In the process of sustainable transformation, resource-based cities (RBCs) in Heilongjiang are in a dilemma. Resilience is a key capability to help RBCs deepen sustainable development, adapt to shocks, and exit the transformation dilemma. This study aims to clarify the resilience measurements and dynamics of RBCs and propose targeted resilience enhancement strategies. First, we construct a resilience indicator system based on the urban complex adaptive system (CAS) and use principal component analysis (PCA) to specify indicator weights to obtain the resilience values of RBCs in Heilongjiang Province during 2010–2019, then use cluster analysis to classify five resilience grades. Second, we identify and analyze the resilience dynamics of RBCs in Heilongjiang Province from 2010–2019 based on the adaptive cycle framework. The results indicate that the overall resilience dynamics of RBCs have exhibited an upward trend over the past decade, but there are clear variations in the level of resilience values and dynamics between the different types of RBCs. The petroleum-based city has the highest level of resilience, is less affected by shocks, and recovers quickly. Forest-based cities have a medium level of resilience and are able to recover from shocks, but they fail to improve and remain at a medium level for a long time. Coal-based cities have a low level of resilience and find it difficult to recover from shocks, but this has improved since 2017. Finally, we propose targeted resilience enhancement strategies for RBCs of different types and resilience levels in Heilongjiang Province to provide RBCs with directional guidance for overcoming the development dilemma through resilience measures.

Resource-based cities frequently face severe bottlenecks during their structural transformation. Viewed through the lens of the adaptive cycle, urban resilience offers a framework to understand the dynamic evolution of urban systems and identify new development opportunities. This study uses Heilongjiang Province, a quintessential resource-based region in China, as a case study to examine the resilience evolution of three types of resource-based cities (oil, coal, and forestry) from 2010 to 2019. Applying the PCA-Catastrophe method and Grey Relational Analysis, we identify the dominant driving factors and their evolutionary pathways. The results reveal that: (1) Resource-based cities exhibit significant typological heterogeneity and incomplete cyclicity in their development. (2) Resilience dynamics are characterized by multi-dimensional interplay and alternating fluctuations. Specifically, oil-based cities are dominated by economic and natural resource resilience, displaying alternating fluctuations; forestry-based cities are driven by social and natural resource resilience, reflecting an interplay between ecological conservation and social security; and coal-based cities undergo a transition from resource dependence to system reconstruction, driven by socio-economic and natural resource factors. (3)The overall resilience dynamics of these cities are heavily influenced by top-down policy interventions. Consequently, we recommend that resource-based cities formulate differentiated transition strategies tailored to the specific resilience evolution patterns of each city type.