A review on quantification of tree leaf pigment using wavelet analysis and remote sensing

Abstract

Accurate prediction of leaf pigment from spectral reflectance is important because it allows non destructive and rapid assessment of oil palm tree. There are many technique can be use to transform spectra reflectance for instance Derivatives Analysis, Artificial Neural Network, and Mathemathical formulation by adding, substracting or dividing the wavebands. Among the methods, wavelet analysis have been exploited for determine predictive capability of spectral reflectance model development for chlorophyll quantification. Thus with the improvement of spectral and spatial resolutions of image satellite, remote sensing technique are applicable in monitoring chlorophyll. The selected wavebands for monitoring chlorophyll consisted of the visible (400-750nm) as compared to the NIR (750-1350nm). This research can be useful to develop models for chlorophyll concentration estimation based on leaf spectra reflectance using wavelet analysis and covering large area for monitoring chlorophyll using remote sensing technique.