Journal of Applied Research in Geographical Sciences

Modeling the factors affecting urban resilience against earthquake risk (Case study: Parsabad Moghan)

Ayat Jahanbani

Resiliency is one of the approaches to reducing the vulnerability of communities and strengthening peoplechr('39')s ability to deal with the dangers of natural disasters, especially earthquakes, and has economic, social, institutional, physical, and environmental dimensions. This research is applied in terms of purpose and descriptive-analytical in terms of nature and research method. The researcher-made questionnaire with 102 items was a tool for collecting research data. The sample size was 386 simple based on Cochranchr('39')s formulas and the sampling method was random. Exploratory factor analysis and path analysis were used in the SPSS25 software platform for data analysis and factor modeling. The results indicate that Parsabad city has the lowest scores in terms of social and physical resilience and is in a moderate to good condition; environmental resilience is in a moderate condition, institutional and economic resilience are in a bad situation. Also question factorization, 13 factors for social dimensions, (behavior during the crisis, crisis awareness, crisis preparedness, knowledge, cooperation, trust, assistance, reliance, interaction, accuracy, attitude, first aid, and necessary measures); 3 factors (Damages, Compensation and ability to return) for economic dimensions; 5 factors (performance of public institutions, the performance of semi-public institutions, institutional communication, institutional measures, and institutional context) for institutional resilience; 4 factors (open space, building resistance, public access and Relief access) for physical resilience and 3 factors (environmental, nutritional and soil factors) for environmental resilience. Finally, the modeling of resilience indicators for Parsabad city was presented.

Measuring effective indicators in improving neighborhood-based participation (case study of Zahedan city)

Gholamreza Miri

Utilizing neighborhood capacities and redefining the role of citizens at the urban neighborhood level has led to a new approach called neighborhood-based participation; Because many urban challenges are rooted in the lack of citizen participation. The city of Zahedan is no exception. In order to achieve neighborhood-based participation, it is very important to pay attention to and strengthen some indicators. The purpose of this study is to measure the effective indicators in improving neighborhood-based participation to improve urban services in the city of Zahedan. The research method is descriptive-analytical and based on data collection in the field through a questionnaire. The statistical population of the study consists of 587730 citizens living in Zahedan. The sample size was calculated using the Cochranchr('39')s formula of 322 people. Examination of 5 variables of reliability, accountability and responsibility, reliability, empathy and attention and tangible and tangible factors show that all 5 variables were significant at the level of less than 0.05. Examining the difference between the mean and t-test statistics confirmed that citizens do not trust the performance of the municipality and managers. Also, one-sample t-test shows that the indicators of transparency, empowerment, economic base, value bases and sense of place are equal to 0.000 and less than 0.05 are significant. This article points to the impact of these indicators on improving neighborhood-based participation. Based on the results of the structural equation model, the greatest effect is related to the transparency index with 0.19, then the sense of spatial belonging with 0.15. Also, one-sample t-test shows that voluntary contributions (mean difference of 0.510), financial (mean difference of 0.611) and intellectual (mean difference of 0.486) with a significance level of less than 0.05 can have a great impact on Improve neighborhood-based participation and improve the quality of municipal services.

Analysis of affecting factors on Durability of low-income housing by Structural Equation Modeling(Case study: Sirjan housing Mehr)

Azam Abbaspour

In todaychr('39')s world, housing and shelter have overshadowed many aspects of human life. Providing adequate housing, especially for low-income urban groups, is one of the most important issues and challenges facing all countries. The desirability of the environment of residential complexes built for low-income groups has always been a challenging issue. In the programs and plans prepared for these groups, due to the huge flood of applicants and also the limited resources and credits, quantitative goals have often been pursued and qualitative goals have been abandoned. A study of the housing pattern of this group in cities shows that attention and application of effective indicators of housing sustainability is one of the categories that should be considered in the process of housing planning. This article, with the aim of analyzing the factors affecting the housing survival of low-income groups, has reviewed the theoretical literature and tested research hypotheses. The statistical population of the study is the residents of Mehr dwelling in Sirjan. After distributing the questionnaire, data analysis was used at two levels of descriptive and inferential statistics. The validity of the structure was confirmed by factor analysis. The reliability of the instrument was also calculated using Cronbachchr('39')s alpha coefficient test of o.7. Data analysis was performed from Sstructural Equation Modeling using Smart PLS software. Findings indicate the relationship between quantitative and qualitative indicators of housing on durability. Quality index with cultural and social criteria and components such as security, privacy, sense of place, user participation has the greatest impact on Durability of low-income housing in Sirjan.

Factors affecting the increase in the attractiveness of ecotourism and geotouriasis of Khorramabad Township

Mostaf Hadavand Mirzaei

The development of nature-based tourism is dependent on the introduction and attention to the attraction of natural tourism attractions. In fact, identifying the factors affecting the increase in the attractiveness of ecotourism and geotourias places is among the most important issues in the development of tourism and naturalization of an area. According to this, the purpose of the present paper is also to investigate the factors affecting the attractiveness of tourist and geotorrhean locations in the study area. The present research is applied in terms of purpose and in terms of its method, descriptive-analytic. The data collection tool and information questionnaire and interview are. The statistical population of the research is experts and specialists in Tourism in Khorramabad in Lorestan province. In this research, 50 experts and natural tourism specialists were selected as samples. The research results indicate that four factors of ecotourist and geotourist tourism products, natural assets, and development of tourism infrastructure and create opportunities of nature-centered tourism boom are the most important factors in increasing the attractiveness of tourist places and geotorrhea. Also, the results showed that the strengthening of regional tourism infrastructure, private sector investment in tourism and the recognition of natural tourism capacities and tourism attractions, and planning for its development, are the most important strategies for development of natural tourism in Khorramabad.

Analysis of synoptic patterns of hot wave generators in Tehran And its effect on bioclimatic risk

Gholamrezaa Janbaz Ghobadi

Temperature is one of the basic elements of climate, so its sudden or short-term and long-term changes can change the climate structure of any place. Intense heat waves are one of the most important climatic disasters that have far-reaching effects on various human activities and when they are of high intensity and frequency, they can produce major problems. In this study, to investigate the trend of 49-year frequency series (1970-1970) of hot wave events in Tehran, from two indices of hot days and hot waves (hot days lasting 2 days or more), non-parametric statistics of Sens trend analysis were used. All stations indicate an increasing trend both in the number of hot days in Tehran and in the frequency of hot wave events in 5 stations in Tehran. In this study, two hot waves were identified in Tehran, the first wave in 2010 covered a large part of the central and western parts of the country and the second wave in 2013, which was in all stations of Tehran and even many provinces. Are registered in the country. The results of spatial analysis of hot wave temperature in the statistical blocks of Tehran showed that generally the central areas of Tehran, including areas 6, 7, 8, 10, 11, 12, 14, 15, 4, 7, and 19 significantly It has been affected by the critical temperatures caused by the warm wave rule, while the northern parts of Tehran have been affected by the lower intensities of the hot wave.

Elaboration of effective strategies to optimize energy consumption in residential blocks (case example: Rushdieh neighborhood of Tabriz)

Morteza Mirgholami

Considering that more than one third of energy consumption is related to residential areas, proper planning and design of neighborhoods according to the climatic conditions of each region can be an effective step towards reducing energy consumption. It aims to optimize energy consumption in the residential blocks of Rushdieh neighborhood in Tabriz. Investigating and understanding the energy consumption situation in Rushdieh neighborhood of Tabriz, its capabilities and bottlenecks in planning is very important, if they are not paid attention to and there are no efficient strategic plans, it will lead to an increase in social, economic and environmental instability. According to its nature, the research method is descriptive-analytical and practical in terms of purpose. It is related to the intended goals of the research, the statistical population of the research is the professors, experts and elites of urban planning, which has been used to examine the indicators and strategies. The method of selecting people was targeted and snowball. Finally, the results showed that the formulation of policies, practical measures to improve the design of main roads and local accesses in the direction of neighborhood air conditioning should be emphasized as the most important strategy. In order to reduce energy consumption, the development of neighborhood design policies and residential blocks with the goals of using wind energy to reduce energy consumption have been placed in the second and third ranks of this prioritization, respectively.

Statistical analysis of Iran's heavy rains during sudden stratospheric warming

behrooz nasiri

sudden stratospheric warming has an obvious effect on the Earth's surface climate. In this research, the changes in precipitation during the occurrence of this phenomenon have been investigated. For this purpose, after revealing the warmings that occurred during the studied period (1986-2020), 18 warmings were identified. The 5th decile and 9th decile of precipitation were calculated for the precipitation data of 117 stations. And the size of the difference from the normal rainfall was checked in two ways. First, the precipitation at the time of warming was compared with the long-term average, and then the trend of changes in precipitation at three times before thewarming, at the same time as the warming, and after the warming was finished. Finally, these results were obtained. Warmings according to the month in which they occur; They have a different effect on the amount of precipitation. In the sudden stratospheric warming that occurred in December, January and February, the northwest experiences the most rainfall changes and is above normal, and the probability of rainfall above the 9th decile increases up to 65%. Western and southwestern regions also have higher than average rainfall and the probability of heavy rainfall is high. Precipitation on the shores of the Caspian Sea shows an inverse relationship with sudden stratospheric warming, so in all the investigations of this research, the lack of precipitation at the time of warming in these areas is significant. Southern regions have less than normal rainfall in all sudden stratospheric warming events. The center of Iran has higher than average rainfall in the sudden stratospheric warming months of March. Eastern Iran also has heavy rains compared to normal during the sudden stratospheric warming months of March.

Analyzing the trend of widespread hot days in the coasts of the Persian Gulf

Mansureh Taheri

One of the climatic characteristics of temperature is the occurrence of extreme temperature. In the present study, the trend of hot days with extreme temperature associated with the coastal plains of the Persian Gulf was investigated. Two environmental and atmospheric databases were used. Environmental data include the average of daily maximum temperature reported from 12 synoptic stations in Persian Gulf coastline (Khuzestan, Bushehr, and Bandar Abbas Provinces) from 1961 to the end of 2018. The extreme temperature for each day temperature was defined to be higher than the average of 75th percentile of the observations at each station and on the same day. Also, the ‘day with extreme temperature’ was applied to a day when the extreme temperature occurred in at least 50% of the stations. The number of hot days with extreme temperature in the study is 554 days, of which 291 days occurred in the warm season and 263 days in the cold season. These days were classified into six groups by performing cluster analysis on sea-level pressure in hot days. Then, for each group, the trend of hot days was examined. In general, it can be concluded that the slope of the line in all groups except the fourth and sixth groups were positive and, as a result, hot days with extreme temperature were increasing.

Assessment and Prediction of Atmospheric PM₁₀ Pollution in Ahvaz City Using Statistical Methods and an Artificial Neural Network

Atefeh Bosak

Air pollution has significant impacts on human health, environmental quality, and the sustainable development of cities. This study aimed to evaluate PM10 using meteorological data from the city of Ahvaz through statistical methods and artificial neural networks. Daily meteorological data and air quality control station data for 4485 days (from 2011 to 2023) were obtained from the National Meteorological Organization and the Khuzestan Department of Environment. Initially, the data were processed and refined, and their normality was assessed using the Kolmogorov-Smirnov test. Given the non-normality of the data, Spearman's and Kendall's Tau-b methods were employed to examine their correlations. The time series and statistical information of the data were obtained using Python programming language. Furthermore, to predict future PM10 levels, the Multilayer Perceptron (MLP) neural network method was utilized. The results of these analyses indicated a significant correlation between meteorological variables and PM10. The Spearman and Kendall Tau-b correlations showed that PM10 had a positive and significant correlation with wind speed (0.094 and 0.061) and temperature (0.284 and 0.187) at a 99% confidence level. Conversely, PM10 exhibited a negative and significant correlation with visibility (-0.408 and -0.300), wind direction (-0.048 and -0.034), precipitation (-0.159 and -0.125), and relative humidity (-0.259 and -0.173) at the 99% confidence level. For future PM10 predictions, the MLP neural network was used. The model was of the Sequential type with an input layer consisting of 6 neurons, three hidden layers of Dense type with 16, 32, and 64 neurons, and an output layer with a linear activation function. The mean squared error (MSE) for the training set was 0.0034, and for the validation data, it was 0.0012. For the test set, the obtained validation accuracy was mse_mlp=0.0048 and val_loss=0.0012. The results indicate a significant direct or inverse correlation between meteorological data and PM10. Additionally, the outcomes of the MLP neural network demonstrated that the network provided satisfactory performance and acceptable predictions for PM10 data in Ahvaz.

Evaluating the relationship between two indeces of crop water stress and the SEBAL algorithm for estimating evapotranspiration using satellite images (Study area: agricultural lands of Dasht Abbas district, Dehlran city)

Mostafa Kabolizadeh

There are various indicators to monitor and management of agricultural water resources in arid and semi-arid countries including Iran, some of which can be extracted directly in situ, and some can be retrieved using remote sensing technology and satellite images. Aim of this study is to propose the most appropriate and efficient indicators of agricultural water resource management for achieving maximum production and maximum water efficiency using remote sensing technology, therefore, Crop Water Stress Index (CWSI) and Surface Energy Balance Algorithm (SEBAL) were used to estimate Evapotranspiration (ET). In the first step, ET rate was calculated using SEBAL algorithm for six Landsat 8 satellite images related to the wheat growth period. Then, zoning of this index was done in the range of zero to one, in four categories of very low, low, medium and high, which respectively indicate the lowest to the highest amount of ET. In next step, CWSI was calculated based on Idso equation, and its results show different changes both in cold season and in warm months. Comparison of ET and CWSI shows a significant relationship between these two indices in warm months, while in cold months, no significant relationship can be seen. These findings along with the established relationship between ET and CWSI can inform water management strategies in arid environments for sustainable crop production.

Analysis of the relationship between facts and perceptions in the context of reducing the physical vulnerability of problematic urban tissues (case study of Region 4 of Urmia city)

keramat ollah ziari

One of the issues raised in the developing countries of the world is the issue of reducing damages caused by natural and man-made hazards. Various theories and paradigms such as crisis management and resilience have been proposed to reduce the level of risk vulnerability. Among the mentioned vulnerabilities is physical vulnerability. Now, the most important question that is raised in this research is whether according to the various studies that have been done in the field of physical vulnerability, apart from objective measures, the level of satisfaction of the residents has also been examined and whether it exists. Is there a relationship between objective and subjective indicators in this field? The case study studied in this research is Region 4 of Urmia City, which has a problematic context. This research is of an applied type and its method is descriptive-analytical, to examine this objective and subjective relationship of physical vulnerability, first objective variables were examined using spatial analysis and then subjective variables were examined using a Likert scale. questionnaire. And finally, this relationship has been measured using Pearson's correlation coefficient. The research results indicate that according to the correlation coefficient of 0.623 between subjective and objective variables; There is a significant relationship between the objective view (reality on the ground) and the subjective view (satisfaction of residents) in the field of urban physical vulnerability indicators.

Understanding Wildfire Regime and Mapping Wildfire Hazard in the Protected Areas in Guilan Province

Roghayeh Jahdi

Every year, wildfires burn large areas in the Hyrcanian forests, of northern Iran. This study aims to know the fire regime and assess fire risk in protected areas in Guilan province (256,488 hectar). Fire ignitions and frequency/frequency of burned areas from 1992 to 2022 were identified. Then fire behavior modeling was done to simulate burn probability and fire intensity (i.e. conditional flame length) using the FlamMap modeling system based on fire weather information, topography maps, local fuel models, and historical fire data. By combining maps of simulated burn probability and conditional flame length, a fire hazard map was prepared in the protected areas. According to the obtained results, 8% of the number of historical fires in the period occurred in the protected areas, although most of these fires have very small sizes and limited burned areas (including 0.1% of the burned areas in the province). Frequent fires (fire frequency more than 1) cover 60% of the protected areas, and 11% of these areas are highly likely to ignite. The changes in the burn probability and fire intensity reflect the diversity of fire activity in the protected areas, especially in the south-central parts, which catch the highest values of burn probability (more than 1) and conditional flame length (more than 3 meters). Finally, the fire hazard mapping showed that 77.7% and 4.8% of the protected areas are classified as very low and low fire hazards, respectively. On the other hand, 12.4% and 5.2% of these areas were placed in high and very high hazard classes, respectively. The quantitative results of this research provide scientific criteria for identifying high-priority areas in protected areas where management efforts can help reverse the increasing fire risk of protected forests.

Analysis of socio-economic effects of religious events tourism on rural households (Villages of Neishabur and Zabarkhan county)

Hamdollah Sojasi qedari

Religious events in a region show the beliefs and sanctity of that place by humans; Rituals and celebrations can have economic and social benefits for the region. Therefore, by examining and analyzing the economic and social effects of events, it is possible to help organize better and more diverse events and tourism in the region. Therefore, in this research, the main goal is to evaluate the impact of religious events tourism on the social and economic dimensions of villages. The current research is descriptive-analytical in terms of methodology and practical in terms of purpose. The statistical population studied consisted of 323 heads of households living in 6 selected villages that organize religious events in Nishabur county and new county of Zabarkhan. SPSS software was used to analyze the findings. The findings of the research show that the highest average belongs to the social dimension with an average of 1.94. Also, the analysis of factors using chi-square (x2) and inferential statistics, normality, one-sample t-test, analysis of variance, Friedman, independent t-test were used. The tests showed that the social and economic effects of tourism of religious events in the studied villages are low, and the people of the region considered the ideological and spiritual nature of the event and did not pay attention to its tourism characteristics. Therefore, it is suggested to provide the necessary infrastructure for holding religious events in rural areas as well as possible, and to conduct more researches in this connection, as well as to create a suitable economic environment and increase employment during events, to prepare brochures or resumes for introduction. area or local event to be addressed.

Identification of Factors Affecting the Realizability of Service Land Uses with a Futures Studies Approach (Case Study: Zanjan City)

Hossein Tahmasbi Moghadam

Land use planning is one of the essential aspects of sustainable urban development, aiming to balance land use in urban areas. This study seeks to identify the factors influencing the realizability of service land uses in Zanjan city through a futures studies approach. Data collection employed a combination of library and field methods. In the field phase, the Delphi method was used, engaging 35 experts in urban planning, urban management, and housing, who assessed key factors across two rounds of questionnaires.
A total of 36 factors were identified across five dimensions: legal, economic, socio-cultural, physical-spatial, and managerial. The data were analyzed using MICMAC software. The results indicated that "urban land use laws and regulations" and "service location and spatial distribution" scored the highest direct influence values (85 and 82, respectively), playing the most significant roles in realizing service land uses. Key barriers identified include weak institutional coordination, inappropriate physical development policies, and lack of effective citizen participation. Cross-impact matrix analysis revealed a 55.32% fill rate, indicating a system of interdependent and mutually influential factors that contribute to the instability of service land use realizability. The study proposed solutions to improve the current situation, including: Revising urban laws and regulations, Strengthening institutional coordination among relevant bodies, Utilizing modern technologies such as GIS for proper service location planning, and Enhancing citizen participation culture in urban planning. The findings not only identified key influential factors but also emphasized the importance of considering multidimensional and sustainable aspects in service land use planning. This research provides a foundation for sustainable development and spatial justice in Zanjan city.

Optimizing Tourist Routes in Tehran’s District 12 Using Open TSP and GIS Network Analysis

Saeedeh Fakhari

Tehran’s District 12, as one of the capital’s cultural and tourism hubs, hosts a collection of prominent cultural institutions and museums that serve as major attractions for domestic and international visitors. However, the absence of systematic planning for routing between these centers leads to wasted time and energy for tourists and diminishes the quality of their visitation experience. This study aims to optimize museum visitation routes in Tehran’s District 12, focusing on minimizing travel time and distance, by selecting 22 active and significant museums in the area as case studies. To achieve this, the mathematical model of the Open Traveling Salesman Problem (Open TSP) was applied within the framework of network analysis in a Geographic Information System (GIS) environment. Precise spatial data—including the geographic locations of museums and the local street network—were imported into ArcGIS software and processed using the Network Analyst tool. Travel cost matrices (based on time and distance) between all museum pairs were calculated, and optimal visitation routes were extracted and ranked using heuristic Open TSP algorithms according to the criteria of minimum time and shortest distance. Findings indicate that applying the Open TSP model within network analysis leads to the identification of significantly more efficient routes compared to conventional patterns or unplanned visits. Quantitative results show that, under normal (non-optimized) conditions, visiting all 22 museums covers a distance of 25.91 km with a travel time of 310 minutes, whereas the optimized proposed route requires only 9.896 km and 118 minutes of travel time. This improvement represents a 62% reduction in both distance and travel time. The study demonstrates the high efficiency of integrating combinatorial optimization models with GIS spatial analysis capabilities for urban tourism planning and can serve as a model for intelligent management of tourist visitation routes in other urban areas. The results enable informed decision-making and optimal planning for both group and individual visits, significantly enhancing the tourism experience by reducing time and physical costs.