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Application of Spectral Remote Sensing for Agronomic Decisions

^a USDA-ARS National Soil Tilth Lab., 2110 University Blvd., Ames, IA 50011
^b CALMIT, School of Natural Resources, Univ. of Nebraska, Lincoln, NE 68583
^c USDA-ARS Soil and Water Conservation Unit, 120 Keim Hall, Univ. of Nebraska, Lincoln, NE 68583
^d USDA-ARS, National Program Staff, 5601 Sunnyside Ave., Beltsville, MD 20705

View larger version (26K): [in this window] [in a new window]   Fig. 1. Absorption spectra of maize leaves.

View larger version (32K): [in this window] [in a new window]   Fig. 2. Reflectance spectra of maize leaves and standard deviation of reflectance.

View larger version (21K): [in this window] [in a new window]   Fig. 3. Reflectance in the blue, green, red, red edge, and NIR ranges plotted vs. total Chl content in maize leaves.

View larger version (19K): [in this window] [in a new window]   Fig. 4. Root mean square error of Chl estimation using chlorophyll index in the form CI = (RNIR/R – 1) in maize leaves plotted vs. wavelength when leaf Chl ranged from 10 to 800 mg/m2.

View larger version (19K): [in this window] [in a new window]   Fig. 5. Relationships between estimated and actually measured Chl content in maize leaves using chlorophyll Indices CIred edge = (RNIR/Rred edge) – 1 and CIgreen = (RNIR/Rgreen) – 1 where green band is between 540 and 560 nm and red edge band is between 705 and 725 nm (Gitelson et al., 2003a, 2005).

View larger version (51K): [in this window] [in a new window]   Fig. 6. Seasonal changes in the reflectance from a corn canopy using an eight-band sensor.