基于连续小波分析的混合植被叶绿素反演

基金项目: 国家863计划资助项2013AA102401 极地测绘科学国家测绘地理信息局重点实验室开放研究基金资助项目201302

详细信息

Retrieval of Chlorophyll Content Using Continuous Wavelet Analysis Across a Range of Vegetation Species

¹School of Remote Sensing and Information Engineering Wuhan University Wuhan 430079 China

摘要: 利用DB4小波函数对两个尺度4个数据集混合植被高光谱数据进行连续小波分析,分析小波系数与叶绿素含量之间的相关性,建立模型并利用验证数据进行验证,将模型精度与植被指数经验模型进行比较,最后进行了不同数据集之间的交叉验证。结果表明,在叶片尺度与冠层尺度上,基于连续小波分析进行混合植被叶绿素反演,所得模型精度均高于植被指数经验模型精度;在相同尺度上,模拟与实测数据集之间有相同的小波系数特征区域,可以用来进行叶绿素含量反演。
- 高光谱 /
- 连续小波分析 /
- 小波系数 /
- 植被指数
Abstract: Continuous wavelet transform is used for vegetation hyperspectral analysis at two scales among four data sets. The relationship between chlorophyll content and wavelet coefficients was built，and the accuracy was compared to the vegetation index emphasis model. Cross validation was carried out between different data sets. The results show that the accuracy of the wavelet coefficients model is higher than the other models at both scales. Several wavelet features were suitable for chlorophyll retrieval from simulated and measured data seta at the same scale.
- hyperspectral /
- continuous wavelet transform /
- wavelet coefficient /
- vegetation index