Long-term transitions and spatial clustering of forest canopy foliage clumping across China based on normalized clumping index

Forest canopy spatial organization influences ecosystem functioning, but long-term large-area assessment remains difficult. The clumping index (CI) quantifies departures of foliage from a random spatial distribution and can extend optical monitoring beyond greenness and canopy amount. Using the 2001–2020 Chinese Academy of Sciences clumping index (CAS-CI) record, we constructed a normalized clumping index (NCI) from CI values to improve comparability across regions and periods and evaluated its relevance, trends, seasonality, spatial clustering and associated factors across China’s forests. We compared NCI with optical indicators, spaceborne light detection and ranging (LiDAR) attributes and high-resolution tree-cover data; quantified trends and spatial autocorrelation; and used interpretable machine learning to examine associations with initial NCI, climate, topography, human activity and forest type. Robustness was examined through sensitivity analyses. NCI showed weak-to-moderate associations with optical and canopy-structure indicators (ρ = 0.256–0.596), and multivariable model comparisons showed that retaining NCI provided complementary out-of-block predictive information for all three Global Ecosystem Dynamics Investigation (GEDI) attributes. Increasing trends covered 69.91% of forest pixels, while 15.19% were stable and 14.90% decreased; significant increases and decreases accounted for 15.84% and 0.85%, respectively. Annual NCI was significantly clustered, and evergreen and deciduous forests showed contrasting seasonality. Initial NCI was most informative in short-term models, whereas longer-term patterns were associated with human activity, climate and topography. Although NCI does not directly measure complete three-dimensional canopy structure, its long-term analysis provides complementary information on relative foliage clumping and supports forest monitoring and conservation under ecosystem sustainable development.