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Title: Estimation of Canopy Foliar Biomass with Spectral Reflectance Measurements

item WANG, LINGLI - George Mason University
item Hunt Jr, Earle
item QU, JOHN - George Mason University
item HAO, XIANJUN - George Mason University
item Daughtry, Craig

Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/24/2010
Publication Date: 12/22/2010
Citation: Wang, L., Hunt, E.R., Qu, J.J., Hao, X., Daughtry, C.S. 2010. Estimation of canopy foliar biomass with spectral reflectance measurements. Remote Sensing of Environment. 115:836-840.

Interpretive Summary: Remote sensing can be used to estimate vegetation cover, leaf area index, and canopy water content using indices that compare one wavelength of a reflectance spectrum with another wavelength. Determining foliar dry biomass using remote sensing is important to: determine growth, determine nutrient concentrations, and predict vegetation susceptibility to wildfire. Recently, the Normalized Dry Matter Index (NDMI) was developed for estimating the foliar dry biomass for fresh green leaves; in this study we use reflectance models and spectral reflectance data for stacks of leaves to test if the NDMI can be used to predict dry matter content for vegetation canopies. The amount of dry matter predicted by NDMI was about equal to the leaf dry matter content multiplied by the leaf area index

Technical Abstract: Canopy foliar biomass, defined as the product of leaf dry matter content and leaf area index, is an important measurement for global biogeochemical cycles. This study explores the potential for retrieving foliar biomass in green canopies using a spectral index, the Normalized Dry Matter Index (NDMI). This narrow-band index is based on absorption at C-H bond stretch overtone and is correlated with leaf dry matter content in fresh green leaves. PROSPECT and SAIL model simulations suggest that the NDMI at the canopy-scale is able to minimize effects of leaf thickness and leaf water content and to maximize sensitivity to variation in canopy foliar biomass. The simulation outputs were analyzed with an ANOVA, and 86.7% of the variation in NDMI is explained by leaf dry matter content. NDMI was linearly related to foliar biomass (g cm-2) from model simulations (R2 = 0.968). NDMI calculated from spectral reflectances of one to four stacked leaves were also correlated with total leaf biomass (R2 = 0.59). These results suggest that it may be possible to determine foliar biomass from airborne and satellite-borne imaging spectrometers, such as NASA's HyspIRI mission.