Accurate remotely sensed estimates of the chemical concentration of vegetation canopies provide a valuable aid to the understanding of ecosystem function and real-time agricultural decision-making. This is because many biochemical processes

such as photosynthesis

respiration and evapotranspiration are highly related to the biochemical concentrations such as chlorophyll

nitrogen

water and so on. Hyperspectral remote sensing images are providing an attractive way for biochemical estimates in a large scale promptly. In this study

investigation was designed to determine whether hyperspectral images of the airborne operative modular imaging spectrometer（OMIS）could be used to estimate foliar nitrogen concentration of wheat at a spatial resolution of 3m. OMIS image had 128 bands covering the V-TIR wavelength range

among which bands between 400nm and 2500nm accounting for 112 bands which were used in this paper. The images were acquired by the airborne OMIS in Xiaotangshan Area

Beijing

China

on April 26th

2001 under a fairly clear weather. While the wheat leaves being sampled and measured foliar biochemistry

calibration was carried out synchronously. Red edge analysis and absorption feature analysis as well as stepwise regression analysis were utilized to determine the characteristic bands and parameters for the canopy-level nitrogen retrieval after accurate geometric correction and accurate image spectra rebuilt. The five concerned absorption features were centered around 675.8nm

1175.8nm

1409.1nm

2078.2nm

2295.1nm

which were selected according to the original image spectra shapes as well as some rational laboratory analysis results of dry materials. At last

the best estimation equation was applied to all the wheat pixels of the image so that a nitrogen concentration distribution map of wheat was obtained. As expected

the red edge slope（Srg）and area（Arg）could estimate the total foliar nitrogen（TN）fairly well（R 2=0.656

0.643 respectively）. The absorption depths and absorption areas of the three absorption features centered around 670nm

1175nm and 1409nm were effective estimators of wheat foliar nitrogen concentration（R 2=0.7447

0.7569 and 0.7073 respectively

n=43）. The new developed spectral indices

NDVI（NRCA 1175.8

NRCA 733.9）and NDVI（dr745

dr699.2）were the best estimators of TN（R 2=0.8145 and 0.769 respectively）. The values of the nitrogen concentration distribution map ranged from 1.8% to 6.5%

which was quite consistent with those of field measurements（2.8%-6.3%）. The distribution agreed highly with the growth status distribution. Therefore to some extent

the estimation equation was validated. So it’s possible

feasible and time-saving to estimate foliar nitrogen concentration at a large scale by using hyperspectral remote sensed images.