تحقیقات کاربردی علوم جغرافیایی

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.

Today, the accelerating trend of urbanization, the lack of guidance and urban management, national and regional inequalities, and differences in the socio-economic base of individuals have led to the growth and expansion of informal housing. Due to this situation, informal housing has been expanding in Tehran's metropolitan area. The present study seeks to find key factors affecting informal housing in the study area and also to determine the relationships between criteria through structural-interpretive modeling (ISM). Are; Which is applied in terms of the nature of the application and in terms of the combined method (quantitative and qualitative) and in terms of the inductive research approach In this method, a questionnaire tool was used and in order to analyze the relationships and present their structural model, the interpretive structural modeling method was used, The results of MICMAC analysis and the classification of key factors in the four matrix clusters It shows that the factors of economic growth, redistributive policies, decentralization and transfer of authority, regional equilibrium policies, revision of development and sanctions laws and regulations and its effects are in the fourth cluster,which are in fact variables of research. In fact, key variables are research, and the only factor in housing policies is the cluster of link variables, which will guide other factors, and change will affect the entire system.

Landslides are among the most common and destructive natural hazards that change the shape of the earth's surface, and reviewing the damages caused by landslides, the need to investigate the factors influencing the occurrence of this phenomenon and predict its occurrence. proves that Khalkhal City, due to its special geological, climatic, and geomorphological characteristics and human activities, has been affected by the risk of landslides for a long time. Therefore, considering the importance of the issue; The purpose of this research is to produce a landslide risk map in this city. In this regard, first, the distribution map of landslides and influencing variables, including; DEM, slope, aspect, land use, lithology, distance from fault, distance from river, distance from road, and rainfall were provided. Next, after the fuzzy membership and determining the weight values of each factor using the CRITIC method, the landslide susceptibility map was prepared using the MARCOS multi-criteria decision-making method. The results of the study showed, respectively; that The factors of slope, land use, and lithology with weight coefficients of 0.148, 0.139, and 0.132 have the greatest influence on the occurrence of landslides in the region. According to the results of the research, respectively; 707.14 and 512.87 square kilometers of the area of the city are in high-risk and very high-risk categories, and these areas are areas that need management work and the implementation of protection projects. Also, considering the use of the ROC curve method the area under the curve (0.89), and the correlation of 0.83% between the final map obtained from the research and the distribution of sliding surfaces, the accuracy of the MARCOS method in identifying and zoning prone areas The risk of landslides in Khalkhal city is great.

Vulnerability is the inevitable result of risks and crises that threaten societies to varying degrees. One of the main threats is earthquakes. The recent approach to disaster management programs is to increase the resilience of communities that have different dimensions. One of them is the physical dimension of urban resilience, which is linked to the components of land use planning. In this research, with the aim of analyzing land use criteria affecting the resilience of Tabriz city and using fuzzy AHP method, research has been done. Based on the results of the study of theoretical foundations, 13 effective criteria have been identified and the basis of action. The required data were extracted and used from maps and spatial information of urban plans, especially the detailed plan of Tabriz, Then Using ARC Map10.3.1 software, each criterion is analyzed and each criterion is presented in the form of a fuzzy map. Sum, Product and gamma fuzzy operators have been used to achieve the final resilience map. Due to the high accuracy of the gamma operator, its results are considered as the final output. The results show that in the city of Tabriz, 2% have very low resilience, 40.8%, low resilience,15.3% moderate resilience, 23.5% high resilience and 7.2% very high resilience - based on the Used criteria-. Areas with low resilience are generally located in the north of Tabriz city and correspond to the informal settlement texture and the worn-out texture of the city, which corresponds to the fault line of Tabriz and Micronutrient and permeability are other features of these areas. Due to the high population density in these areas, it is necessary to immediately adopt the necessary programs to improve the quality of physical resilience criteria in the city.

Correct analysis of the housing market situation and correct knowledge of the factors affecting housing, especially in terms of its price and the extent of the impact of each of them, can help planners and officials in the correct analysis and forecast of the future situation and appropriate Provide appropriate solutions. The aim of this study was to identify the drivers of housing price in Khorramabad. Theoretical data were prepared by documentary method and experimental data by survey method based on Delphi method. The statistical population of the study is 30 experts and specialists in the field of housing in Khorramabad city were selected by purposive sampling. Delphi methods, cross-sectional analysis and MicMac software were used to analyze the data. For this purpose, first 23 factors were identified by Delphi method and using descriptive questionnaires by experts. In the next step, the matrix of cross-effects was designed to measure the impact of factors on each other and provided to experts. Finally, out of a total of 23 initial factors affecting housing prices in Khorramabad, 12 factors were identified as key factors of the system. Size: Household income, land price, building density, number of units and floors, access to urban facilities and services, population density, geographical location of lands, uninhabited future uses, number of rooms, security status, size of property plots, demand status.