三江源区不同土壤类型有机质含量高光谱反演

Hyperspectral Retrieval of Soil Organic Matter for Different Soil Types in the Three-River Headwaters Region

近年来高光谱遥感技术被广泛运用于土壤有机质含量反演的研究中。基于三江源区玉树县和玛多县采集的146个土壤样品的室内ASD FieldSpec 4实测光谱数据及4种变换形式,利用偏最小二乘回归(PLSR)和人工神经网络(ANN)建立土壤有机质含量高光谱预测模型。结果表明:ANN模型反演土壤有机质含量的整体精度高于PLSR模型,总均方根误差均在17.51以下;但是,不同土壤类型的最佳反演模型及指标却有所差异:高山草甸土和沼泽土的最佳反演模型和指标均为ANN模型和BD指标,模型总均方根误差分别为10.29和3.29;高山草原土的最佳反演模型是PLSR模型,最佳指标是REF指标,模型总均方根误差为5.59;山地草甸土的最佳反演模型为PLSR模型,最佳指标为BD指标,模型总均方根误差为4.68。研究发现,利用ANN模型和PLSR模型都能较好地预测三江源区4种土壤类型的有机质含量,而波段深度则是该区域的最佳反演指标。

In recent years,hyperspectral remote sensing technology has been widely used in the inversion of soil organic matter contents.In this paper,in order to inverse soil organic matter contents,indoor spectral of 146 soil sampling data,which is collected from Yushu and Maduo County in Three-River Headwaters Regions,was measured by ASD FieldSpec4;Thereafter,soil organic hyperspectral forecast models for soil matter contents in four kinds of transformation forms were respectively established using Partial Least Squares Regression(PLSR)and Artificial Neural Network(ANN)method.The results showed that the overall accuracy of using ANN model to estimate soil organic matter content is higher than that of using PLSR model,and its total root mean square errors were all less than17.51,however,The different soil types have showed different optimal estimation models and the optimal indicators.The optimal retrieval models and indicators of Alpine meadow and marsh soil are both the ANN model and BD(Band Depth),and their total root mean square errors are 10.29 and 3.29respectively;PLSR model is the optimal estimation model of Alpine steppe soil,the optimal indicator is REF,with the model's total root mean square error of 5.59;PLSR model is the best inversion model for Mountain meadow soil and the optimal index is BD index,with the model's total root mean square error of 4.68.The results further indicated that the ANN model and the PLSR model can better predict SOM contents of four soil types inThree-River-Headwater Region,and the band depth is the best inversion indicator of the study area.