Key Factors for Assessing the Physical Resilience of Urban Neighborhood Fabrics

Introduction
Urban resilience has become a key concept in contemporary urban planning due to increasing natural hazards, climate change, and the growing complexity of cities. While resilience has been widely studied from social, economic, and ecological perspectives, the physical resilience of urban neighborhoods has received comparatively less attention. Physical resilience reduces vulnerability by improving the ability of the built environment to resist, absorb, and recover from external shocks. Therefore, identifying the spatial characteristics that strengthen neighborhood resilience is essential for sustainable urban development.
Previous studies have mainly evaluated physical resilience through separate indicators such as building quality, transportation infrastructure, land use, and accessibility. However, these approaches rarely consider the interaction among physical components of urban neighborhoods. Since neighborhoods function as interconnected systems, resilience should be assessed through the relationships among their constituent elements rather than isolated variables. Accordingly, this study adopts a systemic perspective that conceptualizes urban texture as an integrated structure composed of the street network, blocks, parcels, and buildings. This approach provides a practical framework for identifying resilient and vulnerable urban patterns and supports urban design interventions in deteriorated neighborhoods.
Objective
This study aims to identify the physical factors influencing neighborhood resilience through a systemic urban design approach. It develops a conceptual framework linking urban texture with physical resilience, evaluates the relative importance of physical indicators using integrated spatial analysis, and identifies resilient and vulnerable areas to support urban regeneration and resilience-oriented planning.
Method
The research employs an applied descriptive–analytical methodology within a systemic framework for evaluating neighborhood physical resilience. Following a comprehensive review of the literature on urban resilience, urban morphology, and systems theory, the principal physical indicators were identified and classified according to the structural components of urban texture, including the street network, blocks, parcels, intersections, and buildings.
The analysis combines two complementary techniques. Spatial configuration analysis was conducted using Depthmap to evaluate accessibility, connectivity, and spatial integration within the street network. Geographic Information Systems (GIS) were then used to analyze the spatial distribution of resilience indicators through 30 × 30 m raster cells.
The relative importance of each indicator was determined using the Analytic Hierarchy Process (AHP) based on pairwise comparisons completed by twenty experts and processed in Expert Choice. Weighted indicators were integrated in the GIS environment to produce a comprehensive physical resilience map. Variables included street width and length, intersection density, dead-end distribution, parcel size, block dimensions, building density, number of stories, construction quality, and structural materials. The integration of Depthmap, GIS, and AHP constitutes the main methodological innovation of the study by combining network analysis, spatial evaluation, and expert judgment within a unified framework.
Findings
The results indicate that neighborhood resilience depends on the interaction of multiple physical components rather than individual indicators. The integrated framework successfully identified resilient and vulnerable areas by simultaneously evaluating street networks, block configuration, parcel structure, and building characteristics.
Street network characteristics were found to play a decisive role in physical resilience. Greater street width, higher connectivity, better accessibility, appropriate street length, and a balanced distribution of intersections significantly improve emergency access, evacuation efficiency, and post-disaster recovery. Conversely, narrow streets, poor connectivity, and excessive dead ends increase physical vulnerability.
Urban morphology also strongly influences resilience. Appropriate block dimensions, balanced parcel subdivision, and coherent urban grain improve accessibility and flexibility for emergency response, whereas fragmented urban fabrics and oversized blocks reduce permeability and adaptive capacity.
Building characteristics represent another major determinant of resilience. Building density, number of stories, construction quality, structural materials, and building age significantly affect neighborhood performance during disasters. Areas containing newer buildings with reinforced concrete or steel structures and higher construction quality generally exhibit greater resilience than deteriorated neighborhoods dominated by weaker construction materials.
The AHP results indicate that street width, street length, building density, construction quality, structural materials, parcel size, block dimensions, and building height are among the most influential indicators affecting physical resilience. Their combined evaluation provides a more accurate assessment than considering individual variables separately.
The integration of spatial syntax analysis with GIS proved highly effective for evaluating neighborhood resilience. While spatial syntax identifies movement patterns and accessibility, GIS enables the integration of multiple spatial indicators into a comprehensive assessment. The study further demonstrates that resilience emerges from the interaction among circulation systems, urban blocks, parcels, buildings, and open spaces. Weakness in one subsystem can significantly reduce the resilience of the entire neighborhood, emphasizing the need for a systemic rather than fragmented approach.
Conclusion
This study highlights the importance of the physical dimension of neighborhood resilience from a systemic urban design perspective. Unlike conventional approaches emphasizing post-disaster recovery, it focuses on reducing vulnerability before disasters occur by identifying the physical characteristics that strengthen neighborhood resilience.
The findings confirm that accessibility, connectivity, urban morphology, building quality, construction materials, and spatial configuration collectively determine the adaptive capacity of neighborhoods. Consequently, resilience should be enhanced through integrated planning strategies instead of isolated physical interventions.
The proposed methodology, combining Depthmap, GIS, and AHP, provides a reliable framework for evaluating neighborhood resilience and prioritizing urban interventions. The results also offer practical guidance for urban regeneration by emphasizing improvements in street connectivity, building quality, vulnerable structures, urban density, and the balance between built-up areas and open spaces.
Finally, the proposed systemic framework can be adapted to different urban contexts and provides a useful basis for future studies integrating physical, social, economic, environmental, and institutional dimensions of resilience to support more sustainable and disaster-resilient urban development.