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| 基于连续小波变换的潮土有机质含量高光谱估算 | |
| 引用本文： | 廖钦洪,顾晓鹤,李存军,陈立平,黄文江,杜世州,付元元,王纪华.基于连续小波变换的潮土有机质含量高光谱估算[J].农业工程学报,2012,28(23):132-139. |
| 作者姓名： | 廖钦洪 顾晓鹤 李存军 陈立平 黄文江 杜世州 付元元 王纪华 |
| 作者单位： | 1. 浙江大学遥感与信息技术应用研究所,杭州 310029 2. 北京农业信息技术研究中心,北京 100097 3. 安徽省农业科学院,合肥 230031 |
| 基金项目： | 国家科技支撑计划项目（2012BAH29B01），国家自然科学基金（31071324），北京市科技新星计划项目（2010B024）和农业部农业生态环境保护项目资助 |
| 摘 要： | 土壤有机质含量快速估算对于土壤肥力评价、土壤信息化管理和精准施肥具有重要意义。该文通过对北京顺义地区64个土壤样品高光谱曲线进行连续小波变换,估算了该地区潮土有机质质量分数,并与4种常用光谱变换方法进行了比较。结果表明,潮土具有与其他类型土壤类似的光谱曲线,经过去包络线处理后,在可见与近红波段都出现了明显吸收峰;采用连续小波变换方法所确定的潮土有机质估算的敏感波段为1194、486和866nm,对应小波分解尺度为2,3和4;利用小波能量系数与有机质质量分数所构建的多元线性回归模型的决定系数R2为0.67,模型实测值与预测值的检验精度R2为0.75,RMSE为0.21;而采用4种常用光谱变换方法建立的潮土有机质估测模型的R2最高只有0.09,说明连续小波变换方法更适合于潮土有机质质量分数估测。Kringing插值分析表明,应在顺义地区东南部增加取样点,以提高模型估算精度。该研究可为潮土土壤肥力的快速测定提供参考。 |
| 关 键 词： | 土壤 有机质 光谱分析 连续小波变换 |
| 收稿时间： | 6/7/2012 12:00:00 AM |
| 修稿时间： | 2012/11/14 0:00:00 |
Estimation of fluvo-aquic soil organic matter content from hyperspectral reflectance based on continuous wavelet transformation |
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| Liao Qinhong,Gu Xiaohe,Li Cunjun,Chen Liping,Huang Wenjiang,Du Shizhou,Fu Yuanyuan and Wang Jihua.Estimation of fluvo-aquic soil organic matter content from hyperspectral reflectance based on continuous wavelet transformation[J].Transactions of the Chinese Society of Agricultural Engineering,2012,28(23):132-139. | |
| Authors: | Liao Qinhong Gu Xiaohe Li Cunjun Chen Liping Huang Wenjiang Du Shizhou Fu Yuanyuan and Wang Jihua |
| Institution: | 1.Institute of Agricultural Remote Sensing and Information Technique,Zhejiang University,Hangzhou 310029,China;2.Beijing Agriculture Information Technology Research Center,Beijing 100097,China;3.An hui Academy of Agricultural Sciences,Anhui 230031,China) |
| Abstract: | Hyperspectral remote sensing technology had been widely used in the estimation of soil organic matter due to its non-destructive, rapid, and high spectral resolution characteristics. The 64 fluvo-aquic soil organic matter (SOM) obtained from Beijing Shunyi district had been estimated successfully by using the hyperspectral reflectance based on continuous wavelet transform (CWT), the results had also been compared with four common spectral transformation methods, it showed that the fluvo-aquic soil had the same spectral curves with other types soils, and the absorption peaks appeared in the visible and near infrared bands after the spectral curves removed by hull curve. The sensitive bands for estimating the SOM were 1194nm, 486nm, and 866nm, and the corresponding wavelet decomposition scales were 2, 3, and 4. The R2 of multiple linear regression model built between the wavelet energy coefficients and SOM was 0.67 by using the CWT, the R2and RMSE between the measured value and predicted value were 0.75 and 0.21, respectively, while the highest R2 of estimation model built by the four common spectral transformation methods was 0.09, which showed that the CWT is more suitable for estimating the fluvo-aquic soil organic matter content. Through the interpolation analysis of Kringing, the more sampling points should be increased in the southeast of Shunyi district for improving the precision of models. |
| Keywords: | soils biological materials spectrum analysis continuous wavelet transform |
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