The spatial scaling effect of discrete canopy effective leaf area index retrieved by remote sensing

Leaf area index (LAI) is a critical biophysical variable that describes canopy geometric structures and growth conditions. The scaling effect of LAI has always been of concern. Considering the effects of the clumping indices on the BRDF models in discrete canopies, an effective LAI is defined. The effective LAI has the same function of describing the leaves thick degree with the traditional LAI. The spatial scaling effect of discrete canopies showed significant differences compared with continuous canopies. Based on the directional second derivative method of effective LAI retrieval, the mechanism for producing the spatial scaling effect for discrete canopy LAI has been discussed and a scaling transformation formula for effective LAI has been suggested in this paper. Theoretical analysis showed that the mean values of effective LAIs retrieved from high resolution pixels were always equal to or larger than the effective LAIs retrieved from the corresponding coarse resolution pixels. Both the conclusions and the scaling transformation formula were validated by the airborne hyperspectral remote sensing images obtained in Huailai County, Zhangjiakou City, Hebei Province, China. The scaling transformation formula agreed well with the effective LAI retrieved from hyperspectral remote sensing images.