Estimation of the main characteristics of agricultural crops from reflectance spectrum of vegetation in the optical range

1Kochubei, SM
1Institute of Plant Physiology and Genetics of the National Academy of Sciences of Ukraine, Kyiv, Ukraine
Kosm. nauka tehnol. 2003, 9 ;(5-6):185-190
Publication Language: Russian
Reflectance spectra of vegetation are shown to contain sufficient information for developing a set of parameters to control effectively a status of agricultural crops. Most of the parameters can be based on chlorophyll estimation or on the other characteristics depending on influence of inner structure of leaf tissue on the leaf reflection in the chlorophyll absorption range. A novel chlorophyll index based on a quantitative characteristic of the shape of reflectance spectral curve is proposed for chlorophyll content estimation in winter wheat leaves. The index is a ratio of intensities in two main maxima in the first derivative plot from reflectance spectrum curve in a range of 680—750 nm. The ratio correlates with chlorophyll content. Application of physical, graphic and mathematical models allowed us to test the stability of chlorophyll estimations by the proposed novel chlorophyll index in relation to contribution of soil reflectance. The ratio of two maxima in the first derivative plot is shown to be changed no more than 5 and 11 % when 50 and 25 % projective covering took place and dark soil or sand are used as a background. Coefficient of reflection at 550 nm correlates with chlorophyll and total nitrogen content, but it shows sensitivity to leaf moisture and to the contribution of soil reflection. Therefore, the combinatorial estimations of chlorophyll deriwed with quantitative parameter of the shape of reflectance spectral curve and coefficient of reflection at 550 nm give the possibility to estimate the value of projective covering for dense sowing or to estimate moisture for undense sowing.
Keywords: agriculture, optical range, reflectance spectrum of vegetation
1. Zhumar' A. Yu. Studies of the influence of vegetation parameters on the position of the maximum inclination of the red edge. Issled. Zemli iz kosmosa, 4, 15—20 (1990) [in Russian].
2. Kochubey S. M., Kobets N. I., Shadchina T. M. The quantitative analysis of shape of spectral reflectance curves of plant leaves as a way for testing their status. Fiziol. i biohim. kul't. rastenij, 20 (6), 535—539 (1988) [in Russian].
3. Kochubey S. M., Kobets N. I., Shadchina T. M. Spectral Properties of Plants as a Basis for the Methods of Remote Diagnostic, 136 p. (Naukova dumka, Kiev, 1990) [in Russian].
4. Shadchina T. M. Scientific bases of remote monitoring of grain crops state, 219 p. (Phytosociocentre, Kiev, 2001) [in Ukrainian].
5. Arnon D. I. Copper enzymes in isolated chloroplasts. Poly-phenoloxidase in Beta vulgaris. Plant Physiol., 24, 1 — 15 (1949).
6. Demetriodes-Shan T. H., Steven M. D., Clark J. A. High resolution derivative spectra in remote sensing. Rem. Sens. Envir., 33, 55—64 (1993).
7. Kochubey S. M., Biduk P. I. Novel Approach to Remote Sensing of Vegetation. In: AeroSence. Technologies and Systems for Defence Security: Proc. of SPIE. Int. Conf., 21-25 April 2003, Orlando USA, 5093, 373—378 (2003).
8. Miller J. R., Hare E. W., Wu J. Quantitative characterization of the vegetation red edge reflectance. 1. An inverted Gaussian reflectance model. Int. J. Rem. Sens., 11, 1755—1773 (1990).
9. Savitzky A., Golay M. G. E. Smoothing and differentiation of data by simplified least squares procedures. Analyt. Chem., 36, 1627—1639 (1964).

10. Zarko-Tejada P. J., Miller J. R., Mohammed G. H., et al. Vegetation stress detection through chlorophyll a+b estimation and fluorescence effects on hiperspectral imagery. J. Environ. Qual., 31, 1433—1441 (2002).