Study On Chlorophyll Content Retrieval From Hyperspectral Data In Citrus Tree

In recent years,Hyperspectral remote sensing has great potential for accurate retrieval of forest biochemical parameters.Spectrally continuous hyperspectral remote sensing data can provide nutrition information on forest biochemical contents,which are improtant for studying vegetation stress,nutrient cycling and productivity.Detection of citrus nutrition are signifiance for monitoring vegetation health,productivity, citrus nutrition and fertilization,not only the foundmental research in agricultural remote sensing technology,but also the simple,rapid,low-cost and non-invasive approach in place of the time-cosuming,costly chemical analysis method.In the paper,we provided canopy spectral transformed with wavelet analysis and applied extracted wavelet basis in a regression model for estimation of chlorophyll content.For studying the sensitivity of wavelet analysis,we used wavelet-trasformed reflectance and vegetation indices to estimate chlorophyll content in citrus.The experiment shows that the regression coefficient is 0.73,whereas MCTI is 0.6542.In the result,db1 wavelet has effective estimated chlorophyll content.Finally,retrival chorophyll content is to develop statistical relationship between ground-measured and canopy reflectance measure in the field or stimulation from 5-scale model. The experiment was caculated chorophyll RMSE between simulation and labrary measurement.