| 利用包络线消除法反演黄绵土水分含量 |
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| 引用本文： | 刘秀英,王力,常庆瑞,宋荣杰.利用包络线消除法反演黄绵土水分含量[J].武汉大学学报(信息科学版),2017,42(5):661-668. |
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| 作者姓名： | 刘秀英 王力 常庆瑞 宋荣杰 |
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| 作者单位： | 1.河南科技大学农学院, 河南 洛阳, 471003 |
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| 基金项目： | 国家863计划2013AA102401-2河南科技大学博士科研启动基金13480074国家“十二五”科技支撑计划2012BAH29B04-00河南省科技攻关计划132102110210 |
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| 摘 要： | 采集2014年陕西省乾县黄绵土土壤样本129个，风干过程中进行光谱反射率及水分含量测定，采用包络线消除法提取水分吸收特征参数，进行黄绵土水分含量反演。在对土壤水分含量和光谱吸收特征参数进行相关分析的基础上，运用一元线性回归、对数、指数、幂函数分析法，建立了土壤水分含量定量反演模型。结果表明，相关性较好的为最大吸收深度（D）、吸收总面积（A）、吸收峰右面积（RA）和吸收峰左面积（LA），1 900 nm的光谱吸收特征参数相关性优于1 400 nm。以D1 900、RA1 900为自变量建立的一元线性模型和A1 900、A1 400为自变量建立的对数模型是最佳预测模型，其建模和验证模型的决定系数R2分别大于0.92和0.95，相对分析误差值大于4，预测均方根误差小于1.5%。
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| 关 键 词： | 黄绵土 包络线消除 水分含量 高光谱 |
| 收稿时间： | 2015-03-31 |
Prediction of Moisture Content in Loess Using Continuum-Removed Method |
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| Affiliation: | 1.Agronomy College, Henan University of Science and Technology, Luoyang 471003, China2.College of Natural Resources and Environment, Northwest A & F University, Yangling 712100, China |
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| Abstract: | Loess soil samples (129) taken from the field in Qian county of Shaanxi Province in 2014, were chosen as objects. The gravimetric moisture content and spectra of soil samples were measured during the air drying process. The moisture absorption characteristic parameters extracted using the continuum-removal method, quantitatively predicted the moisture content in loess. Quantitative inversion models of soil moisture content were devised using linear regression, logarithm, power law, and exponential analysis based on analyzing the correlation between spectral absorption feature parameters and the soil moisture content. Results showed that the spectral absorption characteristic parameters of the most correlated coefficients with soil moisture were the maximum absorption depth (D) and total absorption area (A), absorption peak right area (RA), and absorption peak left area (LA). The correlation between the spectral absorption characteristic parameters and the soil moisture content in 1 900 nm was better than 1 400 nm. The best prediction models of soil moisture content were the linear models using the maximum absorption depth in 1 900nm (D1 900) and the absorption peak right area in 1 900nm (RA1 900) as independent variable and logarithm models using the total absorption area in 1 900 nm (A1 900) and the total absorption area in 1 400nm (A1 400) as the independent variable, respectively. The coefficient of determination (R2) of calibration and validation was bigger than 0.92 and 0.95, respectively, and the residual prediction deviation (RPD) was greater than 4, and the root mean squared error of prediction (RMSEp) was smaller than 1.5%. The study provides a reference for rapid determination the soil moisture in precision agriculture. |
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