HR: 0800h
AN: B21A-0039    [Abstracts]
TI: Derivation of Clumping Index via Using BRDF Models and MISR and MODIS Data
AU: * Su, L
EM: sul@email.unc.edu
AF: UNC Deptment of Geography, Saunders Hall, CampusBox3220, Chapel Hill, NC 27599- 3220, United States
AU: Song, C
EM: csong@email.unc.edu
AF: UNC Deptment of Geography, Saunders Hall, CampusBox3220, Chapel Hill, NC 27599- 3220, United States
AB: Clumping index quantified the level of foliage grouping within distinct canopy structures relative to a random distribution. Vegetation foliage clumping significantly alters its radiation environment and therefore affects vegetation growth as well as water and carbon cycles. The clumping index is useful in ecological and meteorological models because it provides new structural information in addition to the effective Leaf Area Index retrieved from mono-angle remote sensing. Multi-angle sensor, for example Multi-angle Imaging SpectroRadiometer (MISR) and Moderate Resolution Imaging Spectroradiometer (MODIS), observations provide a means to characterize the anisotropy of surface reflectance, which has been shown to contain information on the structure of vegetated surfaces. This study shows that available multi-angle data products, MISR RPV Bi-directional Reflectance Distribution Function (BRDF) model parameters and MOIDS kernel-driven BRDF model parameters, can be used to computing the clumping index. First of all, the hotspot and darkspot reflectance were calculated by using MISR RPV and MOIDS kernel-driven BRDF models. Then the clumping index was obtained by applying existed relationship between the clumping index and an index derived hotspot and darkspot. The preliminary findings on estimating the clumping index are: 1) red band is better than near infrared band. 2) The hotspot and darkspot from smaller solar zenith angle is better than ones from larger solar zenith angle. 2) The kernel-driven model and MODIS BRDF parameters product is superior that the RPV model and MISR BRDF parameters product. In order to improve existed approaches of deriving the clumping from multi-angle measurements, the underlying mechanism of foliage structure determining the clumping index have been explored using a geometrical optical and radiative transfer model named GORT. This presentation will display the new methods of computing the clumping index from multi-angle measurements, and evaluation of performance on estimating the clumping index the RPV model and the kernel-driven model.
DE: 0400 BIOGEOSCIENCES
DE: 0428 Carbon cycling (4806)
DE: 0430 Computational methods and data processing
DE: 0480 Remote sensing
DE: 1600 GLOBAL CHANGE
SC: Biogeosciences [B]
MN: 2007 Fall Meeting