3种滤波算法对NDVI高质量数据保真性研究

标准MODIS NDVI产品时间序列仍然存在噪声,必须在利用前处理。理想的去除噪声算法,应该最大限度地去噪,同时最大限度地保留原数据中无噪声像元的真值。以往的研究大多关注不同滤波算法对噪声的处理能力,往往忽略不同算法在滤波处理时对原始高质量数据保真性的研究。基于Timesat 2.3时序滤波工具所提供的3个滤波算法,探讨了原始数据质量差异对滤波算法的保真性的影响以及不同滤波算法对原始高质量数据保真性的差异,通过对比分析发现非对称高斯算法(AG)对原始高质量数据保真性最高,双逻辑曲线拟合算法(DL)性能次之,SG算法拟合结果的保真性较差。

Fidelity Performance of Three Filters for High Quality NDVI Time-series Analysis

Some noises still exist in standard MODIS NDVI product and need to be screened before further applications.An ideal filter should only remove noisy data,and keep the good data as much as possible.Most previous studies only concerned about the filter's performance in terms of handling noisy data,and neglected filter's capacity to retain the original high|quality data (fidelity).The present study analyzed three filters included in Timesat 2.3 tools,examined the effect of data quality on the performance of three filter algorithms,both qualitatively and quantitatively.Through comparative analysis,we concluded that Asymmetric Gaussians has the highest fidelity performance of all,followed by Double Logistic algorithm,and Savizky|Glolay algorithm performance worst.