Orbital drift results in late equatorial crossing times for the afternoon National Oceanic and Atmospheric Administration (NOAA) polar satellites and in changes of illumination that affect measurements made by the advanced very high resolution radiometer (AVHRR). Processing and correcting for calibration variation(s) and atmospheric effects have improved, but one of the standard AVHRR products, the normalized difference vegetation index (N D V I) , may still contain variations due to orbital drift or changes in sun-target-sensor geometry. In this study, the solar zenith angle (SZA) trends associated with orbital drift are identified and analyzed with respect to their effects on the N D V I. The adaptive empirical mode decomposition (EMD) method is used to identify and remove the induced artifacts from the N D V I time series. The EMD is based on the local characteristic time scale of the data and is used to identify embedded nonlinear and nonstationary variation. Trend artifacts associated with drift were uncoupled from the surface signal, and their contributions were quantified at all latitudes. The approach was tested on 1 degree and 8-km N D V I global datasets, and showed that it is very suitable for addressing the long-standing issues of orbital shifting or the inconsistencies of the AVHRR data among sensors. The results showed that the interference of satellite drift artifacts with the surface signal was (i) large in a tropical forest, (ii) moderate in the tropics for less-densely vegetated areas, and (iii) lowest at higher northern and lower southern latitudes.