不同光谱变换形式对土壤有机质偏最小二乘估算模型精度的影响

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中图分类号 S153.621 文献标识码A 文章编号 1007-7731（2025）15-0089-05

DOI号 10.16377/j.cnki.issn1007-7731.2025.15.022

Influence of different spectral transformation forms on the accuracy of partial least squares estimation model of soil organic matter

ZENG Yuanwen FAN Wenwu

（Chongqing Geomatics and Remote Sensing Center， Chongqing 401147， China）

AbstractThisstudyused field-colectedsoil samplesas test subjectsto conduct experiments including soil organicmater （SOM） content determination，hyperspectral data acquisition，and preprocessing.Sixspectral transformationswereapplied to the preprocessd spectral data：absorption depth （Depth），firstderivativeof logreflectance （FD-lgR），second derivativeof log-reflectance （SD-lgR），secondderivativeof reflectance （SD-R），second derivative ofreciprocal reflectance （SD-1/R），andsecondderivativeof reciprocallog-reflectance （SD-1/lgR）.Partial least squares regression （PLSR） models for SOM estimation were establishedunder diffrent spectral transformation forms to analyze thecorrelation between spectral transformationsand SOM content，as wellas their impacton model accuracy.Theresults showed thatall6transformations exhibited bands significantlycorrelated with SOMcontent，with FD-lgRhaving the highest numberofsignificantlycorrelatedbands （71）.TheFD-lgRmodelachievedadetermination coefficient （ R2 ）of 0.995，a root mean square error of calibration （RMSEC） of 0.O63，a cross-validation R2 of 0.775，and a relative percent difference （RPD）of 2.681，allof which were among the highest values acrossall transformations.The scater plot of predicted versus measured values indicated that theFD-lgR model's estimates were close to the actual values，with an R2 of 0.872. Overall， the regression model based on FD-lgR demonstrated high accuracy and good stability.These findings provide a reference for subsequent hyperspectral data preprocessing and estimation model construction for soil organic matter.

Keywordssoil organic matter; hyperspectral; spectral transformation; partial least squares regression

土壤有机质（Soilorganicmatter，SOM）是土壤的重要组成部分，其含量是评价土壤肥力的重要指标；也是农作物生长的重要养分之一，对作物生长有显著影响。（剩余5833字）