Canopy radiative transfer models employ a large number of vegetation architectural and leaf biochemical attributes. Studies of leaf biochemistry show a wide array of chemical and spectral diversity that suggests that several leaf biochemical constituents can be independently retrieved from multi-spectral remotely sensed imagery. In contrast, attempts to exploit multi-angle imagery to retrieve canopy structure only succeed in finding two or three of the many unknown canopy arhitectural attributes. We examine a database of over 5000 destructive tree harvests from Eurasia to show that allometry - the covariation of plant form across a broad range of plant size and canopy density - restricts the architectural diversity of plant canopies into a single composite variable ranging from young canopies with many short trees with small crowns to older canopies with fewer trees and larger crowns. We use the measured variance and covariance of plant canopy architecture in these stands to drive the radiative transfer model DISORD, which employs the Li-Strahler geometric optics model. This correlations introduced in the Monte Carlo study are used to determine which attributes of canopy architecture lead to important variation that can be observed by multi-angle or multi-spectral satellite observations, using the sun-view geometry of MODIS.
Results/Conclusions
While the majority of MODIS geometries in the boreal and temperate regions are more closely aligned with the plane perpendicular to the axis in which the sun casts shadows, there are nevertheless frequent pairs of observations in the principal plane, in which the effects of canopy structure on shading is very sensitive. In these measurements along the principal plane, the tree number density, the crown radius, and the ground cover each have strong impacts on the slope of the reflectance as viewed from different angles. This suggests that tree number and crown size are retrievable from MODIS observations. These canopy attributes themselves covary strongly with tree size, mass, and other ecological attributes such as net ecosystem exchange and successional state, which suggests that allometric constraints to inversion of multi-angle remote sensing can be a useful tool in diagnosing forest condition over large spatial scales. In contrast to temperate biomes, tropical forests have many fewer measurements of crown dimensions that could be used to constrain biomass estimates allometrically. We propose that airborne surveys to characterize tropical forest allometry can inform larger scale analyses with coarser satellite imagery in order to better diagnose the status of tropical forests.
