THE USE OF HIGH SPECTRAL RESOLUTION BANDS FOR ESTIMATING 
ABSORBED PHOTOSYNTHETICALLY ACTIVE RADIATION (A^J 
x Moon S. Kim, 2 C. S. T. Daughtry, 3 E. W. Chappelle, 2 J. E. McMurtrey, and 1 C. L. Walthall 
1 Laboratory for Global Remote Sensing Studies 
Department of Geography, University of Maryland 
College Park, MD 20770 
2 Remote Sensing Research Laboratory 
ARS, United States Department of Agriculture 
Beltsville, MD 20775 
3 Laboratory for Terrestrial Physics 
NASA/Goddard Space Flight Center 
Greenbelt, MD 20771 
ABSTRACT 
Most remote sensing estimations of vegetation variables such as leaf area index (LAI), absorbed photosynthetically 
active radiation (A ), and phytomass are made using broad band sensors with a bandwidth of approximately 100 
nm. However, higii resolution spectrometers are available and have not been fully exploited for the purpose of 
improving estimates of vegetation variables. The study was directed to investigate the use of high spectral 
resolution spectroscopy for remote sensing estimates of A in vegetation canopies in the presence of 
nonphotosynthetic background materials such as soil and leaf utter. A high spectral resolution method defined 
as the chlorophyll absorption ratio index (CARI) was developed for minimizing the effects of nonphotosynthetic 
materials in the remote estimates of A . CARI utilizes three bands at 550, 670, and 700 nm with bandwidth of 
10 nm. Simulated canopy reflectance of a range of leaf area index (LAI) were generated with the SAIL model 
using measurements of 42 different soil types as canopy background. CARI obtained from the simulated canopy 
reflectance was compared with these broad band vegetation indices (normalized difference vegetation index 
(NDVI), soil adjusted vegetation index (SAVI), and simple ratio (SR)). CARI reduced the effect of 
nonphotosynthetic background materials in the assessment of vegetation canopy A par more effectively than broad 
band vegetation indices. 
KEY WORDS: A r CARI, SAIL MODEL, NDVI, SAVI, SR, VEGETATION INDICES 
1. INTRODUCTION 
Current remote sensing estimates of vegetation variables such as green biomass, leaf area index (LAI), and A mr 
are made with broad band sensors with bandwidths of approximately 100 nm. These broad band vegetation indices 
have been shown to suffer from a sensitivity and the reflectance of nonphotosynthetic background materials 
(Choudhury, 1987, Huete, 1989, Goward et al., 1992). 
Although recent advances in technology have allowed the use of high resolution spectroscopy for remote 
sensing, this technology has not been fully exploited for characterization of the atmosphere-plant-soil complex. 
Only a few researchers, to this time, have worked with narrow spectral band reflectance as a means of eliminating 
the effects of nonphotosynthetic background materials in vegetation canopy reflectance. The ratio analysis of 
reflectance spectra (RARS) by Chappelle et al. (1992) showed that ratios of reflectance in narrow bands correlated 
well with leaf pigment concentration, and they suggested that photosynthetic pigments may be remotely estimated 
with high accuracy from narrow band reflectance. The use of second derivative spectra has shown promise for 
reducing the effects of nonphotosynthetic background materials in vegetation canopies (Hall et al., 1990; 
Demetriades-Shah et al., 1990). 
Canopy reflectance is am integrated function of leaf optical properties, plant structure, background 
reflectance, and solar illumination and view angles. Canopy reflectance models have provided tools to; 1) assess 
the effect of different canopy characteristic on reflectance; 2) evaluate plant canopy reflectance under varying 
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