Removal of noise by Wavelet method to generatethe high-quality time series of terrestrial MODIS products

摘要

Time series data for Normalized Difference Vegetation Index (NDVI) derived from TERRA or AQUA/MODIS has been widely used in many researches, including global environment change, agricultural production estimate and disaster early warn, but the data are often suffered from noise caused by cloud contamination, atmospheric variability, background uncertainty and bi-directional effects. To improve the quality of time-series data, many methods are proposed to remove noise. However those methods have several drawbacks that impede their effectiveness in practice application. In this paper, a new method based on wavelet is proposed and used to remove residual noise in the (NDVI) time-series data.