摘要
对在宜兴市和横山县采集的174个土样400 nm^2 500 nm波段的光谱曲线进行了研究。为了有效去除背景噪声对目标光谱的影响,并将非线性关系线性化,首先对土壤光谱进行了14种变换,然后运用光谱微分技术、逐步回归分析等方法研究了土壤光谱反射特性与土壤有机质之间的关系。结果表明,反射率对数的一阶微分这一变换形式对土壤有机质含量最为敏感。建立了相应的回归预测模型,模型方程判定系数达到0.885,较好地利用土壤光谱反射特性预测了土壤有机质的含量。
The spectral curves between 400 nm-2 500 nm of 174 soil samples which were collected in Hengshan County and Yixing County were studied. Fourteen types of transformation were applied to the soil reflectance R to remove the noise and linearize the correlation between reflectance （independent variable） and soil physical-chemical properties （dependent variable）. Then, methods such as derivative spectrum technology, stepwise regression analysis, were applied to study the relationship between these soil spectral features and soil organic matter content. It shows that order lderivative of the logarithm of albedo is the most sensitive to SOM among the various albedo transforms in consideration. The regression model whose coefficient of determination reaches 0. 885 is built.
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2006年第11期975-979,共5页
Geomatics and Information Science of Wuhan University
基金
国家自然科学基金资助项目(40271007)
国土资源部百名优秀青年科技人才计划资助项目
关键词
土壤有机质
光谱特征
逐步回归分析
soil organic matter
spectral features
stepwise regression analysis
