Hyperspectral Characteristic And Estimating Models About Phsiological Ecological Parameters Of Corn In Canopy Level

The precision of agriculture is the fundamental way to break high consumption and low efficiency, and achieve being harmony with environment.Hyperspectral remote sensing can get crop growth information in time. This study analyzes the hyperspectral characteristics of summer corn, clarifies the rules of spatial-temporal change of summer corn of leaf chlorophyll, leaf area index, leaf water content, and analyzes the quantified relationship between their growth process and spectral reflectance. Thus to build hyperspectral estimation based on vegetation indexes and red edge parameters and realize hyperspectral remote sensing estimation of chlorophyll, leaf area index, leaf water content, plant fresh biomass and dry biomass, and then solve the key problem of real-time,fast, non-destructive technology, accuracy and other crop information-related,lay the necessary foundation for spectral diagnostic techniques and development of IT products, and provide effective technical approach for the rapid acquisition of digital agricultural information, thus promoting the development of digital agriculture and agricultural information. The main results are as follows:(1) Summer corn canopy spectrum has the spectrum characteristics of the green vegetation, there are two absorption bands in blue band(center wavelength of 450 nm) and red band(center wavelength of 650 nm), the reflectance between the two absorption bands are low reflectivity, there is a reflection peak near 550 nm of green band, while the reflectance has risen sharply around 700 nm, the curve has a gentle tendency after entering near infrared region, forming a high reflection platform. There exist clear difference of summer corn spectrum characteristics at different stages. In visible band, the reflectance decreases gradually from seven leaf stage to silking stage, the reflectance increases gradually from silking stage to filling stage; In near infrared wavelength, the spectrum reflectance increases gradually from seven leaf stage to silking stage, while the spectrum reflectance reduces gradually from silking stage to filling stage.(2) Red edge characteristic of summer corn at different stages changes obviously, and the red edge position moves towards long wavelength, producing the "red shift", the red edge position move to the direction of short wavelength after silking stage, producing "blue shift". The red edge amplitude and red edge area also appear a trend of first increasing and then reducing with the passage of growth period, and reach maximum in spinning stage.(3) Not only the spectrum characteristics but also red edge feature has clear difference under different chlorophyll content of summer corn, the higher chlorophyll content is, the less spectrum reflectance become, the more spectrum reflectance of near infrared band become,and the larger red edge amplitude and red edge area increases. This study inverse chlorophyll content of summer corn model using vegetation index, high spectral characteristic parameters and red edge parameters, taking the coefficient of the decision, the root mean square error and relative error into consideration, the chlorophyll estimation model based on vegetation index effect is the best.(4) Not only the spectrum characteristics but also red edge feature has clear difference under different leaf area index of summer corn, the higher leaf area index is, the less spectrum reflectance become,the more spectrum reflectance of near infrared band become,and the larger red edge amplitude and red edge area increases. This study inverses leaf area index of summer corn model using vegetation index, high spectral characteristic parameters and red edge parameters,taking the coefficient of the decision, the root mean square error and relative error into consideration, the leaf area index estimation model based on vegetation index effect is the best.(5) Not only the spectrum characteristics but also red edge feature has clear difference under different leaf water content of summer corn, the higher leaf water content is, the less spectrum reflectance become, and the larger red edge amplitude and red edge area increases. This study inverses leaf water content of summer corn model using single band and spectrum vegetation index, taking the coefficient of the decision, the root mean square error and relative error into consideration, taking the single band to inverse leaf water content is more suitable for jointing stage and filling stage of summer corn, and spectrum vegetation index is more suitable for inversing leaf water content of the seven leaf stage, silking stage and ripening stage.