摘要
利用基于傅立叶变换的HANTS算法,对中国地区(不包括南海诸岛)AVHRRNDVI时间序列数据进行简化和压缩,将植被的动态变化情况通过NDVI在时间和空间上量化,实现了时间序列图像中云和错误信息的检测、去除和替代。利用HANTS算法提取时间序列的傅立叶分量(幅值分量、频率分量),并由这些分量得出NDVI时间序列拟合曲线,依照曲线进行时间上的插值,从而重构无缝的时间序列图像。
This paper applied the Harmonic Analysis of Time Series (HANTS) algorithm based on Fourier transformation to predigest and compress the NOAA/AVHRR Normalized Difference Vegetation Index (NDVI) time-series images, and at the same time, wipe off and fill in the data where cloud cover and misdata are examined. The HANTS algorithm outputs such Fourier components as amplitude components and phase components. A fit curve is built according to the Fourier components. Temporal interpolation according to the curve makes it possible to reconstruct the sequential time-series images.
出处
《国土资源遥感》
CSCD
2005年第2期29-32,共4页
Remote Sensing for Land & Resources
基金
国家自然科学基金项目(40271084)
863项目(2002AA130010-1-4)资助。
