Study on Space-based Hyperspectral Detection Parameters for Quantitative Retrieval of Organic Carbon in Multiple Types of Soil
The spectral channel,spectral resolution,signal to noise ratio and other core parameters of space-borne hyperspectral instruments directly affect the accuracy of quantitative retrieval and prediction of soil organic carbon(SOC).In this study,the effects of satellite load spectral resolution,signal-to-noise ratio and spectral characteristic bands on the inversion of organic carbon in different soil types were studied,Based on atmospheric transmission model,spectral resolution analysis model,signal-to-noise ratio analysis model,a hyperspectral satellite'ground-atmosphere-instrument-observation-inversion'full-link simulation analysis method for organic carbon monitoring of different soil types was proposed.And the coupling effect analysis of soil type,atmospheric effect,instrument characteristic parameters and retrieval methods was realized.The results showed that:1)The best spectral resolution was in the range of 10-20 nm for soil organic carbon retrieval in different soil types.2)Different soil types had different requirements for the observed signal-to-noise ratio,a higher signal-to-noise ratio requirement was needed for organic carbon monitoring of Phaeozem than the other two soil types.3)The optimal spectral resolution and signal-to-noise ratio required under different feature band extraction and analysis methods were consistent.The characteristic bands extracted from the spectral data of different soil types were different,among which Chernozem had the best retrieval effect,with 26 characteristic bands,R2=0.826 5,RMSE=3.438 9 g/kg.4)The retrieval model had no coupling relationship with the instrument characteristic parameters,and the best spectral resolution and signal-to-noise ratio requirements of different retrieval algorithms for the same soil type were consistent.5)The best retrieval parameters for SOC contents of Chernozem,Kastanozem and Phaeozem were:spectral resolution15 nm,17 nm and 15 nm,signal-to-noise ratio greater than 506.66,331.42 and 432.51,and the number of feature bands extracted 26,22 and 19,respectively.
Space based hyperspectral detectionSoil organic carbon monitoringAtmospheric transmission modelSpectral resolutionSignal-to-noise ratioFeature band extractionVariable based optimization method
万方数据
维普
