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ARS Home » Research » Publications at this Location » Publication #137611
Title: REMOTE SENSING LEAF CHLOROPHYLL CONCENTRATION IN CORN FIELDS

Author
item Daughtry, Craig
item Hunt Jr, Earle
item McMurtrey Iii, James
item Gish, Timothy
item Walthall, Charles

Submitted to: International Conference on Precision Agriculture Abstracts & Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 8/15/2002
Publication Date: 3/1/2003
Citation: Daughtry, C.S., Hunt, E.R., McMurtrey, J.E., Gish, T.J., Walthall, C.L., Remote sensing leaf chlorophyll concentration in corn fields [abstract]. International Conference on Precision Agriculture [CD ROM].

Interpretive Summary:

Technical Abstract: Nitrogen (N) is frequently the major nutrient limiting crop growth. Variations in soil reflectance and leaf area index (LAI) often confound assessments of leaf chlorophyll concentrations by remote sensing techniques. Our objective was to develop a strategy for assessing leaf chlorophyll status of corn plants using radiative transfer models and aerial hyperspectral imagery. Reflectance and transmittance spectra of field grown corn leaves and reflectance spectra of wet and dry soils were acquired over the 400-2400 nm wavelength range. Corn canopy reflectance was simulated with a radiative transfer model. In the simulated canopy reflectance data, the subtle differences due to changes in leaf chlorophyll concentration were overwhelmed by the large changes associated with soil reflectance and LAI. Some spectral vegetation indices responded primarily to LAI, while other indices responded to both leaf chlorophyll concentrations and soil reflectance. Selected pairs of the spectral vegetation indices plotted together produced isolines of leaf chlorophyll concentrations over a wide range of soil reflectance and LAI values. Adjustments for local conditions (soil reflectance) improved estimates of leaf chlorophyll concentrations. A test of the strategy using aerial hyperspectral imagery and ground sampling showed consistent patterns of leaf chlorophyll concentrations even when LAI varied significantly. This approach holds promise as a management decision aid because leaf chlorophyll concentrations were determined with minimal confounding due to variations in soil reflectance and LAI.