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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #293981

Title: Determining leaf dry matter content using the normalized dry matter index and its possible application for estimating fuel moisture content

Author
item Hunt Jr, Earle
item CHENG, T - University Of California
item RIANO, D - University Of California
item USTIN, S - University Of California
item WANG, L - George Mason University
item HAO, X - George Mason University
item QU - George Mason University

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 4/24/2013
Publication Date: 5/29/2013
Citation: Hunt Jr, E.R., Cheng, T., Riano, D., Ustin, S.L., Wang, L., Hao, X., Qu, .J. 2013. Determining leaf dry matter content using the normalized dry matter index and its possible application for estimating fuel moisture content [abstract]. HyspIRI 2013 Symposium, May 29-30, 2013, NASA GSFC, Greenbelt, MD.

Interpretive Summary:

Technical Abstract: The Normalized Dry Matter Index (NDMI) was developed for the remote sensing of dry matter content using high-spectral resolution data. This narrow-band index is based on absorption at a C-H bond stretch overtone (1722 nm wavelength) and is correlated with 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. NDMI was tested using AVIRIS data acquired in 2012 over almond and pistachio orchards near Lost Hills, CA. Correlations were high for pistachio but were not significant for almond. Fuel moisture content (FMC) is the ratio of canopy water content to canopy dry matter content; we hypothesized that FMC could be predicted using the ratio of a spectral water index to NDMI. For leaf-scale simulations using the PROSPECT model, all water-index/NDMI ratios were significantly related to FMC with a second-order polynomial regression. For canopy-scale simulations using the SAIL model, two water-index/NDMI ratios, with numerators of the Normalized Difference Infrared Index (NDII) and the Normalized Difference Water Index (NDWI), predicted FMC with R2 values of 0.900 and 0.864, respectively. The planned HyspIRI mission will have high spectral resolution for determining NDMI; however, the planned 19-day repeat frequency will not be sufficient for monitoring FMC.