Climate change is a significant environmental concern due to the sensitivity of glacier melting processes and snow density to climate variations. Currently, a range of satellite sensors, including AVHRR, MODIS, GEOS, and MERIS, are employed for snow monitoring and are extensively utilized to analyze fluctuations and changes in global snow cover. The MODIS sensor is particularly favored for its extensive global spatial coverage, suitable spatial accuracy, and frequent temporal coverage across various scales. Consequently, this study utilizes snow products derived from the MODIS sensor. In this investigation, data on snow-related days from the statistical period of 1989 to 2018 were collected for three provinces: Kermanshah, Ilam, and Lorestan. This data was processed using MODIS snow cover information pertinent to the Middle Zagros region, in conjunction with remote sensing techniques. The study provides a detailed examination of snow cover changes within the specified area. The Normalized Difference Snow Index (NDSI) was employed to detect snow cover within the MODIS sensor products. To differentiate pixels and identify various phenomena, the acquired images were processed using Geographic Information Systems (GIS) technology. Analysis of seasonal snow cover changes using MODIS sensor imagery indicates a significant decreasing trend in the majority of the studied area, particularly in the elevated regions. Notably, only the western and southwestern regions of the study area exhibit no discernible decreasing trend. Furthermore, the examination of snow-covered days throughout the study period reveals a decrease in snow cover in the Middle Zagros, with these changes intensifying in recent years, especially in the snow-covered areas of the region. Changes in snow cover during the winter months, particularly in elevated areas, were observed to be more pronounced compared to other seasons and regions within the study area.

The objective of this research is to investigate the factors that enhance the attractiveness of tourism destinations in Tehran. This study is applied in nature and employs a descriptive-analytical methodology. The data collection methods include the use of questionnaires and interviews. The statistical population comprises tourism experts and specialists, and through the application of Cochran's formula and simple random sampling, a sample of 210 tourism experts was selected. Data analysis was performed utilizing descriptive statistics and logistic regression tests.  The findings of the research reveal that, out of the 210 tourism professionals in Tehran, 91 individuals, representing 43.3%, perceived the attractiveness of Tehran's tourism destinations to be at a high level; 29% assessed it as moderate; and only 27% regarded it as low. Furthermore, the results concerning the factors influencing the enhancement of attractiveness in alignment with tourism development indicate that, among the four factors considered, the most significant were: 1) innovative business opportunities, with an impact coefficient of 0.613; 2) the city's natural, cultural, and historical assets, with an impact coefficient of 0.577; 3) the development of tourism infrastructure, with an impact coefficient of 0.497; and 4) urban development, with an impact coefficient of 0.473.
 

 

In the process of urban space creation, there exists a continuous exchange of ideas concerning the current state of that space and the desired conditions as articulated by its inhabitants. Improvements in the challenging realities of urban environments are often manifested through physical changes, one of which is urban regeneration. Given the proliferation of urban regeneration projects in recent decades, it is imperative to consider the social dimensions inherent in these initiatives. In this context, social capital, recognized as a significant social asset within neighborhoods, has assumed particular importance in the discourse surrounding regeneration. This research examines the role of social capital in the regeneration of urban neighborhoods, with a specific focus on the Islamabad Karaj neighborhood. The methodological approach employed in this investigation is descriptive-analytical. The primary objective of this study is to analyze the influence of social capital on the regeneration processes within the Islamabad Karaj neighborhood as perceived by its residents. Data collection for the theoretical framework was conducted using documentary analysis, while the empirical component involved a survey utilizing a questionnaire. The statistical population comprises individuals aged 15 years and older residing in a neighborhood of over 25,000 inhabitants, from which a sample of 410 respondents was selected through simple random sampling, employing Cochran's formula. For data analysis, Spearman's correlation coefficient and multiple linear regression analyses were conducted using SPSS software. The findings indicate a strong correlation between social capital and urban regeneration within the Karaj neighborhood of Islamabad. The implications of this research highlight the necessity to focus on the components of social capital and to implement policies aimed at its maintenance and enhancement to facilitate successful urban regeneration in the Islamabad Karaj neighborhood.

Earthquake resilience, defined as the capacity of societies—including social, economic, institutional, geographical, and other dimensions—to withstand and recover from seismic events, is a critical issue that demands attention across various societal contexts. It is essential to acknowledge that attitudes toward resilience and the analytical frameworks employed to assess it significantly influence both the understanding of underlying causes of resilience and the formulation of policies aimed at risk reduction and management. The objective of this study is to evaluate and rank the earthquake resilience of new urban developments within the Isfahan Metropolitan area through the utilization of a combined index. Given the nature of the subject matter, the research adopts a descriptive-analytical approach. The study's statistical population comprises six new urban developments: Shahin Shahr, Majlesi, Sepahan Shahr, Foolad Shahr, Baharestan, and Shahid Keshvari. This research is characterized as applied in nature, and information for the literature review was gathered through library research methods. According to the results derived from the Potentially Optimal Solutions Evaluation Technique (POSET) analysis, the rankings of the urban developments based on the combined index of resilience to earthquake risk are as follows: Majlesi (3), Baharestan (6), Foolad Shahr (7), Sepahan Shahr (8), Shahin Shahr (11), and Shahid Keshvari (14). Consequently, to mitigate the adverse effects of earthquakes on communities, it is imperative to consider the unique capacities of each urban development, thereby reducing potential human and financial losses resulting from such events.

Policy-making in tourism development planning necessitates the adoption of innovative methodologies within the domain of urban governance. In alignment with this framework, it is imperative to implement policies that focus on the processes of "developing a good governance model for tourism in the post-COVID-19 era in Iran." This approach aims to mitigate the challenges posed by the pandemic, which has imposed significant strain on the tourism industry by reducing the evaluation of tourism governance indicators and establishing a foundation for their implementation. The methodology of this research is descriptive-survey with a practical focus, employing both documentary studies and field research. The qualitative component of the study utilized interviews as a tool for data analysis and the examination of relevant tourism indicators. The statistical population comprises experts and stakeholders involved in the tourism sector in Iran, with a sample size of 14 individuals selected through a combination of purposive and snowball sampling techniques. In-depth semi-structured interviews were conducted, and the data were analyzed through a process of open, axial, and selective coding until theoretical saturation was achieved, leading to the categorization of main and sub-categories. The data analysis was informed by the grounded theory methodology. The findings of this research, which identify indicators of effective governance and elucidate the causal conditions for the application of such governance in Iran's tourism industry, provide a foundation for potential outcomes, including the enhancement of the business environment, particularly in the aftermath of the economic downturn experienced due to the COVID-19 pandemic. These outcomes may lead to the creation of competitive advantages through the establishment of conducive platforms, including organizational measures, infrastructure development, technological enhancements, and the implementation of information and communication management strategies, marketing strategies, and oversight mechanisms, all of which are articulated as a comprehensive model.

This study investigates the impact of the OLR MJO Index (OMI) and the Real-time Multivariate MJO (RMM) of the Madden-Julian Oscillation on the frequency of dust storms in the stations of Abadan, Ahvaz, Bostan, Bandar Mahshahr, Dezful, Ramhormoz, and Masjed Soleiman, located in Khuzestan province, during the period from April to September 1987-2021. Pearson correlation coefficients were computed to assess the relationship between dust data and the indices, and the findings were depicted through zoning maps. Subsequently, the frequency percentage of each index for both positive and negative phases was quantified. The results indicate a direct and significant correlation between the positive and negative phases of the indices and dust occurrences (with the exception of Dezful station), particularly during the positive phase of the OMI and the negative phase of the RMM. The highest correlation coefficients, ranging from 0.77 to 0.72, were observed for Bandar Mahshahr and Dezful stationsduring the positive phase of the RMM index. Analysis of the relationship between the Madden-Julian Oscillation and dust storms revealed that between 51% and 59% of dust storms in Khuzestan province occurred in the negative phase of the OMI index, while 40% to 49% occurred in the positive phase. In the case of the RMM index, 56% to 63% of dust storms were associated with its negative phase, in contrast to 37% to 50% linked to its positive phase. Notably, the negative phase of the RMM index exhibited a higher percentage of dust storms compared to the negative phase of the OMI index. According to the results of the Monte Carlo test, the displacement of the positive and negative phases of the RMM index significantly contributes to the occurrence of dust storms at most stations in Khuzestan province. Furthermore, tracking the pathways of dust entering Khuzestan province using the HYSPLIT model indicates the movement of particles originating from Iraq, Arabia, and the eastern regions of Syria toward Khuzestan province..

Water is a strategic and scarce resource that has become increasingly limited in recent years due to a variety of national and transnational factors, significantly impacting security, stability, development, and prosperity in various countries. The profound influence of water on these domains has positioned it at the forefront of the foreign policy and hydropolitical relations of numerous nations, including those in South West Asia. In recent years, despite the prominence of the water crisis and its implications for the relations between Iran and Iraq within scholarly, political, and media discussions, the complexities of this issue remain poorly understood, leading to disparate interpretations. 
The current research, which is exploratory in nature, utilized library methods for data collection with the aim of achieving a qualitative understanding of the multifaceted hydropolitical relations between Iran and Iraq. This study not only seeks to identify the content and methodological characteristics of existing literature but also aims to uncover research gaps in this field employing a qualitative meta-analysis approach. Through this method, the research examined 34 studies published between 2014 and 2023, including domestic scientific articles, theses, and contributions to reputable international journals. The findings indicate that a comprehensive analysis of the various dimensions of hydropolitical relations between Iran and Iraq has yet to be undertaken. In this context, the absence of accurate and reliable data, alongside the inadequacy of theoretical and cognitive frameworks, represents significant deficiencies in the existing research on the bilateral relations of these two countries.
 

Drought is a natural hazard that annually causes significant economic, social, environmental, and life-threatening damage in vast areas of the Earth. The damages caused by this phenomenon are intangible but very extensive and costly.  In many circomstancs, modern remote sensing techniques can be a useful tool in monitoring drought due to high temporal accuracy, wide spectral coverage, ease of access, no need for atmospheric correction and ground referencing. In recent years, the province of Hamedan has faced many problems due to frequent droughts. Therefore, the present study focused on investigating and monitoring drought in Hamedan province using the Temperature Condition index and its impact on the vegetation cover of the province using Advanced Very High Resolution Radiometer (AVHRR) and National Oceanic and Atmospheric Administration (NOAA) remote sensing data. First, the relevant data was extracted from the Nova star database, and finally, the spatiotemporal behavior of the vegetation cover drought index was examined on 1528 pixels in Hamedan province. The spatial resolution of the data used in this study is 4 kilometers. First, the relevant data were extracted from the Navstar database and ultimately, the spatiotemporal behavior of the drought index and vegetation cover was examined. The results indicate that drought has significantly increased the vegetation cover of Hamedan province based on remote sensing data. Kendall's coefficients indicate the presence of decreasing trends in vegetation cover at a 95 Percent confidence level. Only in May, June, and December has there been a slight decrease in vegetation cover within the extent of drought in the province. The spatial behavior analysis of the drought index on vegetation cover showed that February, March, as well as April have experienced more severe droughts within Hamedan province.

Understanding the daily weather types of any specific location is crucial for identifying its long-term climate patterns. In this study, we utilized the Wos classification method in conjunction with a comprehensive climatological approach to analyze key variables, including minimum, average, and maximum temperatures, as well as cloud cover and daily precipitation. Data from 1985 to 2021 were collected from 39 synoptic stations, which exhibited a well-distributed representation across the country and provided complete datasets. Weather types were identified using established coding techniques. The findings indicated that the predominant temperature types in the country are primarily categorized as hot and very hot, with sub-codes reflecting generally low to moderate cloud cover and negligible precipitation. Furthermore, the application of Ward's clustering method facilitated the identification of three distinct climatic groups. The geographical characteristics of each location, including factors such as altitude, latitude, proximity to the sea, and synoptic influences, play a significant role in the regional differentiation of these groups within the country. The outcomes of this research can be instrumental in developing weather calendars for various regions, with implications for numerous sectors including agriculture and tourism.
 

The contemporary global landscape is characterized by heightened geopolitical competition, in which energy resources have evolved from being mere support for nations to becoming pivotal elements in the contest for power. This context has transformed corridors into significant arenas for competition, as each country endeavors to establish its position within the intricate network created by these emerging corridors. In this regard, the prevailing global geopolitical trend has intensified the competition over maritime chokepoints and secured access to cross-border markets.This research serves as a theoretical foundation, employing a descriptive-analytical methodology that incorporates a comparative approach, utilizing library and internet resources for data collection. Within the chronopolitical framework of Iran-Iraq relations, each actor strives to delineate its role in international corridors while pursuing various objectives. For instance, Iraq is actively engaged in the "FAW Corridor" initiative, whereas Iran seeks to expand economic cooperation and secure a place in the burgeoning alliances of the East. While it is challenging to make definitive predictions regarding the future of relations between the two countries from a chronopolitical perspective, emerging signs suggest a trend toward diminished cooperation and increased competition, influenced by a multitude of variables. A key indicator of this potential competition is the rivalry over transit routes (corridors).
 

Extratropical cyclones, characterized by their frequency, duration, and intensity, serve as the primary drivers of mid- and high-latitude precipitation across the Mediterranean during the winter and autumn months. For this research, climatic variables obtained from the ECMWF network, featuring a temporal resolution of 6 hours and a spatial resolution of 0.25° × 0.25°, spanning from 1979 to 2016, were utilized. Additionally, precipitation data from four basin stations sourced from the Asfezari database for the same period were analyzed. Initially, geopotential height, temperature, humidity, and jet stream data for rainy days were extracted using MATLAB. Subsequently, a cyclonic center extraction algorithm was applied to identify cyclonic centers from the geopotential height data, based on the conditions that the geopotential height is at a minimum and the geopotential gradient is at a maximum. From the geopotential height matrix of rainy days (361×441×498), four distinct atmospheric patterns were identified through cluster analysis. The temporal and spatial frequency of these patterns, as well as the average temperature of cyclonic centers, were analyzed for the cold season months. The results indicated that the first pattern, identified as the Mediterranean trough pattern, is the most frequent, occurring 42% of the time. This pattern is characterized by the presence of a high-level system acting as a barrier, which deepens the low-level Mediterranean system and extends its axis toward the Red Sea. The interaction between low-level and high-level systems enhances instability, resulting in the highest precipitation levels among the identified patterns. Conversely, the fourth pattern, termed the western wind trough pattern, exhibits the lowest frequency at 10%. This pattern is characterized by a trough over the Caspian Sea; however, a high-level system in the southern region inhibits the entry of low-level systems, thereby confining cyclonic activity to the northern portion of the study area. Consequently, the isobars in the northern region assume a more orbital configuration, leading to a decreased influx of cyclones and, as a result, lower precipitation amounts compared to the other patterns. The analysis further revealed that cold-core cyclones accounted for 60% of occurrences in winter and 40% in autumn, while hot-core cyclones constituted 62% in winter and 38% in autumn. Notably, the frequency of hot-core cyclones increased relative to cold-core cyclones in winter, whereas an inverse trend was observed in autumn. Over the past decade, both the frequency and intensity of cyclones have diminished compared to the preceding two decades. In terms of cyclogenesis locations, the western part of the study area has consistently emerged as the most active region. Moreover, cyclogenesis activity exhibits a gradual increase from autumn to winter as the cold season progresses. These findings underscore the dynamic nature of extratropical cyclones and their significant role in shaping precipitation patterns across the Mediterranean region.
 

Dust is a phenomenon with significant environmental impacts across various aspects of human life, including agriculture, economy, health, and more. The purpose of this study is to investigate and predict the dust phenomenon in Kermanshah. Meteorological data with a 3-hour resolution for the statistical period (2000–2020) from the Kermanshah station was obtained from the Meteorological Organization. First, the dust data were normalized, and then Artificial Neural Network (ANN) models were used to predict dust concentration, while the Adaptive Neuro-Fuzzy Inference System (ANFIS) was employed to analyze and predict the time series of dust occurrence in MATLAB software. The findings revealed that the maximum predicted dust concentration, related to the minimum dew point with the highest Pearson correlation with dust, was estimated at 3451.23 µg/m³. Additionally, the results of the time series prediction using the ANFIS model showed that the linear bell membership function with grade 3, during both the training and testing stages, was the most effective input function among other membership functions. According to the forecasting models, the highest probability of maximum dust occurrence in the next 20 years in Kermanshah is 94%. Based on the aforementioned studies, sufficient information was gathered to conduct this research. The phenomenon of dust, particularly in western Iran and the city of Kermanshah, has consistently posed significant challenges for the residents of these areas. This phenomenon is influenced by specific atmospheric conditions that cause irreparable damage annually, leading to respiratory issues and deteriorating air quality. Therefore, it is essential to pay serious attention to the issue of dust.