Introduction
Urban areas are increasingly exposed to natural disasters due to rapid population growth, spatial concentration of infrastructure, and intensified climate-related hazards. As a result, urban resilience has emerged as a critical concept in regional and urban planning, aiming to reduce vulnerability and enhance the capacity of cities to absorb, adapt to, and recover from disruptive events. Urban resilience goes beyond merely returning to pre-disaster conditions and emphasizes adaptive learning, institutional flexibility, and long-term sustainability. In disaster-prone regions, understanding resilience at sub-national scales is particularly important, as spatial disparities in socio-economic, infrastructural, and institutional capacities strongly influence disaster outcomes.

Kurdistan Province, located in western Iran within the Zagros mountain range, is characterized by complex topography, dispersed settlements, and varying levels of development across its counties. The province has experienced multiple natural hazards in recent decades, including earthquakes, floods, and landslides, resulting in significant human, economic, and infrastructural losses. Despite these recurring events, comprehensive assessments of resilience at the county level remain limited. Existing studies often focus on single hazards or emphasize vulnerability rather than resilience as a multidimensional and dynamic capacity.

This study aims to assess and compare the level of resilience of counties in Kurdistan Province against natural disasters over three time periods (1996, 2006, and 2016) using the Baseline Resilience Indicators for Communities (BRIC) model. The main objectives are: (1) to identify key resilience indicators applicable at the county level based on data availability; (2) to analyze temporal changes in resilience across counties; and (3) to classify counties into resilience groups to support evidence-based regional planning. Accordingly, the research addresses the following questions: How has the level of resilience in Kurdistan counties evolved over time? Which counties exhibit higher or lower resilience capacities? What structural patterns can be identified to guide future resilience-oriented policies?

Methodology
This research is applied in nature and adopts a descriptive–analytical approach. The conceptual framework is based on the BRIC model, which conceptualizes resilience as a multidimensional construct encompassing social, economic, institutional, infrastructural, community, and environmental dimensions. Due to data constraints at the county level, a set of 20 indicators consistent with the BRIC framework was selected using official census and statistical data for the years 1996, 2006, and 2016.

Data analysis was conducted in several stages. First, Exploratory Factor Analysis (EFA) was applied to identify underlying resilience dimensions and assign weights to the selected indicators. The suitability of the data for factor analysis was confirmed through the Kaiser–Meyer–Olkin (KMO) test and Bartlett’s test of sphericity. Principal Component Analysis with Varimax rotation was used to extract and interpret factors. Based on eigenvalues and scree plot analysis, four major factors explaining a substantial proportion of variance were retained.

In the next stage, standardized factor scores were used as inputs for cluster analysis. The K-means clustering method was employed to classify counties into distinct resilience groups for each time period. This approach enabled a comparative assessment of spatial and temporal resilience patterns across the province. All statistical analyses were performed using SPSS software.

Results and discussion
The results of the exploratory factor analysis revealed four dominant resilience dimensions, reflecting combinations of social services and infrastructure capacity, emergency and health facilities, demographic and employment characteristics, and economic participation and social cohesion. These dimensions collectively represent the multifaceted nature of resilience and highlight the interdependence between physical infrastructure and socio-economic conditions.

Cluster analysis classified the counties into three resilience levels: low, medium, and high resilience. The findings indicate a clear temporal improvement in overall resilience across Kurdistan Province. In 1996, most counties were concentrated in the low-resilience cluster, reflecting limited infrastructure, weaker institutional capacity, and lower access to essential services. By 2006, an intermediate pattern emerged, with several counties transitioning into the medium-resilience group.

In 2016, resilience levels improved noticeably, with the majority of counties classified as moderately or highly resilient. Sanandaj, the provincial capital, consistently ranked highest across all three periods, benefiting from better access to healthcare, education, infrastructure, and economic opportunities. In contrast, counties such as Bijar and Divandareh repeatedly appeared in the low-resilience cluster, indicating persistent structural disadvantages and slower development trajectories.

The observed trends suggest that investments in public services, infrastructure expansion, and socio-economic development have contributed to enhanced resilience over time. However, the uneven distribution of these improvements underscores the importance of place-based and context-sensitive resilience planning. Without targeted interventions, existing disparities may continue to reproduce vulnerability in less-developed counties.

Conclusion
This study provides a longitudinal and spatially explicit assessment of urban and regional resilience against natural disasters in Kurdistan Province using the BRIC framework. The findings demonstrate that resilience is not static but evolves over time in response to development policies, infrastructure investment, and institutional capacity building. While overall resilience has increased between 1996 and 2016, significant inter-county disparities remain.

The results highlight the necessity of integrating resilience indicators into regional planning and disaster risk management strategies. Policymakers should prioritize counties with consistently low resilience by strengthening emergency services, improving infrastructure, promoting economic diversification, and enhancing community participation. Moreover, adapting the BRIC model to local socio-cultural and environmental contexts can improve its effectiveness as a planning tool.

By offering a systematic and comparative resilience assessment, this research contributes to the growing body of literature on disaster resilience in developing and hazard-prone regions. The methodological framework and findings can inform future studies and support evidence-based decision-making aimed at reducing vulnerability and fostering sustainable regional development.
Funding
There is no funding support.

Authors’ Contribution
Authors contributed equally to the conceptualization and writing of the article. All of the authors approved the content of the manuscript and agreed on all aspects of the work declaration of competing interest none.
Conflict of Interest
Authors declared no conflict of interest.

Acknowledgments
We are grateful to all the scientific consultants of this paper.