The detection of partially contaminated pixels over land is necessary for q
uantitative applications of satellite optical measurements to estimate surf
ace biophysical parameters such as leaf area index or vegetation compositio
n. Threshold-based algorithms suffer from the heterogeneity of land cover a
nd the seasonal variability of the radiation reflected and emitted by the l
and surface. As an alternative, a method based on a Fourier series approxim
ation to the seasonal trajectory of the normalized difference vegetation in
dex (NDVI) had been previously developed [2]. In this paper, we introduce m
odifications to the basic algorithm to more closely represent NDVI seasonal
trends for different land cover types, as well as a simplified way to dete
rmine the time- and pixel-specific contamination thresholds. Based on the t
ests with 1993-1996 advanced very high resolution radiometer (AVHRR) data o
ver Canada, the modified procedure effectively detects contaminated pixels
for boreal ecosystems after the growing season of interest, The modificatio
ns also improved its performance while the growing season is in progress; i
n this case, at least one complete previous growing season coverage is requ
ired to provide the temporal series needed to establish the thresholds. The
modified procedure also yields a contamination parameter that may be used
to estimate the most likely value for NDVI or other variables for each pixe
l. It is concluded that the procedure would perform effectively in other ar
eas, provided that the NDVI temporal trajectories of the cover types of int
erest can be represented by a mathematical model.