Introduction
Resilience, as a key concept in rural development, reflects the ability of communities to cope with crises, adapt to changing conditions, and return to a desirable state after disturbances. In recent years, it has become central to analyzing the challenges of rural areas and serves as a tool for measuring social and economic sustainability. Lorestan Province—especially the Northern Beyranvand Rural District—represents a vulnerable context due to its mountainous geography, insufficient infrastructure, heavy dependence on traditional agriculture, and youth outmigration. This study aims to assess and spatially analyze the resilience of the district’s villages, identify critical weak points and potential capacities, and propose strategies to enhance their resilience.
Methodology
This is an applied study conducted with a descriptive–analytical approach. The statistical population comprises all villages in the Northern Beyranvand Rural District of Khorramabad County. Four main dimensions of resilience—social, economic, infrastructural, and institutional–participatory—were selected as the evaluation framework, with a set of composite indicators for each dimension, such as the presence of health houses, access to water and electricity, village councils and dehyars (local managers), diversity of agricultural and livestock activities, local markets, and volunteer groups.
To avoid subjective bias, equal weighting was applied to all indicators. Villages’ resilience levels were ranked using the TOPSIS technique, which calculates each option’s distance from the positive and negative ideal solutions. For spatial analysis, Kernel Density Estimation was used to identify spatial clusters, and Moran’s I spatial autocorrelation index assessed the statistical significance of distribution patterns. These methods allowed for a combined quantitative and spatial assessment of resilience.

Results and discussion
The results revealed significant differences among villages. In terms of social capital, villages such as Khoshkeh Rud, Tepe Gaji, and Chaghabel ranked highest due to active Islamic councils, local volunteer groups, and influential religious institutions. Conversely, villages like Samadabad and Malakeh scored lowest because of weak institutional networks, which reduced their capacity for collective action and crisis recovery.
In the economic dimension, villages like Deh Reksan, Dar Balut-e Pain, and Gol Zard demonstrated greater flexibility to economic shocks, benefiting from relatively diversified livelihoods and better access to markets. By contrast, many villages remain dependent on single-crop farming or subsistence livestock husbandry, making them highly vulnerable to climate variability or market fluctuations.
Infrastructure analysis showed that access to basic services is the most critical factor differentiating resilience levels. Villages such as Gol Zard, Dar Balut-e Bala, and Tepe Gaji scored highest due to their access to safe drinking water, electricity, piped gas, asphalted roads, and health centers. Villages like Sarab Nourkeh and Samadabad, facing serious infrastructural deficits, ranked lowest. These findings highlight that poor infrastructure amplifies the impacts of crises and slows recovery.
The TOPSIS ranking placed only a few villages—namely Tepe Gaji, Gol Zard, and Dar Balut-e Pain—in the high-resilience category. Most villages fell into a medium resilience level, indicating relative fragility, while more than a quarter of the villages were in the lowest category. Kernel density maps confirmed this pattern: resilient clusters are concentrated in the western and central areas, while low-resilience clusters are dispersed across the eastern and southern parts of the district.
Moran’s I analysis revealed that social and economic resilience lacked significant spatial clustering, suggesting that these dimensions are influenced more by internal village factors than by geographic proximity. Only the infrastructural dimension exhibited a significant clustered pattern (Moran’s I ≈ 0.31, p < 0.05), showing that well-serviced and under-served villages tend to group spatially. Overall resilience also lacked a cohesive spatial pattern, emphasizing the importance of local capacities over inter-village relationships.

Conclusion
This study demonstrates that rural resilience in Northern Beyranvand is most constrained by social and infrastructural weaknesses. Although social capital and livelihood diversity are important, the absence of critical infrastructure remains the primary barrier to sustainable resilience. To address these challenges, development strategies should adopt an integrated and network-based approach.
1. Strengthen vital infrastructure: Equitable development of water, electricity, gas, roads, and public service centers in under-served villages to reduce spatial disparities.
2. Enhance social and institutional capital: Support Islamic councils, local organizations, and volunteer groups to build social cohesion and collective crisis response capacity.
3. Diversify rural economies: Develop agro-processing industries, create shared local markets, and encourage entrepreneurship to reduce dependence on traditional farming.
4. Build inter-village networks: Foster cooperation between well-resourced and disadvantaged villages to transfer capacities and reduce spatial inequality.
5. Leverage local knowledge and experience: Combine traditional resource management practices with modern technologies to improve adaptive capacity.
6. Design comprehensive rural development policies: Integrate social, economic, and infrastructural dimensions simultaneously at the regional level.
These measures can reduce vulnerability, strengthen sustainable resilience, and provide a foundation for balanced and long-term development in the study area. The findings underscore that resilience is a multidimensional concept, shaped by the interplay of social, economic, and spatial factors. Coordinated, participatory strategies at both local and regional scales are essential to improve adaptive capacity, recovery potential, and overall community resilience against future crises.