期刊论文

Determination of Soil Organic Matter Content Based on Hyperspectral Wavelet Energy Features

Yu Lei

中文

光谱学与光谱分析

1000-0593

2019

39

10

3217-3222

10.3964/j.issn.1000-0593(2019)10-3217-06

国家自然科学基金项目(41401232) 中央高校基本科研业务费项目(CCNU19QN050) 湖北省自然科学基金创新群体项目(2016CFA027)资助.

本校为第一且通讯机构

土壤高光谱在采集过程中难以避免噪声干扰, 造成高光谱数据信噪比较低, 影响土壤有机质含量估测精度。 尝试探究小波能量特征方法, 降低高光谱噪声, 提升土壤有机质含量高光谱估测模型性能。 选取湖北省潜江市运粮湖管理区为试验区, 于2016年9月采集80份深度为0~20 cm的水稻土样本; 土壤样本经风干、 碾磨、 过筛等一系列处理后, 在实验室内采集样本光谱, 并通过重铬酸钾-外加热法测定土壤有机质含量; 利用浓度梯度法, 将总体样本集(80个样本)划分为建模集(54个样本)和验证集(26个样本); 以mexh为小波基函数进行连续小波变换(continuous wavelet transformation), 将土壤高光谱转换为10个分解尺...

There is no silver-bullet solution of eliminating noise during the acquisition process of soil hyperspectral. As the noise interference, the observations of soil spectra are in low signal-to-noise ratio, which affects the estimation accuracy of soil organic matter content. This paper attempts to adopt the wavelet energy features method to reduce the noise in soil hyperspectral and improve the estimation accuracy of soil organic matter content. The Yunlianghu Farm of Qianjiang City, Hubei Province, located in the hinterland of Jianghan Plain, wa...