摘要
The study on soil spectral reflectance features is the physical basis for soil remote sensing. Soil organic matter content influences the soil spectral reflectance dramatically. This paper studied the spectral curves between 400 nm-2500 nm of 174 soil samples which were collected in Hengshan county and Yixing county. Fourteen types of transformations were applied to the soil reflectance R to remove the noise and to linearize the correlation between reflectance （independent vari- able） and soil organic matter （SOM） content （dependent variable）. Then, the methods such as derivative spectrum technology and stepwise regression analysis, were applied to study the relationship between these soil spectral features and soil organic matter content. It shows that order 1 derivative of the logarithm of reflectance （01DLA） is the most sensitive to SOM among the various transform types of reflectance in consideration. The regression model whose coefficient of determination reaches 0.885 is built. It predicted the soil organic matter content with higher effect.
土壤上的学习光谱反射特征是土壤遥感的物理基础。土壤有机物内容影响土壤光谱反射戏剧性地。这篇论文学习了光谱在是的 174 土样的 400 nm∼2500 nm 之间的曲线在 Hengshan 收集了县和 Yixing 县。转变的十四种类型被用于土壤反射 R 移开噪音并且线性化在反射(独立变量) 和土壤有机物(SOM ) 内容(依赖变量) 之间的关联。然后，方法象衍生物光谱技术那样和逐步的回归分析，被使用学习在这些土壤之间的关系光谱特征和土壤有机物内容。它证明命令反射(O1DLA ) 的对数的 1 衍生物对在在考虑的反射的各种各样的变换类型之中的 SOM 最敏感。其决心的系数到达 0.885 的回归模型被造。它与更高的效果预言了土壤有机物内容。
基金
Supported by the National Natural Science Foundation of China （No. 40271007）.
