Objective Forest canopy closure is a key indicator characterizes forest structure and growth conditions. Quantitatively assessing the current and potential canopy closure of forests in Northeast China, and dynamically evaluating degradation characteristics in conjunction with net primary productivity (NPP), is of great significance for enhancing regional forest quality with precision and for responding to climate change.

Method Based on 11 472 forest canopy closure datasets at 0.5 m resolution, field plot measurements, a multi-forest-type random forest model was constructed to map the spatial distribution of forest canopy closure in Northeast China at a 100 m grid scale. Building on this foundation, by integrating climatic, soil, and topographic factors, potential canopy closure was estimated using gradient binning and conditional screening methods. Combined with areas exhibiting a decline trend in NPP, the extent and degree of forest degradation were identified.

Result The R² of the random forest model ranged from 0.567 to 0.774, indicating a relatively high fitting accuracy. The spatial pattern of forest canopy closure in Northeast China generally exhibited a “low in the north and high in the south” distribution, with values ranging from 0.264 to 0.976. The average canopy closure values for natural and plantation forests were 0.716 and 0.689, respectively. At the provincial scale, Jilin showed the highest mean canopy closure for both natural and plantation forests (0.738 and 0.717, respectively), whereas Heilongjiang and Inner Mongolia exhibited comparatively lower values. Statistical analysis revealed that canopy closure differed significantly between forest origins (natural/plantation) and among forest types (p < 0.001). The study identified a total of 9.936 million hectares of forest experiencing varying degrees of degradation in Northeast China, accounting for 24.27% of the region’s total forest area.

Conclusion Northeast China’s forests generally exhibit high canopy closure with a wide range of values. Natural forests outperformed plantations, and broadleaf forests surpassed mixed and coniferous forests. However, substantial areas of degradation still existed. This study employed remote sensing spectral data, climate data, and soil and topographic data as key parameters, and, based on estimates of potential canopy closure and NPP trends, was able to accurately, rapidly, and comprehensively identify forest degradation in Northeast China. It provides a novel approach and perspective for assessing current forest structure and for further quantitative studies of forest functions in the future.