| Title | Land cover dependence in the detection of contaminated pixels in satellite optical data |
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| Author | Cihlar, J; Du, Y; Latifovic, R |
| Source | IEEE Transactions on Geoscience and Remote Sensing (Institute of Electrical and Electronics Engineers) 1999., https://doi.org/10.1109/36.921426 |
| Year | 1999 |
| Alt Series | Earth Sciences Sector, Contribution Series 20042807 |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| Document | serial |
| Lang. | English |
| Media | paper; on-line; digital |
| File format | pdf |
| Released | 2001 05 01 |
| Abstract | The detection of partially contaminated pixels over land is necessary for quantitative applications of satellite optical measurements to estimate surface biophysical parameters such as leaf area index
or vegetation composition. Threshold-based algorithms suffer from the heterogeneity of land cover and the seasonal variability of the radiation reflected and emitted by the land surface. As an alternative, a method based on a Fourier series
approximation to the seasonal trajectory of the normalized difference vegetation index (NDVI) had been previously developed (Cihlar 1996). In this paper, we introduce modifications to the basic algorithm to more closely represent NDVI seasonal trends
for different land cover types, as well as a simplified way to determine the time- and pixel-specific contamination thresholds. Based on the tests with 1993-1996 Advanced Very High Resolution Radiometer (AVHRR) data over Canada, the modified
procedure effectively detects contaminated pixels for boreal ecosystems after the growing season of interest. The modifications also improved its performance while the growing season is in progress; in this case, at least one complete previous
growing season coverage is required 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 pixel. It is concluded that the procedure would perform effectively in other areas, provided that the NDVI temporal trajectories of the cover types of interest can he represented by a mathematical model. |
| GEOSCAN ID | 219609 |
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