Novel approach to remote sensing of vegetation

The problem of remote estimation of chlorophyll content in vegetation is considered. A lot of reflectance spectra have been recorded for winter wheat leaves with various chlorophyll content. The plots of the 1-st derivative of reflectance spectral curves have been computed and analysed in respect interrelation with pigment content. The ratio of two maxima in the plots has been revealed as a correlating characteristic, which was used for chlorophyll estimation. To diminish the level of noise in 1-st derivative plots, producing by measuring system, the computing procedure have been applied by Savitzky and Golay formula using 2-d order polynomial estimation of 9-point convolution. Application of genetic algorithm to search of maximum positions in 1-st derivative plots has been tested with a positive result. Pair and multiple regression as well as neural net approach have been tested for estimation of chlorophyll content.