Inversion Vegetation Information Base On Hyper-Spectral Remote Sensing Data

With the global warming, the frequent various geological disasters, people are increasingly concerned about ecological environmental problems. Vegetation can convert solar energy into chemical energy, carbon dioxide in the atmosphere into organic matter, providing mankind’s most basic material and energy sources. All kinds of ecological processes of vegetation, such as evaporation, transpiration, primary production, waste decomposition, and biochemical parameters are closely related of vegetation body materials such as chlorophyll, water, protein, lignin, cellulose etc and physical parameters such as leaf area index (LAI), light and effective radiated (fPAR). How to calculate the ability of the forest carbon sequestration, estimate the forest productivity and biomass, and evaluate the ecological benefits of forest value became a hot issue for national scholars. Remote sensing technology for its large area, fast, dynamic advantage can be obtained forest canopy information in different time and spatial scales without destroying the forest, hyperspectral remote sensing as another milestone in the development of remote sense, can provide more abundant spectrum information, and have greater advantages in recognition of plant, inversion plants in physical and chemical information. In this paper, the main garden trees in central China as the research object, studied the inversion of vegetation chlorophyll, LAI and the identification of species using hyperspectral. The main research work include:(1) Analyzed the non-imaging spectrometer ASD, imaging spectrometer HyperScan data acquisition norms and the basic method of data processing, and that has laid a good foundation for the smoothly subsequent research.(2) Based on the summarizing current atmospheric correction algorithm, conduct atmospheric correction to the hyperspectral image of the Hyperion sensors of EO-1 and HSI sensor of HJ satellite, mainly completed work include:for the Hyperion hyperspectral data having short wave infrared (2.1μm), blue (0.47μm), red band (0.66μm), considering the influence of water vapor and aerosols, using dark target method with iterative way, based on 6S radiation transmission model, retrieve the water vapor content and aerosols optical thickness, conduct atmospheric correction, and achieved good effect; studied HJ satellite hyperspectral data scaling method, obtained the HSI sensor calibration coefficient, and successfully used to Wuhan and Three Gorges Reservoir area experiment data; for HJ satellite HSI hyperspectral data which have only visible and near-infrared wavelengths, using the known water vapor and aerosol parameters, based on 6S radiation transmission model lookup table method, conduct atmospheric correction, and good results were obtained.(3)Based on measuring leaf and canopy spectrum, this paper compared the plant’s spectrum under different scales; First the canopy radiative transfer PROSAIL plants of HuaZhong area main garden plants adaptability was verified;then the influence of structural parameters,chlorophyll content, dry weight, leaf water content, LAI, sun days to plant spectrum parameters in the leaf scale to canopy scale conversion was analysed;finally,through the coupling of the PROSAIL model and 6S on atmospheric radiative transfer model,this paper also analysed the influence of such parameters like chlorophyll content, LAI, aerosols optical thickness to on-board data in the transformation from the earth’s reflectance to satellite’s.(4) From plant leaves scale、single plant canopy scale, the relationship between spectral data and chlorophyll content、LAI is analysed, the inversion of chlorophyll content、LAI based on spectral index statistical model, the inversion effect of NDVI SAVI2、CI is compared, the effect of spectral band width to the inversion of chlorophyll content and LAI is analysed; simultaneously, the inversion methods of phytochrome content based on physical model is studied, the inversion effect of Simulated Annealing and genetic algorithm is compared,at the last inversed the vegetable canopy parameters of Three Gorges Reservoir Area using the HJ satellite Hyper-Spectral Remote Sensing Data.(5)With regard to single plant canopy, analysing chlorophyll、dry weight and the like parameters in different plant species, using ground spectral imaging equipment, Hyper Scan, acquiring spectral datum of single plant canopy applied to species’ classification and identification.Using seven feature points’reflectivity, M(λM,RM)、B(λB,RB),G(λG,RG)、Y(λY,RY)、R(λR,RR), V(λV,RV),I(λI,RI), along with five feature parameters, the gradient of red edge(SV)、clear height of green peak(HG)、clear depth of red valley(HR)、FWHM of green peak(λWG)、FWHM of red absorption peak(λWR) constructing the plant identification feature vectors. Then based on Mahalanobis distance classification maximum likelihood method and Fisher DF clustering method to build a plant species classification and recognition model, and then apply it to the analysis of Chinese HJ Satellite according to which making the application potential report.