نوع مقاله : مطالعه موردی
موضوعات
عنوان مقاله English
نویسندگان English
Introduction
Urban resilience is a concept that emphasizes the ability of cities to absorb, adapt to, and recover from environmental and social crises. Due to its geographical location within the Alborz mountain range, Damavand faces threats such as earthquakes, floods, and landslides. Weak spatial planning and inefficient infrastructure further exacerbate its vulnerability. Urban resilience, as a key concept in urban planning, refers to the ability of an urban system to withstand, adapt to, and recover from environmental, social, and economic hazards. In Iran, the importance of this concept is amplified due to the frequent occurrence of natural disasters such as earthquakes, floods, and droughts, particularly in cities with sensitive geographical locations. Damavand, located within the Alborz mountain range and near active fault lines, is exposed to risks such as earthquakes, floods, and landslides. In addition to these environmental challenges, this region’s dynamic mix of urban and rural settlements has added further complexity to resilience planning. Previous research has emphasized the importance of integrated planning and the reinforcement of urban infrastructure, highlighting the effective role of disaster management programs, collaboration between urban and rural areas, and the use of modern technologies in enhancing urban resilience. Additionally, the use of multi-criteria analysis methods and Geographic Information Systems (GIS) for assessing the physical vulnerability of cities has been emphasized in international research. This study aims to analyze the urban resilience of Damavand using indexing and spatial mapping methods to identify vulnerable neighborhoods and provide recommendations for enhancing resilience.
Materials and Methods
This study employed indexing and spatial mapping methods for resilience, combining spatial analysis and resilience indicators to identify vulnerable zones and propose effective solutions. ArcGIS Pro software was used for data analysis, and the research process was carried out in several main stages.
First, a conceptual and operational model of urban resilience was designed. This model was developed through document review and analysis of the research background to identify the main components of resilience, including environmental resilience, economic dynamism, spatial efficiency, and social diversity. Each of these components was evaluated using selected indicators.
Next, the required data were extracted from various sources, including the 2016 census, spatial data and GIS layers, satellite imagery, and information from relevant organizations. These data were processed in the ArcGIS environment, and thematic maps and necessary information layers for analysis were prepared.
For the spatial analysis of resilience indicators, relevant indicators for each component were selected and analyzed separately. These analyses included Kernel Density analysis for indicators such as population density, urban green spaces, and commercial and agricultural land uses, Network Analysis to examine access to emergency services and transportation stations, and Connectivity analysis using Space Syntax (depthMapX) to evaluate the connectivity of the street network. Additionally, land use change analysis was conducted using Google Earth Engine to identify uncontrolled land use changes. Finally, an overlay analysis combined different indicators to produce the final urban resilience maps.
In the final stage, the prepared maps for each resilience component were reviewed. Each map was prepared in raster format, and areas with the highest and lowest levels of resilience were identified. A composite resilience map was extracted by overlaying the four raster maps, where green indicates the highest resilience score and red indicates the lowest urban resilience score. To analyze the relationship between resilience indicators, spatial regression analysis and scatter plots were prepared. These analyses helped identify spatial patterns and provide practical recommendations for enhancing urban resilience.
Findings
This study examined the relationship between the composite urban resilience index and four key components—environmental resilience, economic dynamism, spatial efficiency, and social diversity—in the neighborhoods of Damavand. Scatter plots and spatial regression models were used to analyze these relationships, providing significant insights into resilience patterns in the city.
The assessment of environmental resilience revealed that this factor plays a decisive role in improving the spatial resilience of neighborhoods. Neighborhoods with higher environmental sustainability experience greater resilience. In contrast, areas facing environmental degradation, soil erosion, and pressure on ecological resources are more vulnerable. Spatial regression analysis showed that neighborhoods with more vegetation and suitable environmental infrastructure have greater stability against natural disasters and ecological changes.
In the area of economic dynamism, the findings indicate that neighborhoods with stable economic activities, suitable commercial infrastructure, and job diversity exhibit higher levels of resilience. On the other hand, despite overall high resilience in some neighborhoods, economic inequalities were observed, which may be due to differences in access to economic opportunities and employment infrastructure. Economically dynamic neighborhoods show greater flexibility in facing economic crises and less dependence on limited financial resources.
The relationship between spatial efficiency and urban resilience was also significantly positive. Neighborhoods with coherent spatial planning, adequate access to urban services, and efficient transportation infrastructure have higher resilience levels. In contrast, irregular land use distribution, inefficient communication networks, and a lack of functional public spaces were identified as factors that can reduce resilience in some neighborhoods. Particularly in areas with high population density and a lack of integrated transportation systems, the likelihood of vulnerability to urban crises increases.
The analysis of social diversity showed that this component plays an important role in enhancing resilience. Neighborhoods with diverse ethnic, cultural, and economic populations perform better in facing crises due to stronger social capital, greater intergroup interactions, and high social participation. In contrast, neighborhoods with less social cohesion are often more vulnerable and cannot manage social and economic crises. Additionally, despite high social diversity in some neighborhoods, challenges such as cultural tensions or a lack of cooperation among local groups were observed, highlighting the importance of social policies in enhancing neighborhood resilience.
Conclusion
This study’s results indicate that Damavand’s urban resilience is influenced by four key components: environmental resilience, economic dynamism, spatial efficiency, and social diversity. Neighborhoods with efficient urban infrastructure, physical cohesion, and diverse land uses have higher resilience levels, while areas with topographic constraints, uneven development, and insufficient infrastructure are more vulnerable. Specifically, the Gilavand neighborhood, due to its strategic location, access to urban infrastructure, and economic dynamism, showed the highest resilience. At the same time, Cheshmeh A’la and Shahrak Avishan, due to their distance from service centers, uncontrolled villa construction, and environmental challenges, had the lowest resilience levels. The neighborhoods of Oureh, Ruhafza, Farameh, and Hesar were at a moderate level, attributed to their favorable access to urban services and public transportation. Accordingly, strategies such as strengthening environmental infrastructure, sustainable development of urban spaces, optimizing land use, enhancing the local economy, and increasing social capital can help improve the resilience of Damavand. This study, by presenting a combined approach based on resilience indexing and spatial mapping, provides a model for analysis and planning in similar cities and can serve as a basis for future decision-making to reduce vulnerability and enhance urban resilience.
کلیدواژهها English
