The synergistic development of new quality productive forces (NQPFs) and forestry economic resilience is vital for sustainable growth in China’s forestry sector, positioning the country as a global leader. This study develops a theoretical framework and employs spatial Kernel density, the Gini coefficient, spatial Markov chains, and geographical detectors to analyze coordination levels, regional disparities, evolutionary trends, and influencing factors. The results reveal that national coordination has progressed from imbalance to high-quality synergy, though regional disparities remain. Development trajectories show stability, with strong path dependence, a Matthew effect, and high transition probabilities between adjacent levels, accompanied by significant spatial spillovers. Factors such as economic development, openness, marketization, social security, the digital economy, and infrastructure play a major role in enhancing coupling coordination, while policy intervention and human capital show limited standalone effects, although their interactions are important. Based on these findings, policy recommendations are provided to guide China’s forestry economy in the new era.

Coordinating new-type urbanization and digital village construction supports urban–rural integration. Using 2012–2023 panel data for 30 Chinese provincial-level regions, this study constructs subsystem indices, calculates the coupling coordination degree (CCD) to summarize joint development, and assesses relative balance separately. The analysis combines kernel density estimation, Dagum Gini decomposition, traditional and spatial Markov chains, spatial autocorrelation tests, and a two-way fixed-effects spatial Durbin model. Both indices increased, and relative balance improved despite a widening absolute index gap. CCD rose as provincial disparities narrowed, but eastern leadership persisted alongside rapid western catch-up, steady central improvement, and slower northeastern progress. East–west and coastal–inland gradients persisted, with interregional disparities remaining dominant. CCD transitions were persistent and gradual, with conditional probabilities varying by initial levels and neighborhood conditions. Provincial CCD showed significant positive spatial dependence. Human capital and fiscal expenditure on science and technology had significant positive local and spatial indirect associations with CCD, while the positive association of fiscal support for agriculture was mainly local. Some estimated effects of openness, industrial structure upgrading, and agricultural machinery intensity were significantly negative. The findings support investment in human capital and technology, cross-regional collaboration, and region-specific policies.