Estimating clumping index of sparse forest using hemispherical photographs combined with Geoeye-1 data

Clumping index is a critical physical parameter used to describe the clumping effect of vegetation canopy. In many studies, foliage elements are assumed to distribute randomly in the canopy and the clumping index is 1. However, for the irregularly or artificially spaced discrete vegetation canopies, such as savanna and sparse forests, the assumption is not in accordance with the actual case, the clumping index varies in the range of 0 to 1. As a result, the Leaf Area Index (LAI) retrieved directly from remote sensing data is always underestimated. Optical instruments, such as LAI-2000 canopy analyzer, TRAC, fish-eye camera, are difficult to measure the clumping index for sparse forests directly. In this paper, taking populus euphratica sparse forest in Heihe Basin as the research object, a new method combining hemispherical photography and high resolution images is established to estimate the clumping index. The results show that the method can accurately calculate clumping index and LAI for sparse forests and improve the validation of LAI products in water stressed regions.