一种新的光谱参量预测黑土养分含量模型

A New Model for Predicting Black Soil Nutrient Content by Spectral Parameters

我国东北黑土富含养分,随着土壤数字制图、精确农业和土壤资源调查等研究的深入,引入航空高光谱数据并提供科学的预测结果成为研究热点。数据源为CASI-1500航空高光谱成像系统,光谱范围380~1 050nm,空间分辨率1.5m。在黑龙江建三江地区采集59个土壤样本,化验获得有机质、全氮、全磷和全钾含量数据,选择eps-regression支持向量机模型,BP神经网络和PLS1最小二乘回归模型,建立光谱与含量的机器学习模型。通过评价3种模型的预测精度,选用支持向量机方法,对航空高光谱数据进行全氮、全磷和全钾的信息提取,采用神经网络方法,反演了有机质信息。研究表明:以光谱统计量、光谱特征值和光谱信息量为大类指标,所选取的18个子指标,能够反映土壤光谱的综合情况,是一种新的土壤光谱数据处理方法。有机质和全钾信息提取精度最高的算法是神经网络法,误差分别为1.21%和0.81%,而支持向量机算法在提取全氮和全磷信息时,验证样本的实测均值和预测均值完全吻合,精度最高。评价航空高光谱提取土壤养分的综合精度,有机质、全氮、全磷和全钾提取误差分别为5.25%,6.05%,2.74%和8.90%,在全磷反演中精度最高。

In the field of soil digital mapping,precision agriculture and soil resourceinvestigation,the study of aerial hyperspectral data to provide scientific prediction results by aerial hyperspectral have become the focus of research,especially in the case of black soil rich in nutrients in Northeast China.The data source is CASI-1500 aerial hyperspectral imaging system with a spectral rangeof 380~1 050 nm,and spatial resolution of 1.5 m.59 soil samples were collected from the Jiansanjiang area in Heilongjiang,and the contents of organic matter,total nitrogen,total phosphorus and total potassium were obtained.In addition,the eps-regression support vector machine model,BP neural network and PLS1 least square regression model are selected to establish the machine learning model of spectrum and content.A support vector machine(SVM)method is used to extract the total nitrogen,total phosphorus and total potassium in aerial hyperspectral data by evaluating the prediction accuracy of the 3 models.The information of organic matter is retrieved by neural network.The results revealed that the datecomputed by the spectral statistic,spectral characteristics and spectral values is a kind of effective spectrum of training data,which can reflect the soilcomprehensive reflectance situation.The neural network method is the most accurate method for the extraction of organic matter and total potassium.The errors are1.21%and 0.81%respectively.The accuracy is the highest in the extraction of total nitrogen and total phosphorus information by support vector machines(SVM).The comprehensive accuracy of aerial hyperspectral extraction of soil nutrients was evaluated.The extraction errors of organic matter,total nitrogen,total phosphorus and total potassium were 5.25%,6.05%,2.74%and 8.90%,respectively,and the total phosphorus retrieval accuracy was the highest.