doi:10.16186/j.cnki.1673-9787.2023030004

Received:2023/03/02

Revised:2023/05/05

Published:2024/05/15

Hyperspectral estimation of coal-derived carbon mass fraction in mine soil based on the CWT-CARS-CNN integrated method

NIE Xiaojun, HONG Wenwen, GILL Ammara, YU Haiyang, CHEN Xiaodong

School of Surveying and Land Information Engineering，Henan Polytechnic University，Jiaozuo 454000，Henan，China

Abstract:  Objectives  There is a shortage of reliable methods to quantitatively identify the coal-derived in soil.    Methods  In this study，soil samples from cultivated lands in Jiaozuo mining area were collected，249 coal-derived source carbon soil samples with different mass fraction were prepared，and spectral data of the samples were obtained by ASD FieldSpec4，the continuous wavelet transform（CWT）-competitive adaptive reweighted sampling（CARS）-convolutional neural network（CNN） method was used to estimate c oal-derived  mass fraction in soil，the estimation effect of coal-derived carbon mass fraction between the CWT-CARS-CNN and traditional spectral index modelswas compared，and the applicability of the CWT-CARS-CNN model was also tested.    Results  The results showed that in the range of 350~2 500 nm，the hyperspectral characteristics between coal and soil were completely different.The spectral reflectance of coal-contained soil samples decreased with increasing coal-derived carbon mass fraction.The CWT method improved the sensitivity of the spectrum to the coal-derived carbon mass fraction in soil，the number of feature waveband of coal-derived carbon mass fraction extracted by the CARS was obviously increased.In general，accuracies of coal-derived carbon mass fraction estimation models based on the CWT-CARS-CNN integrated method were significantly higher than those based on traditional spectral index method.Especially，the CWT-CARS-CNN model constructed with L8 decomposition scale exhibited the highest accuracy，showing R₂=0.999 3 and  RPD =40.308 1 for itsvalidation set.    Conclusions  The study suggests that hyperspectral estimation based on the CWT-CARS-CNN integrated method can accurately estimate the coal-derived carbon mass fraction in soil under different land use types in mining areas，providing reference for accurate assessment of carbon sequestration and fertility in mine soil under the “Double C” background.

Key words:coal-derived carbon;carbon sequestration;hyperspectral estimation;deep learning;mine soil