HIERARCHICAL CHARACTERIZATION OF CANOPY ARCHITECTURE FOR BOREAL FOREST

Canopy architecture, the geometric organization of aboveground vegetat ion, provides an essential link between patterns observable by remote sensing and fundamental ecological processes. As part of the internati onal Boreal Ecosystem-Atmosphere Study (BOREAS); (1) we developed a hi erarchical approach for sampling canopy architecture, and (2) we acqui red a comprehensive data set for characterizing canopy architecture fo r the major BOREAS study sites. The approach involves a series of four sets of measurements at different spatial scales, ranging from the ec osystem to the leaf level: (1) regional characterization, involving me asurements of the climate, ecosystem, and landscape features; (2) stan d characterization, involving measurements of crown geometry (diameter at breast height (DBH), height, and crown extent), individual tree lo cation, and understory cover; (3) tree vectorization, involving detail ed sampling of the three-dimensional distribution of canopy elements a nd crown form; and (4) characterization of canopy geometry as seen fro m beneath, involving acquisition of a multitemporal catalog of hemisph erical photographs. The last three sets of measurements were then used to reconstruct the three-dimensional geometry of the canopy. By compa ring simulated hemispherical views upward from beneath this reconstruc ted canopy with in situ hemispherical photographs, the methodological approach was validated. Simulated photographs faithfully reproduced pa tterns observed for in situ hemispherical photographs, in particular, for gap fraction distributions of the middle ranges of zenith angles ( 20 degrees-70 degrees). Moreover, simulation of the gap fraction for t his middle portion of the zenith angle was insensitive to exact mappin g of the stand. The hierarchical data acquisition approach, involving mapping of tree locations and tree reconstruction, permits realistic r epresentation of canopy material distribution. Our approach and our co mprehensive data set provide a solid basis from which to integrate dat a gathered at the stand and tree scales, and a powerful tool for the s imulation of the light regime anywhere in the canopy.