多时相AVHRR数据的傅立叶分析

傅立叶分析(FourierAnalysis)是一种常用的信号处理方法.将中国全年 36旬的NOAA AVHRR的 1km数据采用最大值合成法获得 1 2个月的NDVI时间序列数据,然后运用离散傅立叶变换检测该时间信号的频率分布状况.结果各频率分量与NDVI的累加值及不同周期的季节性变化等生物学特征相关.其中零频率分量为均值NDVI,而 1/1 2频率分量最大程度概括了中国地表覆盖类型的全年季节性变化模式.将提取出的这些生物学特征引入到地表覆盖分类的特征空间中,提高了类别间的可分性.这些研究表明了傅立叶变换是分析多时相AVHRR数据及提取植被的生物学特征的有用工具

Fourier Analysis of Multi-Temporal AVHRR Data

Fourier transform is presented and applied to monthly composited NDVI data over one year derived from NOAA AVHRR to examine the frequency distribution of the multi temporal signal. It is shown that frequencies of the time series of NDVI are linked to integrated NDVI and seasonal variabilities of different periods of the land cover types. The zero frequency component, or mean NDVI, indicates overall productivity. The 1/12 month -1 frequency component summarizes the relative dominance of annual habit of land cover types over China. The introduction of these characteristic phenology parametersextracted from time series of NDVI into feature space improves the separabilities based on Bhattacharya Distances for land cover types. This research indicates that Fourier transform provides a useful tool for handling temporal sequences of AVHRR data and studying the vegetation phenology.