Modeling Of Chlorophyll Content Of Wheat Using Field Imaging Spectrometer

By using the field Offner imaging spectrometer which developed by the National High Technology Research and Development Program (863)"Development and application of information field crops imaging spectrometer"(2007AA10Z202)and"Agriculture based on domestic rotary wing UAV using low-altitude hyperspectral remote sensing technology"(2010AA10Z201) to collect the spectral and spatial information of winter wheat leaves. First describes the process of imaging spectroscopy, and then studies quantitative analysis of the chlorophyll content in wheat leaves. The main works are as follows:(1) Describes the meaning of imaging spectrometer technology for nondestructive testing of wheat chlorophyll content, history of imaging spectroscopy, and its application in agriculture.(2) Introduces the preprocessing methods, the optimal wavelength selection methods, and the commonly used multivariate calibration algorithm principle, and their advantages and disadvantages.(3) The experiments for field imaging spectroscopy of winter wheat leaves based on the field Offner imaging spectrometer. Introduces the design of experiments and specifications of the imaging spectrometer, actual operation of imaging spectrometer system for acquiring the spectral image of wheat leaves, and data processing method.(4) Based on the imaging spectral data, the partial least squares regression models of the chlorophyll a, chlorophyll b, total chlorophyll, and SPAD are established. Discusses the effect of different spectral preprocessing methods on the accuracy of the emergent model. To improve modeling efficiency and reduce modeling variables, successive projection method is introduced as the preprocessing method in hyper-spectral modeling, and compared with partial least squares regression model of full-band spectral set.(5) Design and implementation of the chlorophyll detection module, which contains the basic data processing and analysis methods in basic quantitative analysis process. The module in Chlorophyll detection will enable hyper-spectral data analysis more convenient and accurate, and provides a quick and convenient tool for extracting information from hyper-spectral data. (6) Innovation of this work is to use the field Offner imaging spectrometer for ground observations of winter wheat in the field experiment, get hyperspectral images information of winter wheat and study the quantitative analysis of imaging spectrometer method. Design and implementation of chlorophyll content detection module based on the field Offner imaging spectrometer.