STUDY ON QUANTITATIVE INVERSION OF REMOTE SENSING FOR ORGANIC CARBON IN THE TYPICAL BLACK SOIL AREAS OF NORTHEAST CHINA
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摘要:
利用多元逐步回归分析法，结合Landsat8 OLI遥感数据对该地区土壤有机碳进行定量反演.试验采集了164个土壤样品，通过3倍标准差准则对样品进行奇异点去除及数据集划分，其中120个样品作为训练集，44个样品作为验证集，建立土壤有机碳的多元逐步回归预测模型.结果表明：有机碳与Landsat8各波段反射率均显著相关；黑土有机碳光谱预测最优模型以倒数为自变量模型最优，决定系数R2=0.180，均方根误差RMSE=0.558，海伦地区适于Corg含量遥感反演，预测模型稳定性好，可以用于揭示黑土典型区Corg含量的空间分布特征.同时认为在不对土壤进行地面光谱测试的情况下，直接采用化学分析数据与遥感卫星相关联的方法预测模型拟合度有限，光谱对有机碳可解释性较低.
Abstract:The quantitative inversion of soil organic carbon (Corg) in the study area is conducted by using multiple stepwise regression analysis method in combination with Landsat8 OLI remote sensing data. For the test, 164 soil samples are collected. Singular points are removed and data sets are divided by tripled standard deviation. Among the total, 120 samples are chosen as the training set and the other 44 as the validation set to establish the multiple stepwise regression prediction model for Corg. The results show that the organic carbon is significantly correlated with the reflectivity of Landsat8 bands. The optimal model for the prediction of black soil organic carbon spectrum is the one that takes the reciprocal as the independent variable, with the determination coefficient R2=0.180, and root-mean-square error(RMSE)=0.558. Hailun area is suitable for remote sensing inversion of Corg content, with a stable prediction model, which can be used to reveal the spatial distribution of Corg content in typical black soil areas. Meanwhile, it is believed that without ground spectral test for the soil, the fitting degree of prediction model by simply using the method of associating chemical analysis data with remote sensing satellite is limited and the interpretation of Corg by spectrum is poor.
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Key words:
- black soil area /
- organic carbon /
- Landsat8 /
- multiple stepwise regression analysis /
- Northeast China
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表 1 黑土样本集划分后的描述性统计
Table 1. Descriptive statistics of black soil samples by set division
样本集 个数 Corg/10-3 最小值 最大值 均值 标准差 训练集 120 1.07 4.19 2.64 1.33 验证集 44 1.24 3.69 2.71 1.42 
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表 2 土壤光谱反射率及变换形式与有机碳含量的特征波段及其相关系数
Table 2. Characteristic bands and correlation coefficients of organic carbon content for soil spectral reflectance and variation forms
R lgR R′ 1/R 波段 相关系数 波段 相关系数 波段 相关系数 波段 相关系数 1 -0.349** 1 -0.346** 1 -0.176 1 0.388** 2 -0.313** 2 -0.332** 2 -0.268** 2 0.357** 3 -0.306** 3 -0.328** 3 -0.259** 3 0.313** 4 -0.295** 4 -0.320** 4 -0.271** 4 0.263** 5 -0.299** 5 -0.327** 5 -0.16 5 0.383** 6 -0.312** 6 -0.343** 6 0.062 6 0.357** 7 -0.354** 7 -0.329** 7 -0.176 7 0.361** **p＜0.01
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表 3 多元逐步回归模型评价指标分析结果
Table 3. Analysis results of evaluation indexes for multiple stepwise regression model
评价指标 非标准化系数 t p VIF R2 F B 标准误差 常数 1.644 0.163 10.069 0.000** - 0.18 F（2，117）=12.833，p=0.000 倒数B1 0.056 0.014 3.975 0.000** 4.559 倒数B4 -0.038 0.018 -2.04 0.044* 4.559 n=120.因变量：Corg. D-W值：1.725. *p < 0.05，**p < 0.01.
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