Remote Sensing Monitoring Of Winter Wheat Growth Based On Comprehensive Growth Parameters

Remote sensing technology with its advantages of fast,simple,macroscopic,non-destructive and objective has increasingly been applied to every link of agricultural production.Agricultural remote sensing applications mainly rely on space remote sensing technology to carry out monitoring of growth,yield and disasters.Among them,crop growth monitoring mainly included crop parameter inversion,crop growth status assessment etc.To this end,the main work and conclusions of the use of multi-source remote sensing data were as follows:(1)Aiming at the inversion of growth parameters.Using the ground hyperspectral data and the measured data of growth parameters,based on the selection of the typical vegetation index and model in the literature,the optimal estimation model of the growth parameters was established.The results show that the LAI estimation model based on r-PLSR-AIC constructed by 4 vegetation indices(RVI、PRI、VOG1、NDVI705)was the best,which can be used for accurate retrieval of LAI in winter wheat.The prediction model based on spectral index RSI(R604,R496)had better prediction ability.The SPAD estimation model of winter wheat with the 7 vegetation indices based on r-MSR-Adj.R2 was the best.The AGB estimation model of winter wheat with the 5 vegetation indices based on r-MSR-Adj.R2 was the best.(2)In view of the single growth parameter,it was difficult to fully reflect the true growth of crops.This paper attempted to characterize the growth of winter wheat leaf area index(LAI),the aboveground biomass(AGB),leaf nitrogen content(LNC),chlorophyll content(SPAD)four single growth parameters using analysis equal weight and principal components respectively(PCA)were integrated to construct a comprehensive growth monitoring index(CGMI).The results showed that CGMI based on PCA method can reflect the real growth of crops more comprehensively.(3)Using the UAV hyperspectral image,the CGMI based on the PCA method was further verified,and then a dual threshold partitioning strategy was applied to evaluate the growth status of crops.According to the field survey and the winter wheat experimental design scheme,the monitoring results of winter wheat growth were in good agreement with the actual growth conditions.It showed that the monitoring precision of the winter wheat comprehensive monitoring parameters(CGMI)based on the PCA statistical analysis method was high,which can provide the appropriate management measures and the guidance for the implementation of the precision operation.