Submitted to: International Journal of Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/23/2007
Publication Date: 9/20/2007
Citation: Eitel, J.H., Long, D.S., Gessler, P.E., Smith, A.S. 2007. Using in-situ measurements to evaluate new rapideye satellite series for prediction of wheat nitrogen status. International Journal of Remote Sensing. Vol. 28, No. 18:4183-4190.
Interpretive Summary: The region of rapid change in reflectance of chlorophyll: termed red-edge, lies between the red and near infrared regions of the electromagnetic spectrum. Spectral channels in the red-edge region are generally more important than red and near infrared channels in predicting crop nitrogen status. The objective of this study was to determine whether red-edge data from the new RapidEye™ satellite sensor would be useful in predicting the nitrogen status of wheat during the growing season. Measurements of crop canopy reflectance were obtained from the ground with a spectroradiometer and converted to the band equivalent reflectance of RapidEye™. At the same time, leaf chlorophyll content was measured in the field with a hand held chlorophyll meter, and leaf nitrogen content was determined for dried and ground leaf samples with laboratory dry combustion analysis. Resulting vegetation indices, computed from the red-edge band, were found to be highly correlated with leaf chlorophyll and leaf nitrogen contents. This finding suggested that red-edge data are important to predicting wheat nitrogen status at mid-season and making decisions about fertilizer nitrogen management.
Technical Abstract: Spectral vegetation indices computed from hyperspectral data containing the red edge region (690-730 nm) have been used to predict plant nitrogen (N) status, but few commercial satellite systems are capable of providing this information. The earth imaging firm RapidEye™, however, plans to provide multispectral data including a red-edge band in 2007. Field experiments with spring wheat (Triticum aestivum L.) were conducted to assess whether simulated RapidEye™ data could match the capacity of hyperspectral data to predict mid-season N status of spring wheat. In-situ spectroradiometer data were converted to the band equivalent reflectance of RapidEye™. Common vegetation indices were computed from resulting hyperspectral and multispectral bands. Predictions of leaf chlorophyll and leaf N levels from linear regressions between ground data and the Modified Chlorophyll Absorption Ratio Index/Modified Triangular Vegetation Index (MCARI/MTVI) gave the highest r^2 values for chlorophyll ranging from 0.45 to 0.69 (P<0.01) for hyperspectral, and from 0.35 and 0.77 (P<0.01) for multispectral. For leaf N, r^2 values ranged from 0.41 to 0.68 (P < 0.01) for hyperspectral, and 0.37 to 0.56 (P<0.01) for multispectral. Our data suggest that the MCARI/MTVI index computed from RapidEye™ data is a potentially useful predictor of mid-season wheat N status.