以田间原状黑土野外实测高光谱反射率为研究对象, 分析黑土有机质的光谱响应波段, 运用光谱分析方法提取光谱指数, 建立基于反射光谱特征的黑土有机质高光谱预测模型. 得出如下结论： (1)黑土反射光谱特征差异主要在小于1 250 nm的光谱范围, 尤其是在小于1 100 nm的范围, 随着有机质含量的变化, 该波谱范围内黑土反射光谱特征呈现单/双谷现象, 有机质是影响黑土反射光谱特征的决定因素. (2)有机质与黑土反射率倒数对数微分的相关系数最高, 最高值在1 260 nm, 达到－0.77(R2), 相关系数高的波谱范围为750～1 260 nm. (3)基于黑土野外光谱反射率的有机质含量高光谱预测模型稳定性强, 预测能力较好, 能够用于黑土有机质含量野外速测.

To develop soil organic matter (OM) quick measuring methods, deepen the application of remote sensing in agriculture, improve agricultural production and management way, and promote the development of quantitative remote sensing studies relating to terrestrial ecosystem, field hyperspectral reflectance in the visible/near infrared bands of black soil in Hailun city, northeast China, was collected and analyzed with spectral analysis methods to discover the spectral characteristics of field reflectance and its influencing factors, and the spectral indices were derived, then black soil organic matter predicting model based on the correlation between OM content and spectral indices was built. Root mean squared error (RMSE) was introduced to validate the predictability and precision of the models, and coefficient of the determination (R2) was used to evaluate stability of the models. The results are as follows: the main spectral region of remarkable differences between field black soil reflectance curves is less than 1 250 nm, especially less than 1 000 nm; OM is the main factor determining the curve shape of field black soil reflectance, anc there are single or double spectral wave troughs for different soil samples because of varying OM content at the spectral region less 1 100 nm; correlation between OM and differential coefficient of logarithmic reflectance reciprocal (DCLRR) is much more significant than that between OM and other reflectance or its transforms, and the maximum coefficient of correlation is at 1 260 nm; the predicting model for black soil OM content is built with DCLRR at 1 260 nm as independent varialble and OM as dependent variable, and the coefficients of determination R2 of the model is 0.71, RMSE is 0.42, so the model is quite good in stability and predictability, and can be used in fast testing of organic matter in black soil.