Abstract
The foliage Clumping Index (CI) is an important vegetation structure parameter that allows for the accurate separation of sunlit and shaded leaves in a canopy. The CI and its seasonality are critical for global Leaf Area Index (LAI) estimating and ecological modelling. However, the cover of snow tends to reduce the reflectance anisotropy of the vegetation canopy and thus probably influences CI estimates. In this paper, we investigate the influence of snow on the magnitude and seasonal variation of the CI retrieved from Moderate-resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF) products based on field-measured CI and statistics from the global MODIS CI product. We find that the backup algorithm can effectively correct abnormally large CI values and obtain more reasonable CI retrievals than the main algorithm without any constraints in snow-covered areas. Validation indicates that the time-series CI product shows the potential in investigating the trajectories of the clumping effect in snow seasons. For evergreen forests, the clumping effect is relatively stable throughout the year; however, for deciduous vegetation types, CI values tend to display significant seasonal variations. This study suggests that the latest version of the global MODIS CI product, in which the backup algorithm is used to process the snow-covered pixels, has improved accuracy for CI retrievals in snow-covered areas and thus is probably more suitable as the input parameter for ecological and meteorological models.
Highlights
The leaves of natural vegetation canopies are usually organized into various canopy structures, including tree crowns, whorls, branches, and shoots [1,2]
The relationship between the Normalized Difference between Hotspot and Darkspot (NDHD) and the Clumping Index (CI), which was originally developed by Chen et al [4], has been used to produce regional and global CI products based on various multi-angular data from the Polarization and Directionality of the Earth’s Reflectances (POLDER, ~6 km resolution) sensor [4,32,33,34], Moderate Resolution Imaging Spectroradiometer (MODIS, ~500 m resolution) sensor [24,26,35,36,37,38,39] and Multi-angle Imaging SpectroRadiometer (MISR, ~275 m resolution) sensor [5]
The CIMODIS values retrieved by the main algorithm are much larger than the field-measured CI values on snow-covered days
Summary
The leaves of natural vegetation canopies are usually organized into various canopy structures, including tree crowns, whorls, branches, and shoots [1,2]. The CI is usually assumed to be seasonally invariant in land surface models [40,41,42] because of the limited data availability. Several studies based on the ground measurements of long-term time series CI data indicate that the CI could have very strong seasonal variations due to species phenology [5,23,43,44]. Various studies based on spaceborne CI products indicate that the retrieved CI values exhibit distinguishable seasonal variations [4,5,6,37,38,39]. The seasonality of the CI should be carefully explored in spaceborne CI products
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