Hyperspectral estimation of water content in larch needles from Dendrolimus superans
[Objective]The early stress of insect infestation will cause small changes in the internal biochemical components such as the moisture content of larch needles,and the spectrum has a significant response.With the development of remote sensing technology,hyperspectral remote sensing can capture these small changes,and has become an important tool for monitoring and identifying early stress of insect pests.Accurate prediction of coniferous moisture content can provide an experimental basis for the early stress and early warning of Dendrolimus superans insect pests.[Method]Taking the forest insect pest outbreak area of the Daxing'anling as the study area,the hyperspectral data and coniferous moisture content data in July 2021 were obtained,and the spectral dimensionality reduction and extraction of sensitive features were obtained through three spectral features:smooth spectral reflectance(SSR),differential spectral reflectance(DSR)and spectral continuous wavelet coefficient(SCWC),combined with Findpeaks function(FP)and successive projection algorithm(SPA),and partial least squares regression(PLSR),random forest(RF)and support vector machine regression(SVMR)to establish a water content estimation model.[Result]1)Most of the sensitive bands of SCWC were concentrated in the three scales of 22,23and 24,and they were more sensitive than SR and SSR.2)FP-SPA quickly and accurately selected sensitive spectral features,reduced data redundancy,and reduced model complexity.3)The PLSR-SCWC-coif4 model had the highest accuracy(R2=0.890 4,RMSE=0.037 5),which was 0.096 3 and 0.115 3 higher than the R2 of DSR and SSR,and 0.007 5 and 0.017 8 lower RMSE,respectively,followed by the SVMR-SCWC-bior4.4 model(R2=0.876 4,RMSE=0.033 0)had the most significant improvement in accuracy.The accuracy was improved by 0.155 4 and 0.130 8 and decreased by 0.026 3 and 0.027 3 compared with DSR and SSR,respectively.[Conclusion]SCWC is more sensitive to coniferous moisture content than DSR and SSR,and FP-SPA can quickly and accurately extract sensitive spectral features,so SCWC has reliable accuracy in estimating coniferous moisture content,so as to accurately predict the moisture content of D.superans.
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