Crop biomass inversion method based on SEBAL-HJ model

Abstract

The invention discloses a crop biomass inversion method based on a SEBAL-HJ model. The crop biomass inversion method is characterized by comprising the following steps: S1, acquiring HJ-1 CCD, IRS images and elevation data DEM in a research plot, and carrying out geometric fine revision to the images; S2, inversing a land surface albedo, NDVI, SR, land surface emissivity and inversing land surface temperature; S3, calculating net radiation flux according to inversion results in the S2, and further calculating soil heat flux on the basis; S4, calculating sensible heat flux through cyclic reduction; S5, calculating the coefficient of evaporation ratio and obtaining evapotranspiration per day through space-time dimension expansion; S6, inversing fPAR on the basis of vegetative cover indexes NDVI and SR; S7, inversing NPP according to the inversion results of evapotranspiration per day in the step S5 and the inversion results of fPAR in the step S6; and S8, obtaining crop biomass through the accumulation of NPP after space-time reconstruction. According to the invention, the high-precision inversion of crop biomass is achieved, and the amount of calculation is relatively smaller.

Description

technical field [0001] The invention relates to the technical field of agricultural remote sensing, in particular to a crop biomass inversion method based on the SEBAL-HJ model. Background technique [0002] Crop biomass refers to the accumulation of net crop production. It is one of the important parameters to characterize the characteristics of crops, and it is also an important basis for crop growth monitoring, yield estimation, and farmland ecological environment evaluation. The traditional method of measuring crop biomass in the field is time-consuming, laborious, destructive and can only obtain data from limited sampling points, which is limited in practical application. Remote sensing is an effective technical means to quickly obtain large-scale ground object information, and inversion of crop biomass based on remote sensing images is a fast, economical and effective method. Currently, remote sensing images used for crop biomass retrieval include NOVV AVHRR, LandSat ...

AI Technical Summary

Problems solved by technology

This method establishes the relationship between biomass and vegetation index through a simple linear or nonlinear relationship, which has the advantages of less input variables and fast calculation. In addition, this method is poor in generalization, and it is difficult to promote and apply the model established in one area to other areas.

Model-based methods, such as the BIOME-BGC model, include the physiological and ecological mechanism of crop growth, have a certain theoretical basis and high accuracy, and are a reasonable method for inverting the physiological quantities of crops. The models are relatively complex and need to input more parameters when using them, so they are limited in practical applications

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