Effects of atmospheric variation on AVHRR NDVI data

Abstract

The AVHRR (Advanced Very High Resolution Radiometer) series of instruments has frequently been used for vegetation studies. The 25+ year record has enabled important time-series studies. Many applications use NDVI (Normalized Difference Vegetation Index), or derivatives of it, as their operational variable. However, most AVHRR datasets have incomplete atmospheric correction, because of which there is considerable, but largely unknown, uncertainty in the significance of differences in NDVI and other short wave observations from AVHRR instruments. The purpose of this study was to gain better understanding of the impact of incomplete or lack of atmospheric correction in widely-used, publicly available processed AVHRR-NDVI long-term datasets. This was accomplished by comparison with atmospherically corrected AVHRR data at AERONET (AErosol RObotic NETwork) sunphotometer sites in 1999. The datasets included in this study are: TOA (Top Of Atmosphere) that is with no atmospheric correction; PAL (Pathfinder AVHRR Land); and an early version of the new LTDR (Long Term Data Record) NDVI. The other publicly available datasets like GIMMS (Global Inventory Modeling and Mapping studies) and GVI (Global Vegetation Index) have atmospheric error budget similar to that of TOA, because no atmospheric correction is used in either processing stream. Of the three datasets, LTDR was found to have least errors (accuracy = 0.0064 to − 0.024, precision = 0.02 to 0.037 for clear and average atmospheric conditions) followed by PAL (accuracy = − 0.145 to − 0.035, precision = 0.0606 to 0.0418), and TOA (accuracy = − 0.0791 to − 0.112, precision = 0.0613 to 0.0684). It was also observed that temporal maximum value compositing technique does not cause significant improvement of precision in regions experiencing persistently high AOT (Aerosol Optical Thickness).