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Remote sensing systems using either passive reflectance (R) or actively induced fluorescence (F) have long been explored as a means to monitor species composition and vegetative productivity. Passive F techniques using the Fraunhofer line depth (FLD) principle to isolate solar induced F (SIF) from the high resolution R continuum have also been suggested for the large-scale remote assessment of vegetation. The FLD principle was applied to both canopy R spectra and AISA multi-spectral imagery to discriminate the relatively weak in situ vegetation F in-fill of the telluric O2 bands located at 688 nm and 760 nm. The magnitudes of SIF retrieved from R ranged from 7 to 36 mW/m2/nm/sr and the ratio of the two spectral bands successfully discriminated the four N treatment levels. In addition, a number of R indices including but not limited to the physiological reflectance index (PRI), R550/R515 and R750/R800 were calculated from the AISA aircraft imagery and the high-resolution canopy R spectra. These indexes were then evaluated against georeferenced ground measurements of leaf area index (LAI), pigment contents, grain yields, and light use efficiency (LUE). A number of significant relationships were evident in both R and SIF indices to the biophysical changes in corn induced by N application rates. From this investigation we conclude that valuable SIF information can be extracted from high-resolution canopy R data and indices calculated from both data types can supply useful information for modeling N use for carbon sequestration by vegetation.