Abstract: Vegetation clumping index (CI) is a structural parameter characterizing spatial clustering degree of vegetation canopy leaves, and playing an important role in extracting other vegetation parameters and in modeling land surface． Currently, remote sensing CI products are limited to a few multiangular satellite-borne sensors, compared to other remote sensing products (e.g., leaf area index, LAI). Therefore, study on long time series of CI products is needed: many models do not consider the cyclical variations of CI product in many applications． The global long-time series (2001-2019) and monthly CI products developed and produced by the author’s research team are therefore used here, to explore interannual periodic variations of 19-year CI product on a global scale, with Fourier decomposition technique． The CI product is first preprocessed by screening out and smoothening outliers, and filling in gaps, to generate a relatively complete year-to-year time series of CI product, with effective pixel proportion accounting for 75.58% of vegetation area on the global scale． Assuming that interannual variations of time-series CI product can be decomposed into a sequence composed of multiple sets of cosine wave signals with possible additive noise of random distribution, discrete Fourier transform is used to extract the cosine wave with the largest amplitude (main wave) in the time series． This is further used as the main index to characterize interannual periodic variation frequency． The period and amplitude of main waves are analyzed and further cross-compared with annual phenological NumCycles (NC) and peak time (Peak_1) of MODIS phenological products (MCD12Q2). Anti-noise performance of this method is tested by simulation data and high-quality CI pixels． The pixel proportions with = 12 are found significantly larger than in other periods, accounting for 76.22% of the study area． This indicates that interannual variations with 12-month period length is most significant among various periodic variations of CI time frequencies． Validation results show that the period with = 12 in the study area highly coincided with annual phenological period of MODIS phenological products with = 1, with validation accuracy reaching to 96%． For the pixel with = 12, low-peak month of the main wave is close to value of MODIS phenological product and average difference between them is about 1.37 months． In general, low-peak month of CI product (i.e., month with most clumping vegetation foliage) is earlier than peak value of MODIS phenological product, probably related to greenness of vegetation foliage． This implies that maximum clumping status is probably earlier to maximum greenness status for vegetation foliage． The present study provides evidence for improved understanding of interannual periodic variations for vegetation foliage clumping effect．