approach using the Analytic Network Process (ANP). This integrated framework enables the evaluation of both internal network interdependencies among the components and the external dependency of each component in enhancing spatial resilience. The results of the quantitative ANP analysis provide a priority-based roadmap for resilience-oriented spatial planning. The findings reveal that “equitable distribution and accessibility of open and shelter spaces” constitute the core of spatial resilience, accounting for 62.5% of the overall contribution. Beyond serving as final evacuation destinations, these spaces independently contribute to mitigating primary damages. The “quality of the street network” ranks second with a weight of 23.8%, highlighting its critical facilitative role in ensuring effective access to safe spaces and urban services during emergencies. Although “access to medical and emergency services” has the lowest independent weight (13.6%), its importance increases to 39.5% through network interactions, indicating a strong dependence on street network efficiency and proximity to safe open spaces. Overall, the study underscores the analytical superiority of network-based approaches over hierarchical models and emphasizes the necessity of adopting a holistic perspective in urban spatial resilience planning. https://geoplanning.tabrizu.ac.ir/article_21321.html Objective: This research aimed to investigate and analyze the role of the circular economy in the transformation of Iran's urban management system, focusing on Isfahan city as a case study. Methods: This study is applied in purpose and descriptive-analytical in terms of data collection and analysis. Field data were collected using a researcher-made questionnaire, the validity and reliability of which were confirmed, from 384 citizens of Isfahan through multi-stage cluster sampling. The data were analyzed using Confirmatory Factor Analysis (CFA) and a One-Sample T-Test in SPSS and AMOS software. Results: The findings of the confirmatory factor analysis confirmed the desirable fit of the research's conceptual model. The results of the T-test indicated that the overall status of the circular economy in Isfahan's urban management, with a mean score of 2.75 (on a 5-point scale), was significantly below the average. The "Governance and Policy" dimension, with a mean of 2.45, was identified as the weakest dimension. The "Technology and Innovation" (mean 2.80) and "Economic and Market" (mean 2.70) dimensions also showed an unfavorable status. In contrast, the "Socio-Spatial Structure" dimension, with a mean of 3.05, was rated as average, and the "Citizen Awareness and Participation" criterion (mean 3.20) was recognized as a relative strength. Conclusions: Despite having suitable social potential and human capital, the city of Isfahan faces challenges in transitioning towards a circular economy due to significant obstacles in the dimensions of governance, technology, and economics. Success in this transition requires an integrated and multi-dimensional approach. Accordingly, operational strategies are proposed, including formulating a strategic document for Isfahan's circular economy, revising construction regulations, developing an ecosystem for circular innovation and businesses, establishing an innovation center, designing supportive financial mechanisms, and developing recycling infrastructure. https://geoplanning.tabrizu.ac.ir/article_21332.html In the contemporary era,urban areas have become increasingly vulnerable due to the growing complexity and interdependence of urban systems.Cities are simultaneously exposed to natural hazards, technological failures,and socio-security threats, which can severely disrupt urban life. Among urban lifeline infrastructures, water supply systems are considered critical facilities,as their disruption can lead to widespread economic losses, social instability, public health risks, and security challenges.These systems are particularly vulnerable to military and terrorist attacks; therefore,the application of defensive and security considerations is essential. Passive defense, as a set of non-structural and structural measures aimed at reducing vulnerability and increasing resilience without the use of military force, plays a significant role in enhancing the sustainability and continuity of urban infrastructure services.This study was conducted using a descriptive–analytical research method to assess the vulnerability of Ilam’s urban water infrastructure against security and law-enforcement threats within the framework of passive defense.The required data were mainlycollected through field surveys, including interviews with experts and the distribution of structured questionnaires. In order to analyze the data and determine the relative importance of thecriteria and sub-criteria, theAnalytic Hierarchy Process(AHP)and network analysis were employed.The results indicate that the criterion of critical infrastructure facilities and key managerial indicators has the greatest impact on the vulnerability level of Ilam’s urban water supplysystem.Among the sub-criteria, the water transmission network and water resources and storage reservoirs, with a weight of 0.615, were identified as the most influential factors contributing to system vulnerability.In addition, the proximity to military centers, governmental offices, and municipal facilities ranked next, with relative weights of 0.362 and 0.475, respectively.Finallythe vulnerability layers were integrated to produce a spatial zoning map of Ilam’s urban water infrastructure based on passive defense principles.The study also proposes practical strategies aimed at reducing potential damages and improving the resilience of the water supplysystem against security-related threats. https://geoplanning.tabrizu.ac.ir/article_21361.html The aim of this research is to evaluate the change in Iran'sclimate indicators over two 30-year periods (1960-1990) and (1991-2020). In this study, statistics from 43 Iranian synoptic meteorological stations related to the climatic parameters of monthly mean maximum and minimum temperatures, mean temperature and precipitation were used. The indicators used were potential evapotranspiration, dry season length, middle season length, and wet season length. First, the data were qualitatively controlled. The run test was used for data homogeneity. Then, the Papadakis method was used to evaluate the change in Iran's climate indicators. The classification system invented by Papadakis is a type of system that tries to avoid the lack of accuracy in common climate classifications by creating smaller geographical units and providing greater climatic uniformity, and to determine the agricultural suitability of these units due to their smaller size. Papadakis has established 12 main and 40 sub-thermal regimes that are important from an agricultural perspective in his system. The types of thermal regimes depend on the summer and winter temperature conditions. Papadakis devised 14 moisture regimes defined by a moisture index and its annual distribution. The results of the Papadakis method showed that potential evapotranspiration and temperature in most climatic regions have increased and precipitation has decreased. The results of this study also showed that on average about 15 days have been reduced from the wet season and in contrast, 1 day has been added to the middle season and 14 days to the dry season. All studied stations were classified into 7 main climatic groups and 11 sub-categories, including Mediterranean desert, subtropical Mediterranean, subtropical semi-arid Mediterranean, Mediterranean semi-arid desert, desert desert, subtropical desert, and monsoon desert. https://geoplanning.tabrizu.ac.ir/article_21362.html In the present study, Land Surface Temperature (LST) for Ardabil County was retrieved using OLI sensor images from the Landsat 8 satellite, applying the Single-Channel (SC) and SEBAL algorithms. In the next step, the results were validated using SLSTR sensor data from the Sentinel-3 satellite and finally compared with synoptic station data of the study area. Overall, the Single-Channel algorithm estimated higher surface temperatures compared to the SEBAL algorithm. This difference can be attributed to the fact that SEBAL utilizes both thermal bands 10 and 11 for LST retrieval, while the computational parameters in the two algorithms differ. Despite its more complex computational process, the SEBAL algorithm produced more realistic and accurate LST estimations. Furthermore, comparison between thermal bands 10 and 11 within the SEBAL framework indicated that band 10, due to its higher signal quality, is more suitable for LST extraction, although combining both bands can further improve accuracy. Daily temperature fluctuations were observed in both algorithms; however, their magnitude was more pronounced in the Single-Channel method. Moreover, by analyzing the difference between the daily mean temperature derived from Landsat 8 satellite data and the temperature recorded at the synoptic station, the SEBAL algorithm demonstrated better agreement with actual ground temperature, with a lower mean temperature difference (16.21 °C) compared to the Single-Channel method (25.60 °C) during the statistical period. Results from linear regression analysis and correlation coefficient calculations revealed an average correlation (R) of 0.96, confirming the high accuracy and reliability of the estimated values. This study highlights the importance of careful selection of retrieval algorithms and satellite sensors, as well as the influence of environmental factors on temperature variability, emphasizing that data validation is a crucial step in both scientific and applied research. https://geoplanning.tabrizu.ac.ir/article_21376.html .The purpose of this research is to investigate the effect of land usechanges, temperatureand precipitation on the fluctuations of underground water in Tuiserkan city during the years 2000, 2009 and2020 using Landsat 8 satelliteimages.First, pre-processing was doneusing the maximum likelihood algorithm and land cover map was prepared and the intensity of surface impermeability was evaluated with the NDBI index.Then, using the data of 9 piezometric wells and the IDW interpolation method, a map of water level changes was prepared, and the ground surface temperature was also checked from Landsat images andLSTcalculation.and finally, Kendall-Tao correlation test was used to investigate the statistical relationship between water level, land use and surface temperature.The results showed that the area of built land has increased by 5.86% and the vegetation has decreased by 15.39%The NDBI index showed that the amount of impervious surfaces has increased with the increase of barren and built-up lands and the decrease of vegetation, which has caused a decrease in water infiltration and aquifer nutrition.Investigating the statistical relationship between water level fluctuations and surface temperature showed that only in 2009 there was a significant positive relationship at the level of 1% and at the rate of 0.142.The results show that due to the increase of impervious surfaces due to the change of land use and more water withdrawal from the plain aquifer, the level of the watershed is mainly affected by the rainfall and currents entering the aquifer and the amount of water withdrawal.Because with the increase in land use changes and the expansion of built-up areas, the changes in the water level of the wells are uniform and not in accordance with the increase in built-up land and the decrease in vegetation, which indicates that the depth of water impact has decreased and the level of underground water has increased. https://geoplanning.tabrizu.ac.ir/article_21377.html The present study systematically analyzes the conceptual structure, maps research trends, and identifies knowledge gaps in the literature on multi-level governance within urban planning and management. Using a descriptive-analytical bibliometric approach, 1,662 articles indexed in the Web of Science between 2001 - 2025 were retrieved, screened, and organized in Excel. Network analysis via VOSviewer produced three bibliometric visualizations: keyword co-occurrence, conceptual density, and temporal overlay maps. Results show a marked increase in scholarly output from around 2010, with a peak of 130 publications in 2021. Network analysis revealed eight thematic clusters: (1) core mechanisms and institutions of multi-level governance; (2) urban resilience and institutional collaboration; (3) sustainable development and the urban economy; (4) network structures and public participation; (5) climate change and urban agriculture; (6) tourism and local communities; (7) local authorities and organizations; and (8) managerial communication and spatial planning. Temporal patterns indicate a shift from institutional-structural topics toward interdisciplinary, technology-driven, and environmentally oriented approaches. The study confirms the maturity and thematic diversity of the field and recommends that future research prioritize comparative analyses, quantitative network metrics, and stronger integration of bibliometric techniques with field-based investigations. https://geoplanning.tabrizu.ac.ir/article_21415.html Specialized ecotourism plays a pivotal role in promoting sustainable rural development. Despite its significant natural and cultural potentials, Zrivar Wetland faces various structural and managerial challenges, limiting the development of nature-based tourism in the region. Accordingly, systematically identifying the current conditions and barriers to specialized ecotourism is essential for effective planning and policy formulation.This applied study adopts a comprehensive mixed-methods approach, integrating quantitative and qualitative techniques to examine the status of nature-based specialized tourism along the Zrivar Wetland tourism axis. Data collection involved structured questionnaires, in-depth interviews, and meticulous field observations. The study population consisted of academic experts, local informants, development authorities, and tourism practitioners, selected purposively to ensure relevant insights. In the qualitative phase, grounded theory was employed to achieve a comprehensive understanding of the current situation and diagnose the stagnation of tourism development in the area. In the quantitative phase, path analysis was applied to validate qualitative findings. Furthermore, the prioritization of target villages for tourism development was conducted using the TOPSIS technique based on a Delphi expert consensus.The results indicate that the development of specialized ecotourism in the Zrivar Wetland area is at a “low” to “very low” level. Institutional deficiencies and limited financial resources emerged as the most significant barriers, followed by weaknesses in planning, policymaking, and management, inadequate infrastructure and services, socio-cultural limitations, insufficient education and promotion, and the influence of border security management. Path analysis revealed that institutional inefficiencies (0/547) and financial constraints (0/433) exert the greatest impact on the persistence of unfavorable tourism conditions.Based on the TOPSIS analysis, Yengijeh Village was identified as the main target and central hub for nature-based tourism development among the designated villages. These findings provide a strategic foundation for addressing existing challenges and advancing specialized ecotourism in the Zrivar Wetland region. https://geoplanning.tabrizu.ac.ir/article_21492.html Citizen participation , as an effective tool in urban planning , helps to create a sense of belonging and responsibility among residents . this process not only leads to transparency and democratization of decision –making , but also improves the quality of urban plans according to the real needs and desires of the people. On the other hand, active citizen participation can lead to identifying problems and providing solution, this approach also helps to strengthen social solidarity and increase trust in government institutions . the purpose of this research is to create reform solutions in plans, rules, and regulations to increase citizen participation . the innovation of the present article is in the realistic examination of the issue of participation and democratic planning in the structure of iranian cities. The research method in the present study is mixed ( qualitative and quantitative )with an applied purpose and an analytical and exploratory nature. For thiss purpose , first , the issue of public participation has been explained through documentary studies, which in the first part refers to the analysis of data obtained from interviews and surveys , and in the second part, a questonnaire has been used to measure public participation .which has twenty questions and two components of participation resulting from a favorable organizational climate and spontaneous partocipation . which has been presented for data analysis using spss and among software and based on the participation of 384 people for the two regions for gorgan.The results show that the number of repeated themes for facilitating access to plans is the highest 48 thems , this is followed by strengthening the role of civil society organizations in the decision –making process with 31themes, ensuring the rights of citizens to participate in decision –making with 31 themes, https://geoplanning.tabrizu.ac.ir/article_21519.html Objective: Extracting floodplains in watersheds is the first management strategy in developing flood control and containment programs. For flood management in the Qarasu River watershed located in the Ardabil plain, the present study was conducted using the Random Forest (RF) technique. Research Method: For this purpose, first, the training points of the random forest technique were determined, including 183 flood points and 163 non-flood observation points in the spatial distribution of the basin. Then, 17 effective parameters in the flooding of the watershed, including DEM map, the slope of the river bed, distance from the channel, distance from the waterway, Topographic Position Index (TPI), Modified Catchment Area (MCA), Terrain Ruggedness Index (TRI), Topographic Wetness Index (TWI), Stream Power Index (SPI), distance from the dam, the density of waterways, drainage density, the direction of waterway flow, land use, geology, soil erosion and geomorphological landforms selected and entered the model as independent variables. Using the random forest model, a flood hazard map was drawn for the Ardabil plain. Results: The results showed that the model evaluation metrics including AUC, MSE, MAI, RMSE and R2 were obtained as 0.996, 0.026, 0.045, 0.161 and 0.90, respectively, which indicates the reliability of the model used. Among the independent parameters, distance from the Qarasu River, DEM, MCA, and TWI had the greatest impact on flooding in the Qarasu River watershed with a correlation coefficient of -0.753, -0.471, 0.382, and 0.366, respectively. The final map obtained from the model indicated that lands close to the Qarasu River, especially in the Ardabil Plain, have the highest risk of flooding. Conclusion: In general, about 80,497 hectares of the Qarasu River watershed, which are mainly located in the central part of Ardabil, are at very high risk of flooding with heavy rainfall. https://geoplanning.tabrizu.ac.ir/article_21534.html The present study aimed to investigate the homogeneity and trend of changes in annual minimum temperature, maximum temperature, and precipitation across 112 synoptic stations in Iran over a 30-year period (1991–2020). For homogeneity analysis, four tests (Pettitt, SNHT, Buishand, and von Neumann) were applied, while trend analysis was performed using the ordinary Mann–Kendall (MK) test and the modified Mann–Kendall test with pre whitening (MMK TFPW). The true slope of the trends was then estimated using Sen’s slope estimator. Subsequently, breakpoints (shift points) were identified, and stations were classified based on their degree of homogeneity. The results indicated that the SNHT test identified the highest percentage of homogeneous stations for minimum temperature (50%) and maximum temperature (41.96%), whereas for precipitation, Pettitt’s test showed the highest homogeneity (89.29%). Trend analysis using the MK method revealed a prevailing increasing trend in maximum temperature (86.92% of stations) and no significant trend in precipitation (91.96%). After applying the modified method (MMK TFPW) to remove the effect of autocorrelation, the percentage of stations with no significant trend increased markedly for all three variables (reaching 83.04%, 80.36%, and 100%, respectively). The results of the true trend slopes varied considerably among the stations. The years 1997 and 2008 were identified as the main breakpoints across all variables and tests. In the final classification, precipitation data were predominantly (74.11%) placed in the homogeneous class (A), while temperature data (especially maximum temperature) were largely classified as non homogeneous (class C, 77%). These findings suggest that temperature data are more sensitive than precipitation data to factors causing inhomogeneity. The variation in homogeneity results and breakpoints among different stations highlights the strong influence of local conditions and spatial heterogeneity on climatic time series and underscores the necessity of considering these factors in future studies and climate change modeling. https://geoplanning.tabrizu.ac.ir/article_21535.html Lake Urmia, the second saltiest lake in the world, has faced a drastic reduction in surface waters and intensified drought over the past two decades. This crisis comes with cross-border environmental impacts. The present study analyzes three key indicators of groundwater change, the SPI, and the VHI using satellite data from Google Earth Engine (Landsat, MODIS, GRACE, TRMM) across two northern regions (Sharfkhaneh and Golonjeh) and two southern regions (Chapghalu and Shirwan Shalyan) for the period 2002–2017. The findings show that the decline in groundwater depth is nearly uniform across all regions. However, the SPI index indicates severe drought in the Sharfkhaneh area (northeast) due to an above-average decrease in precipitation compared with other regions. Additionally, the VHI, calculated as the equal combination of the VCI and TCI, reveals a notable decline in vegetation health by 13 percent in the same region. These results suggest a movement of the watershed feeding the lake toward drought, with the pace of this trend being significantly higher in the north, particularly the northeast. Key factors behind this phenomenon include the depletion and homogenization of groundwater resources, reduced precipitation in the north, and human impacts—especially in the eastern part—such as dam construction, unbridled agricultural expansion, and the drilling of unauthorized wells. These changes threaten the regional ecosystem, local communities’ livelihoods, and agriculture. A more precise examination of these factors could guide effective strategies to reduce drought and maintain ecological balance. It is essential to prioritize the challenges and develop operational actions to improve the environmental conditions and living standards of the region’s residents. These strategies should include sustainable water resource management, a reevaluation of dam projects, and lake ecosystem restoration. Attending to these points will prevent the crisis from worsening and foster the resilience of local communities to climate change. https://geoplanning.tabrizu.ac.ir/article_21567.html Objective: A livable city, as a key component of sustainable urban development, relies on an efficient system of urban planning regulations. In Iran, despite the development of numerous documents and codes, a significant gap persists between theoretical goals and practical realization of livable cities. This study aims to examine the urban planning regulatory system in Isfahan metropolis and analyze its role in achieving urban livability indicators.Methods: This applied research employs a descriptive–analytical approach. Data were collected through library studies and 30 questionnaires completed by urban planning experts. Livability indicators were organized into three dimensions: social, physical–environmental, and institutional–managerial. Statistical analyses including one-sample T-tests, Friedman tests, and Partial Least Squares (PLS) structural equation modeling were applied. Cronbach’s alpha was used to assess the reliability of indicators, all exceeding 0.7.Results: Findings indicate that social and physical–environmental dimensions, such as social participation, sense of place, and green spaces, performed better than institutional–managerial aspects. In contrast, indicators like transparency, accountability, and equity scored low. Certain urban planning regulations, including zoning and façade design, positively influenced livability, while others, such as density aggregation and building height regulations, had negative effects, reflecting weaknesses in the coherence and flexibility of Isfahan’s regulatory system.Conclusions: Achieving a livable city in Isfahan requires revising urban regulations with a localized, participatory, and transparent approach. In particular, shifting from a rule-based to a guideline- and performance-oriented model is essential to prioritize spatial quality and citizen satisfaction in urban decision-making. These findings align with previous studies in other Iranian cities and emphasize the need for transforming urban governance structures and strengthening the linkages among institutional, social, and physical dimensions to achieve sustainable livability. https://geoplanning.tabrizu.ac.ir/article_21604.html Objective: The primary aim of this study is to identify, analyze, and prioritize the key factors influencing the development of sustainable creative tourism, with a specific focus on Ardabil Province in Iran. Employing a mixed-methods approach, the study investigates both conceptual and empirical dimensions of sustainable creative tourism within a regional context, ultimately proposing an optimized conceptual-operational model for policymaking. Methodology: This research adopts a sequential mixed-methods design with unequal weighting. In the qualitative phase, data were collected through semi-structured interviews with 23 experts, selected based on theoretical saturation. The interviews were coded using ATLAS.ti version 24. This process led to the identification of 26 critical parameters influencing sustainable creative tourism development. Additionally, a conceptual map was developed to illustrate the interrelationships among these parameters. In the quantitative phase, the RReliefF and TOPSIS techniques were employed via MATLAB version 2018 to determine the relative weights and priorities of the identified factors. For comparability between qualitative and quantitative outputs, all data were normalized using the Min–Max scaling method. Findings: The findings indicated that components such as “preservation and promotion of cultural heritage,” “improvement of environmental quality,” “economic resilience and sustainability,” “local participation and governance,” and “enhancement of employment quality” received the highest composite scores. Subsequently, all factors were categorized into five parameter layers, including core, strategic, operational, supportive, and expandable parameters. These layers constituted the final model of the present study. Conclusion: The study concludes that the development of sustainable creative tourism requires a systematic and integrative approach that combines conceptual analyses with statistical decision-making. The final model demonstrates the interaction of the five parameter layers and has the capacity to serve as a framework for policymaking at both regional and national levels. Moreover, this model enables the design of flexible pathways for sustainable creative tourism. https://geoplanning.tabrizu.ac.ir/article_21605.html Precipitation is one of the most complex and critical elements of Earth's atmosphere. Its temporal and spatial variations can control the environmental characteristics of any geographical region. Consequently, many climatologists regard precipitation as the most important atmospheric phenomenon and one of the principal climatic elements. Continuous advancement in remote sensing technology has led to the development of numerous satellite precipitation products aimed at providing continuous global precipitation data at various temporal and spatial scales, and the expansion of satellites and satellite precipitation algorithms has provided new potential for precipitation estimation. However, the use of these satellite data requires comprehensive evaluation of their accuracy and efficiency. Therefore, the objective of this study is to examine and evaluate the accuracy of PERSIANN-CDR and CHIRPS satellite precipitation data at the daily scale in the western half of Iran. To this end, PERSIANN-CDR and CHIRPS satellite precipitation data and daily precipitation data from 24 synoptic stations during the statistical period (2001-2023) were utilized. To assess the accuracy of PERSIANN-CDR and CHIRPS satellite precipitation data, statistical indices including CC, RMSE, MAE, and PBias, as well as three categorical indices POD, FAR, and CSI were employed. The results indicated that absolute preference cannot be established for either of these two satellite datasets. Overall, the results obtained from the mean values of CC, MAE, PBias, and FAR indices suggest the relative superiority of CHIRPS over PERSIANN-CDR. In contrast, PERSIANN-CDR precipitation data demonstrate superiority in RMSE, POD, and CSI indices. Therefore, the selection of the desired satellite data should be based on the index of interest. Finally, the average results of the evaluation indices indicate the relative superiority of CHIRPS over PERSIANN-CDR. https://geoplanning.tabrizu.ac.ir/article_21617.html Objective: The presence of multiple actors with differing interests and perceptions in rural tourism supply has led to numerous conflicts, posing a serious obstacle to community-based tourism development. Therefore, the present study aims to analyze strategies and conflict management patterns among rural tourism stakeholders to identify equilibrium states and propose an optimal model. Methods: This study utilized game theory (collaborative approach and non-quantitative method, graph model). The study population included 19 rural tourism destination villages in Torghabeh Shandiz County. Data were collected through interviews with 81 stakeholder representatives (including local residents, business owners, tourists, village managers, and relevant organizations) and strategy prioritization by 17 experts. The data were analyzed using conventional content analysis and the conflict resolution model framework employing GMCR+ software. Results: The results showed that among 12 feasible states, there are 2 stable equilibrium states and 5 semi-stable equilibrium states in managing conflicts among stakeholders of rural tourism destinations. State 12, which includes strategies such as: participation and support of the local community in tourism development, development of indigenous, participatory, and legal tourism businesses by tourism business owners, tourists’ respect for local laws and values, mutual cooperation of rural managers with other stakeholders towards sustainable tourism development, support from relevant organizations for the development of natural and indigenous tourism, and improvement of current structures and regulations, was identified as the most stable equilibrium state and provides the greatest benefit to all actors. This state, within the framework of the fivefold conflict management model, tends toward cooperation and compromise. Conclusions: Achieving a stable equilibrium state (State 12) and consequently sustainable and community-based rural tourism development require structural reforms, trust-building, cooperation, and comprehensive participation of all actors involved in the conflict. https://geoplanning.tabrizu.ac.ir/article_21684.html Objective: The UNESCO Creative Cities Network (UCCN) promotes music as one of the key drivers of sustainable urban development, emphasizing the linkage between creativity, cultural identity, social cohesion, and the creative economy. For the first time in Iran, this study evaluates the capacity of the city of Rasht—an emerging city with a rich Gilani musical heritage—to join the music field of the UCCN, adopting a mixed qualitative–quantitative approach. The aim is to provide a systematic analysis of the music ecosystem based on UNESCO’s seven official criteria and to propose practical spatial–institutional strategies. Methods:The methodology consists of a systematic document analysis and 15 semi-structured interviews with artists, cultural managers, and academics (purposive sampling until theoretical saturation). Thematic analysis conducted in MAXQDA transformed 107 initial codes into 15 main themes, categorized according to UNESCO’s criteria. The findings reveal a structural duality: notable strengths in indigenous musical heritage, stylistic diversity, informal education, and social dynamism coexist with serious weaknesses in professional production infrastructure, digital archiving, institutional networking, and the spatially centralized distribution of music-related facilities. Results: In this study, a SWOT matrix was first developed to organize this duality. In the next step, a weighted Quantitative Strategic Planning Matrix (QSPM), based on the Analytic Hierarchy Process (AHP) and sensitivity analysis, was employed to prioritize strategies. Accordingly, the three top strategies identified include hosting music events in public–historic spaces, creating an integrated network of music-related spaces, and institutionalizing indigenous music education. Conclusions: By proposing a novel spatial–institutional framework for music policymaking in developing cities, this research addresses a gap in the literature by linking local heritage with participatory governance and spatial justice, and offers practical implications for urban regeneration and the development of the creative economy. https://geoplanning.tabrizu.ac.ir/article_21713.html Objective: The aim of the present study is to investigate the role of artificial intelligence in improving the environmental performance of the municipality with the mediating role of management support in the city of Natanz. Methods: The present study was conducted in terms of applied purpose and descriptive-survey method. The statistical population of the present study included all employees of the Natanz municipality, 250 people, and the sample size was selected based on Cronbach's alpha as 152 people. The research tool included three standard questionnaires: artificial intelligence from Makilaw (2021) with 16 items, environmental performance from Maltik (2015) with 5 items, and management support from Sachs and Thorpe (2015) with 9 items. The validity of the tool in formal, content, and construct methods and its reliability based on Cronbach's alpha for the entire questionnaire was confirmed at 0.857. The collected data were analyzed based on structural equation path analysis in PLS software. Results: The results indicated that artificial intelligence has an impact on environmental performance with an impact coefficient of 0.749 and a t value of 438.15, artificial intelligence has an impact on management support with an impact coefficient of 0.765 and a t value of 122.12, and management support has an impact on environmental performance with an impact coefficient of 0.563 and a t value of 252.6. Also, the results of the Sobel test showed that artificial intelligence has an impact on improving the environmental performance of the municipality with the mediating role of management support with a T value of 397.15. Conclusions: The role of AI in improving the environmental performance of municipalities, especially in cities like Natanz, is very important. This can include the use of AI in areas such as air pollution monitoring, water resource management, waste management, energy consumption optimization, and environmental change prediction. https://geoplanning.tabrizu.ac.ir/article_21714.html This study aims to evaluate and identify the critical drivers influencing the quality of life in the metropolis of Tabriz. Understanding these factors can assist in recognizing problematic urban zones, uncovering causes of citizen dissatisfaction, prioritizing residents’ needs, analyzing the impact of socio-demographic variables on quality of life, and monitoring the effectiveness of related policies and strategies. Methods: The research is applied in nature and follows a descriptive-analytical approach. The study was conducted in three main phases: (1) identification of critical drivers through theoretical literature review and the Delphi method; (2) development and assessment of probable and desirable scenarios using structural analysis (cross-impact analysis) via MicMac software; and (3) formulation of optimal strategies based on the selected scenario using SWOT analysis. In the first phase, 55 relevant variables were initially identified. In the second phase, critical drivers were extracted using MicMac software, and scenarios were developed accordingly. Subsequently, the most probable and desirable scenarios were selected through expert input via the Delphi panel and Scenario Wizard software. Results: The results of the study indicate that among the 55 variables initially identified, 18 variables were found to play the most significant roles as critical driving forces influencing the quality of life in the metropolis of Tabriz. Among the 269 developed scenarios, five were selected as the most plausible and robust, with the first scenario — exhibiting a relative desirability level of 55 percent identified as the optimal scenario for strategic formulation. Considering that most of the key driving forces in the scenario combinations were in static or critical conditions, the first scenario, with its 55 percent relative desirability, was adopted as the strategic baseline. Accordingly, based on this scenario, the contingent (ST) strategy was determined as the most effective and prioritized strategic approach for enhancing the quality of life in Tabriz. https://geoplanning.tabrizu.ac.ir/article_21719.html The paper is a simulation of the spatiotemporal post-conflict urban growth of a strategic transit hub, Alton Kopri, in the northern region of Iraq, using an integrated Cellular Automata and Logistic regression model (CA-LR). Urbanization with high rates of urban growth after geopolitical stabilization in 2017 has increased pressure on local agricultural lands and riparian ecosystems. We therefore counted a massive increase in the urban footprint, which grew by 353% overall between 2003 and 2024 using multi-temporal Landsat and Sentinel-2 imagery, with an urban footprint presence growing from 8.78 to 39.79 km2. The Logistic Regression model found the Distance to Roads (β = -3.84) and Elevation (β=-6.87) as the main spatial factors, which supports the topographically limited, transportation-based growth trend. The simulation model had excellent validation (Kappa = 0.83; overall LULC accuracy of above 96%). By 2030, three scenarios were projected that included Business as Usual (BAU), River Protection, and Rapid Economic Recovery. Predictions in BAU setting include doubling urban space, which is characterized by ribbon sprawl along the Kirkuk-Erbil highway. It is interesting to note that the River Protection scenario, although successful in preserving the Little Zab ecosystem, led to the creation of a paradoxically greater total urban area (68.282 km2) by moving development into less dense peripheral agricultural areas. These results offer vital decision support indicators to local planners that the densification policy should accompany the policy of conservation of the environment in order to reduce unwanted urban sprawl. https://geoplanning.tabrizu.ac.ir/article_21769.html Urban presence in public open spaces is considered an important indicator of the vitality and dynamism of urban environments and is influenced by environmental quality, spatial organization, and the social characteristics of place. Urban squares are among the most significant public spaces in cities, providing settings for social interaction, collective activities, and everyday urban experiences. However, in many Iranian cities a decline in citizens’ presence and interaction within urban squares has been observed, which may indicate deficiencies in the environmental, functional, and social qualities of these spaces. Therefore, identifying the factors that influence presence in urban squares can contribute to improving the quality of public spaces and enhancing urban vitality. Accordingly, this study examines the impact of environmental quality on urban presence in four major squares of Hamadan: Imam Khomeini Square, Bu Ali Sina Square, Imamzadeh Abdullah Square, and Baba Taher Square. This research is applied in nature and adopts a descriptive–analytical approach using quantitative methods. Data were collected through a researcher designed questionnaire, and the statistical population consisted of citizens using the selected squares. A total of 400 questionnaires were completed through convenience sampling. The collected data were analyzed using statistical tests and structural equation modeling to examine the effects of different dimensions of environmental quality on citizens’ presence. The findings show that all dimensions of environmental quality have a significant relationship with urban presence in public squares. However, the social, physical, and functional dimensions have the strongest influence on citizens’ willingness to visit and remain in these spaces. Squares characterized by diverse activities, perceived safety, suitable accessibility, and the presence of staying spaces demonstrate higher levels of presence and social interaction. Accordingly, enhancing presence in Hamadan’s urban squares requires strengthening social interactions, improving spatial organization, increasing the quality of staying spaces, and promoting environmental comfort. https://geoplanning.tabrizu.ac.ir/article_21807.html Objective: The purpose of this study is to compare and analyze the spatial pattern of leisure in tourism and non-tourism villages in order to determine the impact of tourism on the spatial distribution and concentration of leisure indicators. Methods: The research method is descriptive–analytical, and both spatial and statistical data were collected through a questionnaire and spatial datasets. The statistical population consisted of rural residents of the Dezpart region. Using a convenience sampling method, 246 individuals were determined as the sample size. In the ArcGIS environment, spatial statistical algorithms including Moran’s I, Hot and Cold Spot Analysis, and Spatial Clustering Analysis were used to identify clusters and spatial distribution patterns across the rural areas. Results: The Results revealed a significant difference (p = 0.000) between tourist villages, with a mean rank of 217.5, and non-tourist villages, with a mean rank of 86.5, in terms of the overall leisure time indicators. Furthermore, the results indicated that both active and passive leisure time in tourist villages were significantly better and qualitatively different compared to non-tourist villages. In this regard, the results showed that indicators such as recreational travel, sports activities, family tourism, internet use, and scientific study were also considerably more favorable in tourist villages. Spatial analysis using the hot spot–cold spot algorithm and Moran's I index demonstrated that the observed differences were mainly influenced by the tourism status of the villages, and the spatial pattern was random. Conclusions: These findings underscore that rural tourism is an effective factor in enhancing the quality, diversity, and participation in leisure time, as well as improving the well-being of residents. https://geoplanning.tabrizu.ac.ir/article_21808.html The rapid and accelerated process of urbanization in Iran, particularly in the peripheral areas of coastal cities in southeastern Iran such as Chabahar, has led to significant challenges in these settlements. Assessing the resilience of residents in these areas to cope with such challenges is essential. The present study aims to analyze the status of resilience indicators among residents of Chabahar’s peri-urban neighborhoods (Kamb, Moradabad, and Ramin) from the perspective of local facilitation centers. The research is applied in purpose and descriptive-analytical in method. Data were collected using questionnaires. The statistical population consisted of 12 facilitators working in the facilitation centers of these neighborhoods, all of whom were surveyed through a census approach. Data analysis was conducted using statistical tests including the one-sample t-test, Post Hoc test, and structural equation modeling. The findings indicate slight differences in resilience levels among the neighborhoods. Among the three studied neighborhoods, Ramein demonstrated relatively better resilience compared to Moradabad and Kamb, while Moradabad showed relatively higher social resilience than Kamb. Overall, although the level of social resilience was not particularly high, the differences among the three neighborhoods were minimal. Structural model results revealed that both social and economic conditions significantly influenced social resilience (p < 0.001). However, economic conditions (factor loading = 0.390) had a stronger effect compared to social conditions (factor loading = 0.146) on social resilience in Chabahar’s peri-urban areas. https://geoplanning.tabrizu.ac.ir/article_21821.html Objective: Rapid global population growth and rising demand for affordable housing have made urban housing planning a critical challenge for developing nations. This crisis not only diminishes residents’ quality of life but also triggers severe environmental degradation—depleting natural resources, polluting air/water, accelerating climate change, and destabilizing ecosystems. Many current housing initiatives neglect ecological considerations, underscoring the urgent need for a holistic framework to assess and mitigate environmental impacts during project design and execution. Methods: This study applies descriptive-analytical methods paired with advanced tools (foresight modeling and MICMAC analysis) to examine environmental drivers in low-income housing. Focusing on Iran’s Kouy-e Zangan settlement, it identifies pivotal factors: sustainable material sourcing, water/energy management, disaster-resilient design, and compliance with environmental regulations. Results: These elements are shown to minimize negative externalities and enhance long-term sustainability. Additionally, reviews of global and local precedents highlight that effective policymaking, cross-sector collaboration, and coherent legal structures are essential for scaling sustainable housing. Conclusions: Complementary enablers include stakeholder engagement, stringent environmental benchmarking, and innovative construction technologies—all vital for resilient, eco-friendly solutions. Policymakers are urged to adopt data-driven strategies rooted in sustainability metrics and systematic analysis. Such measures will optimize resource use, shrink environmental footprints, and advance equitable urban development while improving living standards. https://geoplanning.tabrizu.ac.ir/article_21824.html This research adopted an integrated futures-oriented methodology. Key variables affecting the future of water resources—including hydrological indicators, climate change, land-use patterns, socio-economic activities, and water governance mechanisms—were first identified. Expert judgments were then collected and refined through the Delphi method to achieve consensus and finalize the variables. Subsequently, causal–influential relationships among the selected variables were analyzed using structural analysis in MICMAC software to determine their levels of influence and dependence and to identify key drivers and critical uncertainties. Based on these results, the identified key and uncertain variables were entered into Scenario Wizard software, and a cross-impact consistency analysis was conducted to develop internally consistent future.The findings indicate that the realization of rational and coherent scenarios—based on controlled urban development, sustainable population management, groundwater resource restoration, enhanced institutional coordination, and improved policy transparency—can facilitate a transition from the current critical water situation toward relative sustainability. These results provide a futures-based, spatially oriented decision-support framework for informed policymaking in regional water resources management. https://geoplanning.tabrizu.ac.ir/article_21861.html The uncontrolled proliferation of informal settlements has intensified governance deficits as a central concern in urban management. These settlements are typically characterized by informational opacity, weak participatory agency, and distributive inequalities in urban service provision, all of which directly impair residents' quality of life. Achieving good urban governance presupposes institutional efficacy, meaningful citizen engagement, and the implementation of spatial justice policies. However, in many Iranian metropolises—including Tabriz—these principles encounter multiple path-dependent institutional rigidities and structural impediments. This study aims to assess the status of good urban governance within the informal settlements of Tabriz Metropolis.A convergent parallel mixed-methods design was employed, integrating quantitative and qualitative techniques. In the quantitative phase, data were collected via 390 structured questionnaires and analyzed using one-sample t-tests, exploratory factor analysis (EFA), and multivariate regression models. In the qualitative phase, thematic analysis of citizens' narratives was conducted to identify the underlying challenges of urban management and governance. The findings indicate that all indicators of good urban governance in Tabriz's informal settlements fall significantly below the normative threshold. The equitable distribution of urban services exerts the strongest positive effect on citizen satisfaction (β = 0.572). Conversely, social participation and transparency of urban information demonstrate adverse effects, attributable to procedural deficiencies and implementation gaps. Thematic analysis further reveals that accountability voids among urban managers, tokenistic participatory mechanisms, and the spatial misallocation of urban services constitute the most critical governance challenges in these areas. Improving good urban governance in the informal settlements of Tabriz Metropolis necessitates institutional restructuring, enhanced transparency mechanisms, recalibration of participatory policies, equity-oriented reallocation of urban resources, integration of urban digital governance platforms, and the expansion of citizen-led monitoring systems. Such interventions can contribute to enhancing residents' quality of life and restoring public trust in urban management. https://geoplanning.tabrizu.ac.ir/article_21867.html Objective: Urban tourism is one of the most dynamic and rapidly growing sectors of the tourism industry, which has gained increasing importance in recent years. The urban environment plays a crucial role in shaping tourists’ experiences, perceptions, and behaviors, influencing how visitors interact with urban spaces and residents. Despite its significance, few studies have directly examined how indicators of urban environmental psychology affect tourists’ citizenship behavior. Therefore, this study aims to evaluate the impact of urban environmental psychology dimensions on tourists’ citizenship behavior in Babolsar. Methods: This applied research uses a descriptive–analytical approach. Data were collected from 385 domestic tourists traveling to Babolsar using a questionnaire and simple random sampling. Additionally, the questionnaire was confirmed in terms of reliability Cronbach’s alpha (α= 0.958), convergent validity (AVE > 0.5), and discriminant validity (HTMT < 0.90). The collected data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine relationships among latent variables associated with urban environmental psychology and tourists’ citizenship behavior. Results: The results of this study indicate that psychological indicators of the urban environment had a significant impact on tourists’ citizenship behaviors. Among these indicators, the perceptual dimensions of the urban environment had the strongest influence, followed by the social and visual dimensions, while the physical dimensions of the urban environment showed no significant effect. Conclusions: The present study bridges the research gap between urban planning, environmental psychology, and urban tourism. It demonstrates how urban environmental psychology indicators can enhance tourists’ overall experiences and promote their engagement in citizenship behaviors, including recommendation and feedback, in urban destinations. https://geoplanning.tabrizu.ac.ir/article_21895.html Objective: The objective of the present study is the effect of urban culture on urban innovation with the mediating role of urban strategic management in Shahrekord. Methods: This study is a descriptive survey of the field branch in terms of data collection method and is applied in terms of purpose. The statistical population of the present study includes all citizens of Shahrekord, 190,441 people. The sample size was selected based on the Cochran formula as 383 people. The research tool includes a 32-question questionnaire in three sections: urban culture with 20 questions, urban innovation with 5 questions, and urban strategic management with 7 questions. Its validity has been examined and confirmed in a formal, structural, and content manner, and its reliability has been confirmed based on the Cronbach formula at 0.87. The collected data were analyzed based on structural equation path analysis in Smart PLS software. https://geoplanning.tabrizu.ac.ir/article_21896.html Assessing spatial justice in tourism requires analyzing the spatial configuration of services across different spatial scales, as merely counting facilities cannot adequately reflect patterns of spatial balance or inequality. This study aims to examine the spatial distribution of tourism services in the rural areas of Binalood County (Torqabeh–Shandiz) and to interpret its implications for spatial justice. The research is applied in purpose and descriptive–analytical in method. The statistical population consisted of 54 villages, of which 35 villages (17 tourism-oriented and 18 less tourism-oriented) were selected through purposive sampling. Spatial data—including eco-lodges, restaurants and cafés, cultural sites, and historical attractions—were collected from official sources, field surveys, and satellite imagery and validated through multi-source cross-verification. Spatial analyses were conducted using the Nearest Neighbor Index (NNI) and Global Moran’s I in ArcGIS. The NNI results reveal statistically significant clustered patterns for all service categories at the local scale (NNR < 1; p < 0.01). The highest clustering intensity was observed for eco-lodges (NNR = 0.33; Z = -14.24) and restaurants and cafés (NNR = 0.32; Z = -17.53), indicating strong spatial concentration in specific nodes. Public services (NNR = 0.49) and historical sites (NNR = 0.54) also exhibited clustering but with lower intensity. At the regional scale, Global Moran’s I confirmed a polarized spatial structure only for market-driven tourism services. Eco-lodges (I = 1.65; p < 0.001), restaurants and cafés (I = 0.97; p < 0.001), and cultural sites (I = 0.97; p = 0.003) showed significant positive spatial autocorrelation, whereas public services (p = 0.96) and historical sites (p = 0.32) lacked spatial dependence and followed random distribution patterns. The findings indicate a multi-scalar spatial differentiation: while local-scale clustering is ubiquitous, only market-oriented tourism activities form structured regional hubs. From a spatial justice perspective, https://geoplanning.tabrizu.ac.ir/article_21901.html Third places—public arenas mediating between the private sphere of home and the formal environment of work—play a vital role in shaping urban social dynamics, fostering collective capital, and operationalizing social sustainability goals. This study aims to conduct a comprehensive structural analysis and precisely delineate the intellectual landscape of the emerging interdisciplinary intersection of "third places" and "social sustainability" in international scholarship. The methodology employs a bibliometric approach and scientific mapping techniques. Data from 186 scholarly documents indexed in Scopus (1987–2026) were processed using VOSviewer 1.6.20, followed by network analysis and scientometric visualization generation. The findings reveal multiple patterns: exponential growth in publications, particularly accelerating after 2019; pronounced geographical concentration of knowledge production in specific developed countries (the United States, the United Kingdom, and Australia) alongside a deep participation gap from developing nations; identification of six distinct thematic clusters centered on urban social sustainability, spatial justice, collective well-being, social capital, local governance, and resilience; and a low-density, project-oriented structure in the international co-authorship network. Temporal trend analysis also indicates a cognitive shift from purely theoretical discourses toward contemporary applied areas, including urban resilience in crises and the role of hybrid digital-physical spaces. In conclusion, this research redefines third places as essential "soft" social infrastructures for achieving resilient and equitable cities. Accordingly, it emphasizes that formulating and implementing integrated urban policies to support these spaces—particularly in recognizing their role in enhancing social health and neighborhood cohesion—is imperative. Furthermore, directing future research toward context-sensitive and comparative studies in underrepresented geographies is essential to fill knowledge gaps and ensure more equitable outcomes in urban social sustainability. These constitute additional key findings of this investigation. https://geoplanning.tabrizu.ac.ir/article_21934.html Food security is a key component of human health and sustainable development, and remains a major global challenge under conditions of climate change and environmental degradation. This study aims to assess spatial patterns of food security in rural areas of the East Azerbaijan Province, Iran, using a GIS-based multi-criteria decision analysis (GIS-MCDA) framework. The model integrates the several steps of the implementation environmental and socio-economic indicators including criteria selection, standardization, criteria weighting based on the fuzzy analytic network process, sensitivity analysis and criteria aggregation using the ordered weighted averaging method. For this goal, a total of 21 criteria representing climatic, topographic, agricultural, and land-use conditions were used to develop a food security map in East Azerbaijan Province, Iran. The results indicate that 544 villages (22.15% of the rural population) are located in high and very high food secure zones, while 1,905 villages (57%) fall within food insecure areas. The remaining villages are classified as moderately secure. The findings highlight strong spatial disparities in food security, mainly driven by environmental constraints and agricultural conditions. The proposed framework provides a critical decision-support approach for regional planning and sustainable food security management under climate change conditions. https://geoplanning.tabrizu.ac.ir/article_21938.html Today, food tourism is one of the fastest growing segments of the tourism market and covers many aspects of the food and tourism industries. Most tourists are motivated by food travel, From the perspective of sustainable development of local food tourism, local foods havepotential to improve the competitiveness of destinations. Therefore, food tourism can provide a deep experience for tourists, then go through different models and stages of development in several countries around the world. This research is classified as qualitative-quantitative research in terms of its development goal and in terms of the method of data collection and analysis. Initially, since the aim of the present research is primarily to design and explain the sustainable development model of local food tourism in Tabriz city and for this purpose, there is a need for qualitative data, a qualitative approach using content analysis was chosen in the first step to identify the elements of the model under study. In the second stage, to validate the presented model after exploring the elements of sustainable development of local food tourism, quantitative methods and structural equation models were used to refine and review them. As research findings, the factors of sustainable development of local food tourism were categorized into 8 main themes, namely economic sustainability, social sustainability, cultural sustainability, environmental sustainability, ethical sustainability, political sustainability, educational sustainability and creative and innovation sustainability. And using the structural equation model, a model of sustainable development of local food tourism from the perspective of tourists in Tabriz was presented. The results can increase the knowledge of managers and officials in the field of local food tourism regarding the sustainable development of local food tourism and provide practical guidelines for managers, officials, planners and policymakers of sustainable development of local food tourism at different national and regional levels. https://geoplanning.tabrizu.ac.ir/article_21945.html Objective: Good urban governance, as a key concept in urban management, plays an important role in sustainable development and improving the quality of life of citizens. This concept is based on the principles of transparency, accountability, participation, rule of law, efficiency, and justice. In fact, achieving good urban governance requires identifying and strengthening the key drivers affecting it. In this regard, the aim of the present study is to explain the key drivers affecting good urban governance in Kermanshah city. This study attempts to identify the factors affecting good urban governance using scientific methods and considering the specific conditions of Kermanshah city and provide strategies for strengthening them. This research also seeks to identify strategic and key variables by managing them, which can prevent critical scenarios and draw an operational roadmap for future-oriented management in Kermanshah metropolis. Research Method: The present study is applied in terms of purpose and descriptive-analytical in terms of method. Data collection tools are library sources and documents and surveys (questionnaire with Cronbach's alpha reliability higher than 0.7). The research area is Kermanshah city and the statistical sample of this study is 50 experts and specialists in the field of urban and urban management. Results: Data analysis using Delphi and Mi'kmaq methods showed that among the 46 parameters affecting good urban governance in Kermanshah, 17 factors were identified as key drivers that have the greatest impact on the future. Conclusion: The main findings emphasize that the sub-indicators of reducing costs and improving the quality of services, transparency of municipal performance, and attracting participation through accountability of managers have the highest direct impact on the realization of good urban governance in Kermanshah. Therefore, strengthening these key drivers, especially through active citizen participation, transparency, and increased efficiency, is essential to improve urban management in this metropolis https://geoplanning.tabrizu.ac.ir/article_21946.html Selecting an appropriate location for urban development is crucial due to geomorphological hazards. Active faults, slope and elevation, proximity to earthquake epicenters, and drainage networks represent the most significant constraints for urban expansion. These factors may induce earthquakes, landslides, floods, and erosion, threatening urban infrastructure and hindering sustainable development. Therefore, identifying and analyzing geomorphological hazards is an essential prerequisite for accurate site selection in urban planning. This study aims to identify suitable lands for physical development in Bostanabad city. Four main factors were assessed, including topography (elevation, slope, slope aspect), geology (lithology, distance from faults, distance from epicenters), hydrology (distance from main and secondary waterways), and human factors (land use, distance from roads and communication lines), represented by ten sub-criteria. The Analytic Hierarchy Process (AHP) was applied for weighting, and a zoning map was generated. Results showed that the distance from earthquake epicenters had the highest weight (0.232), followed by the distance from faults (0.179) and the distance from main waterways (0.161). The analysis revealed that suitable areas for urban development are primarily scattered across central, southeastern, southwestern, and parts of northeastern Bostanabad. In contrast, the northern sector, influenced by the Tabriz North Fault, is not appropriate for development. Overall, highly suitable and suitable zones account for 39.85% (30.36 km²), relatively suitable zones for 19.97% (15.21 km²), while relatively unsuitable and unsuitable zones comprise 40.18% (30.6 km²) of the study area. https://geoplanning.tabrizu.ac.ir/article_21967.html Physical transformations of rural settlements are driven by the interaction of economic, socio-cultural, infrastructural, and environmental factors within broader processes such as urbanization, industrialization, and changing livelihood patterns. In Jam County, the expansion of the oil and gas industries, increasing intra-regional migration, and the growth of service and construction activities have significantly reshaped the spatial and physical structure of rural settlements. This study aims to analyze the factors influencing the physical transformations of rural settlements in Jam County. The research is applied in purpose and adopts a descriptive–analytical approach. Data were collected through documentary research and field surveys. The statistical population comprised 8,530 rural households in villages with more than 20 households, from which 368 households were selected using Cochran’s sampling formula. Since the data were not normally distributed, Spearman’s rank correlation coefficient, Kendall’s tau-b correlation coefficient, the coefficient of variation, the chi-square test, and Cramér’s V statistic were employed for data analysis. The findings revealed significant positive relationships among the examined indicators. The strongest correlation was observed between physical transformations and the economic indicator (0.709), followed by building materials and architectural design and the economic indicator (0.645), whereas the weakest relationship was found between infrastructure and the socio-cultural indicator (0.288). The coefficient of variation (21.8) indicated variations in the intensity of physical transformations among the studied villages, which were classified into four structural groups. Villages located in the Central District of Jam County experienced the greatest degree of transformation. Overall, the findings identify economic factors as the primary driving force behind physical transformations. Sustainable rural development therefore requires strengthening local economic foundations, improving land-use management, conserving the rural physical fabric, enhancing community participation, and promoting rural tourism while preserving vernacular architecture. https://geoplanning.tabrizu.ac.ir/article_21971.html Flooding, as one of the most destructive natural disasters, causes significant loss of life and property annually in various regions worldwide, particularly in the semi-arid areas of Iran. In this context, accurate flood risk modeling plays a decisive role in the planning and risk management of this phenomenon. This research aims to assess and map flood risk in the Darab watershed, utilizing the Support Vector Machine (SVM) and Random Forest (RF) machine learning algorithms within the GIS environment and the R programming language, to compare the performance of these two models in spatial analysis. For this purpose, a comprehensive spatial database was compiled, including environmental indicators (soil type, geology, distance to road, NDVI), hydrological indicators (drainage density, distance to river, stream power, NDWI, TWI, SPI, and WRI), and topographical indicators (elevation, slope, aspect, and slope length). The results of the model performance evaluation indicated that both algorithms possess a suitable accuracy in identifying spatial flood patterns; however, the RF model demonstrated higher accuracy compared to SVM (R² = 0.8906 vs. R² = 0.875). The RF model identified approximately 71% of the watershed area as very low and low-risk zones, which aligns with the actual flood occurrence patterns (concentrated around the river channels and lower-lying areas of the watershed). In contrast, the SVM model, emphasizing the correlation between hydrological indicators and remote sensing data, classified nearly 77% of the watershed area into medium to very high-risk categories, primarily in the central and eastern parts of the basin. These findings highlight the high efficiency of machine learning algorithms, particularly the RF model, in flood risk modeling, confirming their superiority over traditional physical and semi-empirical methods like HEC-RAS in terms of performance, speed, and reduced need for field data. https://geoplanning.tabrizu.ac.ir/article_21990.html Objective: Accurate monitoring of snow cover, a critical component of the hydrological cycle in mountainous regions, is essential for water resource management and climate change assessment. This study evaluates and compares the performance of five snow indices—Normalized Difference Snow Index (NDSI), S3, Snow Ratio Index (SRI), Normalized Difference Snow Water Index (NDSWIn), and Snow Surface Reflectance (SSR)—for snow cover extraction using Sentinel-2 and Landsat 8/9 imagery in the Ardabil and Marivan regions of northwestern Iran. Methods: Six satellite images acquired between 2022 and 2025 were processed via Google Earth Engine. Snow cover maps were generated for each index, and classification performance was assessed using 200 reference points, employing Overall Accuracy (OA) and Kappa coefficient metrics. Results: All indices detected snow-covered areas; however, S3 and NDSWIn consistently achieved the highest accuracy across both sensors and regions. In Ardabil, their mean OA exceeded 99% with Kappa ≈ 0.99. Landsat 8/9 generally outperformed Sentinel-2 in accuracy and temporal stability, while SSR showed the highest variability and lowest performance throughout the study period. Conclusions: S3 and NDSWIn are the most reliable and effective indices for snow cover mapping in mountainous regions of northwestern Iran, supporting operational snow monitoring using multispectral satellite imagery. https://geoplanning.tabrizu.ac.ir/article_22000.html Objective: The risk of land subsidence can always have different causes, including dissolution, compaction of deposits, slow ground movements, excessive extraction of groundwater or human operations such as mining and extraction of oil and gas resources. In this study, Sentinel 1 radar images from 2016 and 2024 were used to assess subsidence in the Mallard Plain, and SARSCAPE software was used to process the information. Among the results of this study, we can mention the findings of this study using piezometric data, which, according to the interpolation map, the groundwater level of the plain has a downward trend despite seasonal fluctuations. The results of the water level survey showed that a 6-meter decrease in groundwater level can be observed over 8 years. A study of the subsidence situation in the last five years from 2014 to 2024 in the study area shows that the maximum subsidence is 9 cm, this issue can mainly be attributed to the issue of groundwater extraction for drinking water, agriculture and possibly other influential factors such as geology and related tectonic features. A 9 cm subsidence for residential use can provide unsafe living conditions for residents and increase their risk of land hazards. https://geoplanning.tabrizu.ac.ir/article_22001.html Objective: In recent years, accurate extraction of surface water areas from satellite images has gained special importance due to their key role in water resources management and environmental monitoring. Despite development of numerous spectral indices for water identification, performance of these methods in vast mountainous and heterogeneous areas is often limited by spectral interference, shadow and dark surfaces. Methods: In this study, an integrated framework based on the combination of common spectral indices including NDWI, MNDWI, AWEI_sh, AWEI_nsh and WRI along with Landsat-8 OLI multispectral raw bands is presented for extracting surface water areas. Then, the support vector machine (SVM) algorithm was used as a machine learning method to optimally integrate feature space and separate water and non-water classes. Reference data were prepared from a combination of field observations, visual interpretation of high-resolution images, and Open Street Map (OSM) vector data, and spatial dependence of the samples was reduced by applying quality filters and spatial compression. Results: Model performance evaluation using quantitative criteria including Recall: 90%, IOU: 53%, and Dice: 70% showed that model provides stable performance in identifying water bodies. SVM model was able to obtain a Recall value of 0.90 for water class, which indicates high power of the model in correctly identifying most of real water pixels. Also, Dice value of 0.70 and IoU of 0.53 indicate moderate to acceptable spatial agreement between the predicted map and reference data. Conclusions: Results indicate that enriching feature space by combining raw bands and spectral indices plays a key role in improving continuous and accurate identification of water body boundaries. This framework can be used as an efficient and reliable method for extracting surface water areas in complex and large-scale areas and support decision-making in water resources management. https://geoplanning.tabrizu.ac.ir/article_22021.html Objective: In Tehran, despite the abundance of health care centers, residents do not benefit equitably from healthcare services due to an inappropriate distribution of services at the neighborhood level. What is immediately apparent is the disproportionate and unjust distribution of services across Tehran. However, the specific spatial distribution of health care services at the neighborhood level remains unclear. Therefore, the aim of the present study is to analyze the spatial pattern of healthcare service centers in Tehran. Methods: This research is applied in terms of objective and descriptive-analytical in terms of method. Data and information were collected using library research. Spatial statistical analysis methods employed for data analysis. In this study, four main indicators explaining healthcare services, including hospitals, clinics, pharmacies, and health houses, were examined. Results: The results of spatial autocorrelation tests for the four healthcare service indicators demonstrate a clustered spatial distribution pattern for hospitals, clinics, and pharmacies, and a random spatial pattern for health houses across Tehran. The hot spot analysis results for hospitals, clinics, and pharmacies indicate that neighborhoods primarily located in the north, center, and to some extent the east of Tehran are hot spots and concentration areas for the highest number of healthcare service centers. Conversely, the southern and eastern parts of Tehran represent hot spots and concentration areas for neighborhoods with the highest population density. Conclusions: The spatial distribution of healthcare centers in Tehran does not align with population density. Furthermore, the southern and eastern areas of Tehran, which have the highest population density, are in a less favorable position regarding access to healthcare services. This imbalance signifies a form of spatial inequality in the provision of health care services, which could lead to serious social and long-term consequences. https://geoplanning.tabrizu.ac.ir/article_22035.html This study aims to analyze stakeholder perception gaps regarding sustainable tourism-led regeneration in the historic Oudlajan neighborhood of Tehran. It examines differences in the perceptions of three key stakeholder groups—residents, tourists, and urban experts/managers—across the principal dimensions of sustainable tourism regeneration and identifies the dimensions with the greatest perceptual disparities. It also evaluates the degree of convergence and divergence among stakeholders’ perceptions in the economic, socio-cultural, physical-spatial, environmental, and managerial dimensions to provide practical implications for improving regeneration policies. This applied study adopts a descriptive–analytical design with a quantitative approach. Data were collected through a structured questionnaire using a five-point Likert scale. Based on Cochran’s formula, a sample of 384 respondents was selected, including 220 residents, 100 tourists, and 64 urban experts/managers. Simple random sampling was used for residents, convenience sampling for tourists, and purposive sampling for experts and managers. Data were analyzed using SPSS through the Kolmogorov–Smirnov and Shapiro–Wilk tests, the Kruskal–Wallis test, Spearman’s rank correlation, exploratory factor analysis, and exploratory multiple regression analysis. The findings indicate statistically significant differences in stakeholders’ perceptions of sustainable tourism regeneration. The largest perception gaps were found in the economic (χ² = 10.41, p = 0.005) and socio-cultural (χ² = 8.92, p = 0.012) dimensions, whereas no significant difference was observed in the environmental dimension (p = 0.176), suggesting relatively strong perceptual convergence. Differences among stakeholder groups were primarily associated with perceived economic benefits and the social impacts of regeneration. The results demonstrate that the main challenge of sustainable tourism regeneration in Oudlajan stems from stakeholder perception gaps rather than deficiencies in any single dimension. Strengthening participatory mechanisms, promoting integrated governance, and adopting balanced regeneration strategies can reduce perception gaps, enhance stakeholder consensus, and improve the long-term sustainability and effectiveness of tourism-led regeneration in historic urban districts. https://geoplanning.tabrizu.ac.ir/article_22091.html Outgoing Longwave Radiation (OLR) is a fundamental component of Earth's energy budget, playing a critical role in climatic studies and environmental changes. This research was conducted to analyze the temporal variations and spatial patterns of OLR within the Lake Urmia basin over the period from 1987 to 2024. Monthly OLR data with a spatial resolution of 1° × 1° were extracted from NASA's Giovanni system and applied to the basin area and the locations of regional meteorological stations. For data analysis, statistical methods including the Standard Normal Homogeneity Test (SNHT), trend analysis via linear regression and the Mann-Kendall test, and geostatistical techniques (Inverse Distance Weighting (IDW) interpolation and Geographically Weighted Regression (GWR)) were employed. The results indicated that the annual mean OLR in the region exhibited a significant increasing trend with a slope of 0.1095 W/m² per year, with the most pronounced increases observed during the summer and autumn seasons. Structural breakpoints in the seasonal time series were identified in 1993, 1998, and the 2002–2004 period. The spatial pattern of OLR decreases from the southwest to the northeast of the basin, with the central and southwestern regions experiencing the highest values. The GWR model revealed that the relationship between OLR and spatial location is non-stationary across the basin, providing a significant improvement in predictive accuracy compared to the global model. Variations in OLR in the region may be influenced by factors such as the receding water level of Lake Urmia and changes in land use. https://geoplanning.tabrizu.ac.ir/article_22105.html Objective: The objective of this study is to analyze and map landslide susceptibility in the Shalmanrud watershed, Guilan Province, Iran, using machine learning algorithms including Support Vector Machine (SVM), Random Forest (RF), and Gradient Tree Boosting (GTB). Methods: First, effective factors influencing landslide occurrence such as elevation, lithology, slope, slope aspect, distance to stream, distance to fault, distance to road, slope curvature, precipitation, and vegetation cover were compiled using remote sensing data, the 30-meter ASTER Digital Elevation Model (DEM), and other authoritative sources, followed by processing in Geographic Information System (GIS) and Google Earth Engine (GEE) environments. For modeling purposes, 450 identified landslide points were utilized as dependent variables and, along with non-landslide points, were randomly divided into training (70%) and validation (30%) datasets. Subsequently, the SVM, RF, and GTB models were trained within GEE to generate continuous landslide susceptibility maps. These maps were categorized into five susceptibility classes (ranging from very low to very high) using the natural breaks classification method. Results: The results demonstrated that the spatial pattern of landslide hazard in the study watershed exhibits a decreasing trend from south to north. High-risk zones are predominantly concentrated in the southern and southwestern areas, characterized by steep slopes, high elevation, and unstable lithology, whereas northern regions display lower risk and relative stability. Model comparison revealed that all three algorithms achieved excellent performance in predicting landslide-prone areas, with Area Under the Receiver Operating Characteristic Curve (AUC-ROC) values of 0.999, 0.997, and 0.998 for RF, SVM, and GTB, respectively. Conclusions: Overall, the findings highlight the high accuracy and reliability of these models in landslide susceptibility mapping. Variable importance analysis indicated that slope angle plays the most critical role in landslide triggering. These findings can be effectively applied to mitigate landslide-induced damages in similar geographic settings. https://geoplanning.tabrizu.ac.ir/article_22111.html Objective:The aim of this study is to explore the internal and external factors influencing the competitiveness of rural tourism development in Mazandaran Province Methods: This study is applied in terms of purpose and qualitative in terms of methodology. It was conducted using an exploratory approach within the framework of grounded theory. In this regard, 20 experts in the field of tourism planning were selected through purposive sampling and interviewed using semi‑structured interviews. In addition, direct observation, document analysis, and the researchers’ experiential insights were also employed. The collected data were subsequently analyzed through qualitative content analysis. Results: Through axial coding and the development of a narrative storyline, 5 categories, 14 sub‑categories, and 35 concepts related to the internal and external barriers to the competitiveness of rural tourism development in Mazandaran Province were identified. In examining internal factors, 5 categories, 17 sub‑categories, and 24 concepts were extracted, while external factors were classified into 6 categories, 12 sub‑categories, and 32 concepts. Ultimately, a framework and a set of strategies for improving the competitiveness of rural tourism development were proposed, consisting of 5 categories, 18 sub‑categories, and 56 concepts. The resulting model indicates that both internal and external factors are shaped by a set of environmental, economic, socio‑cultural, physical‑infrastructural, and policy‑institutional endowments, which collectively provide diverse strategic pathways for enhancing the competitiveness of rural tourism in Mazandaran Province. Conclusions: The findings indicate that the competitiveness of rural tourism in Mazandaran is the result of a complex interaction between internal and external factors operating across environmental, economic, socio‑cultural, physical‑infrastructural, and institutional dimensions. Accordingly, the extracted model proposes a set of multidimensional and integrated strategies aimed at strengthening and improving the competitiveness of rural tourism development in the province. https://geoplanning.tabrizu.ac.ir/article_22143.html Objective:Digital transformation as a key requirement of contemporary local governance has significant potential to improve rural development outcomes.This study aims to examine the status of digital transformation and local governance within rural administrations (Dehyaries) and to analyze their effects on rural development in the villages of Borujen County, Iran. Methodology:This study is applied in terms of objective and adopts a descriptive-analytical methodology. Data were collected through a field-based survey using a researcher designed questionnaire.The statistical population included all Dehyars of 25 villages with populations exceeding 100 persons, and a census approach was adopted. Instrument validity was confirmed through expert judgment, and reliability was verified using Cronbach’s alpha.Data analysis employed one-sample t-tests to compare the observed mean scores of the variables against the scale midpoint of 3. and multivariate regression analysis to explain variations in rural development. Results:The findings indicate that local governance indicators, including efficiency and effectiveness (mean=3.15), electronic participation and interaction (mean=3.08), and transparency and accountability (mean=3.15), were above average.Regarding digital transformation, digital infrastructure and access (mean=3.06) and digital organizational culture (mean=3.15)were evaluated as desirable,whereas the application and diffusion of key digital technologies (mean=2.93) remained undesirable.Regression results showed that digital transformation components explained approximately 69 percent of the variance in rural development, with digital infrastructure and access having the strongest effect (β=0.335). Conclusion:Overall, the results emphasize the central role of digital infrastructure and digital organizational culture in strengthening rural governance and promoting sustainable rural development.Nevertheless, insufficient utilization of advanced digital technologies remains a major challenge for rural administrations. Addressing this gap requires targeted capacity-building, institutional support, and policy interventions focused on technology adoption, interoperability, and participatory service delivery.These findings provide practical implications for policymakers seeking to enhance the effectiveness of digital transformation strategies in rural governance systems. And they contribute to evidence-based decision-making in local rural development planning processes. https://geoplanning.tabrizu.ac.ir/article_22163.html Abstract Informal settlements are one of the fundamental challenges facing urban planning systems in developing countries and require effective intervention policies such as “formalization.” However, reducing this policy to physical measures and administrative procedures for issuing property documents has, in many cases, hindered the achievement of sustainable urban development. This study aims to deeply investigate the challenges and opportunities of the formalization process and identify the explicit and implicit dimensions affecting the organization of informal settlements. The study adopted a qualitative approach using thematic analysis. To collect data, relevant articles and studies were identified through Scopus, Web of Science, ScienceDirect, Google Scholar, and SID and selected after content evaluation. The selected texts were then organized, coded, and analyzed thematically using MAXQDA 2020. In this process, 115 initial codes were extracted and classified into 14 organizing themes, comprising seven challenging and seven opportunity-oriented themes. The findings indicated that, among the major barriers, themes such as “structural and institutional gaps,” “economic barriers,” “incompatibility of laws and regulations,” and “weak social participation” were prominent. In contrast, the development drivers included “resident empowerment,” “strengthening social capital,” “economic resilience,” and “spatial justice.” The results indicate that the success of formalization requires a shift from exclusionary and project-oriented approaches toward a comprehensive, process-oriented, and community-based approach. Establishing a one-stop urban management system, employing microfinance models, strengthening local and civil institutions, and adopting a gradual upgrading strategy can facilitate the activation of local capacities, improvement of quality of life, and sustainability of the formalization process. https://geoplanning.tabrizu.ac.ir/article_22182.html Objective: Climate change and its consequences on the increasing frequency and intensity of extreme weather events are among the most important contemporary environmental challenges. Methods: In this study, daily maximum temperature data for the Tabriz station for the period of 2000 to 2024 were received from the Iran Meteorological Organization, and the extreme temperature threshold was determined using the 95th percentile. To identify the synoptic patterns affecting extreme days, sea level pressure and 500 hPa geopotential height data were extracted from the NOAA database and classified using the Ward hierarchical clustering method and Euclidean distance. Three main patterns were identified and examined by analyzing geopotential height, sea level pressure, omega, relative humidity, and temperature maps at 500 and 850 hPa levels. For future assessment, potential heatwaves for the 2025 to 2050 period were estimated using the Delta statistical downscaling method, based on the output of the MPI-ESM1-2-HR model under SSP2-4.5 and SSP5-8.5 scenarios. Results: The establishment of thermal lows over the Arabian Peninsula, Iraq, and Pakistan, accompanied by the strengthening of the Azores subtropical ridge at the 500 hPa level, by creating subsidence and transferring hot desert air, has been the main factor for heatwaves in Tabriz. The results of the scenarios indicate the intensification of thermal conditions in the region in the future; in the SSP2-4.5 scenario, an increasing trend of days with temperatures above 36°C was observed with a slope of about 0.37 days per year, while in the SSP5-8.5 scenario, more severe events and longer heatwave periods are predicted. Conclusion: The results show that extreme heat events are mainly concentrated in July and August, and the probability of occurrence and intensity of heatwaves in Tabriz will increase in the coming decades. https://geoplanning.tabrizu.ac.ir/article_22183.html Fog, a critical meteorological phenomenon, plays a supplementary role in meeting vegetation water demands during the summer season, particularly in areas with minimal or absent precipitation. This study examines the temporal behavior of foggy days in the eastern region of Ardabil over a two-decade span from 2003 to 2022, focusing specifically on summer months. Given the unavailability of a synoptic station within the defined spatial scope, MODIS satellite data were utilized to detect fog occurrence. To evaluate temporal trends, non-parametric statistical tools—namely the Mann-Kendall test and Sen’s slope estimator—were applied. The findings indicate that, on average, summer experiences approximately 20 foggy days. The Mann-Kendall test for the summer season yielded a Z value of 0.43, suggesting no statistically significant trend in foggy days at the 95% and 99% confidence levels. Similarly, Sen’s slope estimator produced a Q value of zero, indicating no meaningful increasing or decreasing trend at these confidence levels. The graphical Mann-Kendall test also confirmed the absence of a statistically significant trend at the 95% confidence level. It is noteworthy that the repeated intersection of two curves within the ±1.96 range implies that the average number of foggy days varies annually during summer. The Sen’s slope trend line appears flat, with an R² of zero, reinforcing the conclusion that no significant trend exists in the number of foggy days during summer in eastern Ardabil Province. https://geoplanning.tabrizu.ac.ir/article_22185.html Objective: The aim of this study was to analyze the structural relationships between the social and economic dimensions of the damages of informal settlements in Tabriz metropolis using structural equation modeling (SEM). Methods: The present study is applied in terms of purpose and descriptive-correlational in terms of method, and was conducted as a survey among 384 residents of 12 marginal neighborhoods in the north and northwestern part of Tabriz. Data were collected using researcher-made questionnaires and analyzed with Smart-PLS version 4 software. Results: The findings showed that contextual factors (age, education, occupation, and length of residence) have a direct and significant effect on economic and socio-cultural damages. In particular, economic damages act as a powerful mediating variable and explain 71.5% of the total effect of contextual factors on socio-cultural damages. The overall model fit index (GOF) showed a value of 0.695, indicating a strong model fit. Conclusions: In general conclusion, it can be emphasized that approaches to organizing these settlements should include integrated strategies that simultaneously address economic dimensions (through job creation and economic empowerment) and socio-spatial dimensions (through physical-social integration and promotion of environmental security). https://geoplanning.tabrizu.ac.ir/article_22242.html this research Inspired by the concept of "biodiversity hotspots," this study aims to identify and prioritize "geodiversity hotspots" in the Joghatay Heights (western Khorasan Razavi Province, Iran), an area characterized by ophiolitic nature and complex geological history. Methods: The research methodology consists of three stages: (1) calculation of the Geodiversity Index (GI) by integrating four components—geology, geomorphology, soil, and hydrology—within a 400-hectare hexagonal grid; (2) calculation of the Threat Index (TI) based on protection level, land degradation degree, and land use type; and (3) combination of these two indices through multiplication to generate the Sensitivity Index (SI) and identify hotspots. To optimize computations, the GI grid was converted into a continuous raster surface using Ordinary Kriging interpolation with a spherical model (range = 1200 m), at a pixel size of 100 × 100 meters, to ensure alignment with the 1:25,000 base map scale and the minimum geological feature size . Results: Results indicated that the geological component contributes the most to the region's diversity, with the Joghatay Heights serving as the core of geodiversity. Hotspots are predominantly concentrated in the eastern half and adjacent to urban centers (Sabzevar, Joghatay, Neqab, Davarzan, Soltanabad, and Nodeh-e Enqelab), where the highest geological diversity coincides with the greatest degree of anthropogenic threats (particularly mining, agricultural expansion, and settlement growth). Approximately 9.3% of the area exhibits very high geodiversity and 11.5% shows high geodiversity, mainly corresponding to highlands and areas with active faults. Conclusions: Findings reveal that the most geodiverse regions (such as active chromite mines) are also among the most threatened, underscoring the urgent need for conservation intervention. Establishing a western Khorasan Geopark centered on the Joghatay Heights is recommended as a strategy for sustainable protection of this valuable heritage. https://geoplanning.tabrizu.ac.ir/article_22243.html Job creation in rural areas, especially in less-developed regions, is considered one of the fundamental priorities for achieving sustainable development. Nahzatabad District in Rudbar-e-Jonub County, which faces a high unemployment rate, necessitates the implementation of effective employment policies. In this context, the provision of microcredits and self-employment loans by institutions such as the Imam Khomeini Relief Committee has emerged as a supportive strategy. This study aims to assess the impact of self-employment loans from the Relief Committee on the development of local businesses and the improvement of rural household livelihoods in the region. The research method is descriptive-analytical and applied in terms of its objective. Data were collected through questionnaires and official sources, and analyzed using one-sample t-tests and multivariate regression. The statistical population includes all 220 households that received loans in Nahzatabad District. The findings indicate that the main businesses created using these loans include greenhouse farming (25.5%), cattle raising (21.8%), and sheep or goat raising (18.6%). Other economic activities such as handicrafts, carpet weaving, tailoring, and small-scale retail accounted for 34.1% of the created jobs. Statistical analysis using one-sample t-tests revealed a significant impact of self-employment loans on self-employment rates, household income, and savings. Furthermore, regression and ANOVA tests confirmed a strong and significant relationship between loan provision and household job creation. Therefore, microcredits from the Imam Khomeini Relief Committee play a crucial role in strengthening self-employment, increasing income, and improving the economic condition of rural households, and can be regarded as an effective tool for rural sustainable development. https://geoplanning.tabrizu.ac.ir/article_22244.html Objective: Considering the high uncertainty of Snow Cover Area (SCA) in mountainous regions with complex topography, this study aimed to improve snow discrimination from other land surfaces through the combination of spectral indices and metaheuristic optimization algorithms. Methods: Landsat 8 satellite images from Alborz and Chaharmahal and Bakhtiari provinces, acquired in January and March, were used. Spectral indices, including NDSI, NDSII-1, S3, SWI, and the second principal component (PCAM2), were extracted. To model snow as a continuous phenomenon, an Adaptive Neuro-Fuzzy Inference System (ANFIS) and its optimized versions using metaheuristic algorithms, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), Differential Evolution (DE), and Ant Colony Optimization (ACOR), were employed. Model performance in training and testing phases was evaluated using RMSE and MSE. Results: The results indicated that algorithm performance depends on the spatial and temporal conditions of the study area. In the Karun North watershed, PSO achieved the lowest RMSE (0.077) on 2022/11/20, and together with ANFIS, it showed the minimum error on 2023/03/20. In contrast, WOA exhibited the highest error and instability in both regions. In the Tehran–Karaj watershed, ANFIS consistently provided the most accurate and stable performance. Overall, ANFIS-based models and metaheuristic algorithms, particularly PSO, demonstrated higher capability in discriminating snow from other land surfaces, while WOA performed relatively poorly. Conclusions: The study demonstrates that combining multiple spectral indices with metaheuristic-optimized computational intelligence models can significantly reduce uncertainty in snow cover estimation in mountainous regions. Among the evaluated models, PSO and ANFIS are recommended as the most efficient options for snow cover monitoring in mountainous watersheds. https://geoplanning.tabrizu.ac.ir/article_22262.html Objective: “The aim of this study is to analyze the state of urban resilience in Tabriz through a systematic review of existing studies in this field. Given the importance of urban resilience in addressing natural hazards and chronic urban stresses, and considering the fragmented nature of previous research on Tabriz, this study seeks to systematically synthesize earlier findings in order to identify dominant patterns, research focuses, and knowledge gaps in the urban resilience literature of Tabriz. Methods: This research is descriptive–analytical in nature and employs a systematic review approach based on the PRISMA framework. Relevant studies on urban resilience in Tabriz were identified using Persian and English keywords across معتبر domestic databases including SID, Magiran, and IranDoc, as well as international databases such as Scopus, Web of Science, ScienceDirect, and SpringerLink. After removing duplicate records, studies were screened based on titles and abstracts, followed by full-text assessment according to predefined inclusion and exclusion criteria. Finally, 24 eligible studies were selected for in-depth analysis. The extracted data were analyzed using qualitative content analysis and comparative methods. In terms of hazards, single-hazard approaches primarily focusing on earthquakes dominate the existing literature. The findings reveal significant spatial inequality in urban resilience across Tabriz, with areas characterized by deteriorated urban fabric, informal settlements, and parts of the historic city center exhibiting lower levels of resilience. Factors such as unequal access to urban services, limited economic capacity, and low levels of social participation were identified as key contributors Conclusions: Overall, the findings demonstrate that urban resilience in Tabriz is not spatially uniform and is characterized by notable intra-urban disparities. These results highlight the need for multidimensional and integrated approaches in urban planning and management, as well as the formulation of targeted resilience enhancement policies tailored to the specific conditions of different urban areas in Tabriz. https://geoplanning.tabrizu.ac.ir/article_22269.html Urban agriculture has attracted increasing attention worldwide as an innovative response to the growing challenges of urbanization, food security, and sustainable development. This study aims to conduct a scenario study with the aim of future research and analyzing the factors affecting the extension of urban agriculture in the Tabriz metropolis. The research method is descriptive and applied, and using a quantitative approach, data were collected through questionnaires and library studies. Scenario Wizard software (for scenario writing) was used to develop urban agriculture development scenarios. The statistical population included experts, urban managers, local elites, and households in Tabriz. This study predicted three main scenarios (green, yellow, red) for the future of urban agriculture in Tabriz, of which only four scenarios were highly compatible. These findings emphasize the importance of focusing on operational and compatible scenarios in future planning. Furthermore, the present study demonstrated that urban agriculture is not only an economic solution for food security, but also has broad social and environmental benefits, including increased public welfare, enhanced food security, and enhanced urban resilience. The findings are consistent with existing theoretical and empirical literature on the critical role of urban agriculture in sustainable development and food security. This study emphasizes the need to integrate urban agriculture into comprehensive urban planning and provides practical suggestions for policymakers and planners. https://geoplanning.tabrizu.ac.ir/article_22278.html Objective: The shortage of adequate housing for low-income groups in Tabriz metropolis has become a chronic urban challenge. This study aims to identify and structurally analyze the key factors influencing the development of social housing in Tabriz and to delineate plausible future scenarios Methods: This research is mixed-method in nature and applied-developmental in purpose. Initial factors were identified through systematic documentary studies and semi-structured interviews with 25 experts in housing and urban planning. A 21×21 cross-impact matrix was developed and administered to 50 experts. Additionally, a separate questionnaire was administered to 100 residents of Tabriz metropolis. Data from the matrix were analyzed using MICMAC software, while resident questionnaire data were analyzed using descriptive statistics. Results: The MICMAC analysis revealed that the social housing system in Tabriz is unstable and dominated by a limited number of key variables. Three variables were identified as critical drivers: "Amount of government investment in social housing" (E3), "Integration of urban planning with social needs" (G3), and "Increase in slum population" (S3). Based on these drivers, four scenarios were formulated: desirable (participatory governance), technological development (green technologies), threat-oriented (intensified housing crisis), and stagnation (economic instability). The most likely future path for Tabriz is the development based on green technologies and physical-technical solutions, as this scenario can be achieved without deep structural reforms in governance.Text Conclusions: Sustainable government investment, institutional integration in urban planning, and controlling slum growth were identified as three priority strategic axes. The desirable scenario faces structural barriers in the short to medium term due to weak transparency and public participation. Therefore, the middle path based on improving physical quality, energy efficiency, and climate adaptation represents the most realistic strategy for Tabriz's policymakers https://geoplanning.tabrizu.ac.ir/article_22302.html Precipitation is one of the most important hydrological and climatic variables and plays a fundamental role in water resources management, flood forecasting, and hydrological process modeling. In many regions, the limited spatial distribution of rain-gauge stations has led to the use of satellite precipitation products as a complementary, and in some cases alternative, source of precipitation data. However, because of the complexity of precipitation processes and the influence of physiographic factors such as topography and climatic conditions, regional-scale evaluation of these products is essential. In this study, the performance of the GPM-IMERG Version 07 (Final Run) satellite precipitation product was evaluated over northwestern Iran using ground-based rain-gauge observations. The performance of GPM-IMERG was assessed at monthly and seasonal timescales using a set of continuous and categorical statistical indices. The results showed that GPM-IMERG tends to overestimate precipitation in most months of the year and has limitations in accurately reproducing observed precipitation amounts. Negative Nash-Sutcliffe efficiency (NSE) values during most periods indicate weak performance in simulating actual precipitation variability, while relatively high false alarm ratio (FAR) values and low probability of detection (POD), critical success index (CSI), and Heidke skill score (HSS) values indicate limited skill in correctly detecting precipitation events. Seasonal analysis further showed that the product performs better in autumn and winter than in other seasons. Overall, the findings of this study indicate that the direct use of GPM-IMERG in northwestern Iran for sensitive hydrological applications is subject to important limitations, and that bias correction, regional calibration, and integration with ground-based observations can play a significant role in improving the accuracy and reliability of this product for climatic and hydrological studies. https://geoplanning.tabrizu.ac.ir/article_22331.html The rapid rate of population increase has led to extensive changes in land-use patterns. These effects, stemming from urban development and urbanization, are observable in both developing and developed countries. One of the most pressing challenges in Iran in recent years has been land-use change and its resulting consequences and hazards, such as land subsidence. This phenomenon has destructive impacts on transportation networks, infrastructure, and structures. If these changes occur in an uncontrolled manner, they will lead to irreversible effects. In such circumstances, identifying areas susceptible to land subsidence and their exacerbating factors can provide a framework for spatial planning and land-use management, thereby facilitating the control of this phenomenon and the mitigation of associated risks. The main objectives of this research are to analyze and investigate the impact of land-use changes on land subsidence in the Tabriz plain, as well as to identify areas prone to subsidence within this plain.” Methods: To achieve these objectives, Landsat satellite imagery from four time periods (1994, 2004, 2014, and 2024) was used to analyze land-use changes. Additionally, the fuzzy ANP model was employed to identify high-risk areas. https://geoplanning.tabrizu.ac.ir/article_22340.html In Iran's large metropolitan areas, empirical assessments of smart city dimensions from the citizens' perspective remain limited. Therefore, the present study was conducted with the aim of identifying and evaluating the effective dimensions of the smart city and analyzing the current status of smartization indicators in Tabriz Data were collected through a structured questionnaire with 57 items across 9 main dimensions from 102 citizens in 10 municipal districts of Tabriz. Descriptive and inferential statistical methods as well as multi-criteria decision-making techniques were used for data analysis. The highest scores belonged to "General Smart City Indicators" (4.05) and "Urban Environmental Management" (3.98), while the lowest scores belonged to "Neighborhood Liveability" (2.65) and "Bioclimatic Environment" (2.74). TOPSIS ranking showed that districts 8, 4, and 6 (new fabric) with coefficients of 0.784, 0.721, and 0.653 had the best performance, while districts 5, 2, and 10 (old fabric) with coefficients of 0.312, 0.351, and 0.387 had the weakest performance. DEMATEL analysis showed that smart mobility (R-D=+0.23) and smart governance (R-D=+0.21) are the main causal (driving) variables that have the greatest impact on other dimensions. The largest gaps were observed in energy consumption management (-2.78), intelligent lighting (-2.69), smart public transport (-2.67), and high-speed internet (-2.65), which were placed in the critical zone of the priority matrix. Overall satisfaction had the strongest correlation with three components: internet access (r=0.67), public transport (r=0.62), and citizen participation (r=0.58). Based on future research scenarios, new fabric districts can reach the desired level within 3 years under an optimistic scenario, while old fabric districts, especially districts 2 and 5, require urgent intervention and special capacity-building programs. Conclusion: Unbalanced development between the old and new fabrics of Tabriz, weaknesses in basic infrastructure (energy, internet, lighting), and insufficient citizen participation are the most important barriers to achieving a sustainable smart city. https://geoplanning.tabrizu.ac.ir/article_22343.html Objective Geotourism, as an approach to the sustainable utilization of geological heritage, requires models capable of simultaneously analyzing the intrinsic values of geosites and their spatial–environmental capacities. The key gap in previous studies lies in the absence of an integrated framework that combines qualitative geosite evaluation with quantitative geotourism potential zoning while statistically examining expert accuracy and agreement. The innovation of this research lies in the simultaneous integration of the Comănescu model (geosite valuation), the Best–Worst Method (BWM) for preferential weighting, and fuzzy analysis, along with the application of Kendall’s W, 95% confidence intervals, Levene’s test, and Welch’s ANOVA to assess the validity and reliability of the results. The main objective of the study is to conduct a comprehensive evaluation of geosites and to map geotourism potential in Takab County. Methods: First, geosites were ranked using the five criterion Comănescu model. Subsequently, environmental layers—including lithology, land use, elevation, slope, aspect, precipitation, temperature, distance from waterways, and distance from roads—were prepared and standardized using fuzzy membership functions. The importance of spatial criteria was determined through the BWM, and finally, a geotourism potential zonation map was generated using the Weighted Sum model. Results: Findings revealed that Takht e Soleyman Lake, the Badarlo Moving Meadow, and Mount Belqis achieved the highest scores in the Comănescu evaluation, with cultural value contributing the most to the overall scoring structure. Kendall’s W coefficient of 0.95 and narrow confidence intervals indicated very high expert agreement. In the BWM model, “distance from waterways” and “distance from roads” were identified as the most influential criteria. The final zonation map showed that more than 87 percent of the study area falls within the “medium” and “high” geotourism potential classes. Conclusions: The results of this research have significant implications for prioritizing tourism infrastructure development, designing geo routes, and identifying investment hotspots https://geoplanning.tabrizu.ac.ir/article_22352.html This study analyzes and explains the effects of tourism development activities on changes in the level of resilience of rural areas (Case study: Oraman District, Sarvabad County). Tourism development was examined as a transformative activity in the rural environment of Oraman, a border and deprived region of Iran, , The research is applied, and in terms of method, it is descriptive-analytical. Data were collected using a quantitative approach and a documentary-survey method. The statistical population consisted of the heads of households in 10 inhabited villages of Oraman District (1517 households). Using Cochran's formula and proportional stratified sampling, 260 individuals were selected as the sample. The data collection tool was a researcher-made questionnaire based on a Likert scale, whose validity was confirmed by experts and its reliability was obtained with a Cronbach's alpha coefficient of 0.84. For data analysis, Wilcoxon signed-rank test, Friedman test, one-way ANOVA, Tukey's post hoc test, and spatial analysis using Moran's I test were employed. The results showed that tourism activity in the studied area has failed to create sustainable and comprehensive resilience in social, economic, and environmental dimensions. Although limited improvements in infrastructure and institutional attention were observed, the impacts in social dimensions (e.g., social capital) and economic dimensions (seasonal employment and unstable income) were mostly weak and unsustainable. Furthermore, the spatial distribution of benefits is highly unequal, with only a few villages (such as Selin and Belbar) benefiting from them, while most settlements remain deprived or even face new challenges. Undoubtedly, this unjust pattern seriously threatens the long-term sustainability of tourism and the region's resilience. Therefore, to achieve sustainable resilience, tourism development strategies must be revised with an emphasis on the equitable distribution of benefits and the reduction of spatial inequalities. https://geoplanning.tabrizu.ac.ir/article_22353.html Objective: The aim of this study is to analyze the spatial pattern of housing quality and its influencing factors in the city of Sari. Research Methodology: To this end, 11 indicators were defined across four main dimensions—housing unit structural quality, housing unit spatial adequacy, residential environment density, and housing unit access to neighborhood services—and calculated at the statistical block level using data from the 2016 census. The SWARA method was employed to determine the weights of these indicators. Spatial analysis of housing quality was conducted in ArcGIS using Global Moran’s I, Hot Spot Analysis (Getis-Ord Gi*), and Local Moran’s I. Additionally, linear regression analysis was performed in SPSS to examine the factors influencing housing quality. Findings: The Moran statistic results revealed a clustered pattern among the statistical blocks of Sari, indicating that blocks with similar quality levels tend to be located adjacent to one another. Local Moran analysis further showed that "High-High" clusters are predominantly situated in the intermediate urban fabric surrounding the city's historic core; these clusters account for approximately 16.5% of the total block area. In contrast, "Low-Low" clusters are mainly located in the eastern and southern parts of the city, covering 18.21% of the total area. Finally, linear regression analysis demonstrated that distance from the city center, the prevalence of apartment living, literacy rates, employment status, and resident age significantly influence housing quality across the statistical blocks. Conclusion: This study indicates a stark spatial disparity in housing quality within Sari. Notably, areas characterized by "Low-Low" quality clusters should be prioritized for intervention.