砂姜黑土土壤有机碳高光谱特征与定量估算模型的研究

有机碳作为衡量土壤肥力的重要指标,其定量化快速监测成为精确农业研究的热点。以安徽淮北平原区宿州市采集的砂姜黑土为研究对象,进行室内理化分析、预处理与室外光谱测量等一系列工作,在土壤原始光谱反射率的基础上,采用去包络线和波段深度提取突出吸收特征,剖析土壤光谱响应特征。基于原始光谱和8种变换形式,分析不同变换光谱形式与有机碳含量的相关性,结合有机碳光谱响应特征分析和光谱特征参量挑选,确定诊断土壤有机碳含量的最佳敏感波段,利用逐步回归方法建立了土壤有机碳高光谱的预测模型。结果表明,550~750nm波段范围是典型砂姜黑土有机碳的主要光谱响应区域。去包络线和波段深度处理突出了土壤有机碳光谱吸收特征,随着有机碳含量的降低,吸收值呈现下降趋势。在不同光谱转换形式中,归一化比值指数(R/R_(M(450-750)))的转换形式与土壤有机碳相关性最强,最敏感波段分别出现在451 nm和644 nm处,相关系数分别达0.80和–0.90。相关性最好的波段范围主要集中在600~700 nm波段附近。基于相关分析与逐步回归分析方法,确定了606、637和644 nm波段处的归一化比值指数为诊断土壤有机碳含量的最佳敏感波段,基于最佳敏感波段的归一化比值指数(R_(606)/R_(M(450-750)),R_(637)/R_(M(450-750))和R_(644)/R_(M(450-750)))建立的高光谱预测土壤有机碳模型具有良好的预测效果,模型的决定系数(R~2)为0.81,均方根误差(RMSE)为0.14,展现了较好的稳定性和预测精度。

Hyperspectral characteristics and quantitative estimation model of soil organic carbon in the Shajiang black soil

As an important indicator of soil fertility,quantitatively and rapidly monitoring soil organic carbon has become a hot spot in precision agriculture research.In this paper,Shajiang black soil samples were collected from Huaihe plain area of Anhui Province to conduct a series of experiments,including physical and chemical analysis,pretreatment and outdoor spectral measurement.Based on the original spectral reflectance of the soil,the characteristic of soil spectral response was analyzed by extracting the prominent absorption characteristics using Continuum removal (CR) and Band-depth (BD).The correlation between different spectral forms and organic carbon content (SOC) was analyzed based on the original spectra and eight transformations.Meanwhile,combined with spectral response characteristics of SOC and the selection of spectral characteristic parameters,best sensitive bands of soil organic carbon were determined for establishment of the hyperspectral prediction model of SOC by the stepwise regression method.The results showed that the main response wave bands between SOC and spectral reflectance were distributed in the range of 550-750 nm for the Shajiang black soil.CR and BD obviously highlighted the spectral absorption characteristics,and the absorption value showed a downward trend with a decrease of SOC content.In different spectral transformations,the normalized ratio index (R/RM(450-750)) exhibited the strongest correlation with SOC,and the most sensitive bands appeared at 451 nm and 644 nm,with the correlation coefficients of 0.80 and -0.90,respectively.The best correlation bands were mainly in the 600-700 nm.Based on the correlation analysis and stepwise regression analysis,the normalized ratio index at 606 nm,637 nm and 644 nm bands was determined as the best sensitive band for diagnosing SOC content.Furthermore,the hyperspectral prediction of SOC model established by the normalized ratio index (R606/RM(450-750),R637/RM(450-750)and R644/RM(450-750)) showed a good predictive effect,with the coefficient of determination (R2) of 0.81 and the root mean square error (RMSE) of 0.14.Overall,the hyperspectral inversion model showed good stability and prediction accuracy,which can provide a reference for remote sensing monitoring of the soil fertilizer information in the Shajiang black soil.