Corn canopy LAI and chlorophyll content joint inversion method and corn canopy LAI and chlorophyll content joint inversion equipment

Abstract

The invention provides a corn canopy LAI and chlorophyll content joint inversion method and corn canopy LAI and chlorophyll content joint inversion equipment. The corn canopy LAI and chlorophyll content joint inversion method comprises: obtaining actual corn canopy spectral reflectivities of multiple spectrums at each growth period; establishing a lookup table based on a PROSAIL model, wherein theinput parameters in the lookup table comprise the leaf area indexes (LAI) and the chlorophyll contents of corn at each growth period, and the output parameters of the lookup table are corresponding simulated corn canopy spectral reflectivities; establishing a cost function based on a weighted square difference sum form, wherein the cost function is used for calculating the error between the simulated corn canopy spectral reflectivity and the real corn canopy spectral reflectivity; and carrying out inversion on the corn canopy LAI and the chlorophyll content based on the corresponding simulated corn canopy spectral reflectivity in the case of the minimum value of the cost function. According to the present invention, the LAI and the chlorophyll are simultaneously inverted with the one setof the parameters by establishing the joint distribution of the corn canopy LAI and chlorophyll content parameters so as to improve the parameter inversion efficiency.

Description

technical field [0001] The invention relates to the technical field of agricultural remote sensing, and more particularly, relates to a method and equipment for joint inversion of corn canopy LAI and chlorophyll content. Background technique [0002] Surface vegetation biophysical and biochemical parameters, such as Leaf Area Index (LAI), chlorophyll content, leaf moisture, etc., are key structural variables to explain the biophysical processes of vegetation canopies and quantitatively evaluate the energy exchange between the surface and the atmosphere. The remote sensing information, especially the visible light and near-infrared bands, provides the inversion of spatial and temporal continuous distribution information of these key surface vegetation variables. This is because the vegetation canopy reflectance information can reflect the characteristics of vegetation structure, leaf biochemical composition, etc. For example, LAI has a great influence on the near-infrared (NI...

AI Technical Summary

Problems solved by technology

[0005] The present invention provides a joint inversion method and equipment for corn canopy LAI and chlorophyll content that overcomes the above problems or at least partially solves the above problems, and solves the problem of using different input parameters in the prior ar...

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