Hyper-spectral inversion of grain size and total organic carbon in loess profile of Mangshan， Zhengzhou
loess； hyper-spectral； grain size； total organic carbon； partial least squares method
(1.Institute of geography， Henan Academy of Sciences， Zhengzhou 450052， China；2.School of Surveying and Land Information Engineering， Henan Polytechnic University， Jiaozuo 454000， Henan， China)
Abstract：The occurrence and development of loess has recorded abundant historical information， and its mean grain size and total organic carbon(TOC) can accurately reflect the environmental evolution. In order to explore the application of hyperspectral remote sensing technology in obtaining loess environmental information， Zaoshugou loess profile in Zhengzhou was taken as the research object. Combining hyperspectral technology， spectral data were mainly correlated with macro element of loess profile by smoothed original spectra， first-order differential (FD)， second-order differential (SD)， de-envelope (CR) and reciprocal logarithm (Log(1/R). A PLSR (Partial Least Square Regression) model was established to analyze the larger band of correlation coefficient R as characteristic band. The results were as follows： The changes of grain size and total organic carbon in Mangshan Loess profile indicated that the study area experienced a climate cycle of cold dry-warm wet-cold dry since about 5400 a.BP in the middle Holocene；The reflectance spectra of loess in different stratigraphic units showed their own characteristics and differences. The law of spectral reflectance was L0-2〉L0-1〉Lt〉S0-1〉TS；Among the inversion models， the PLSR model with the spectrum transformed by FD as the independent variable was the best model for retrieving the average grain size of loess profile， and the PLSR model with the spectrum transformed by SD as the independent variable is the best model to retrieve the TOC of loess profile.
2022, Vol. 56 
