Evaluating the quality of AVHRR Pathfinder NDVI data for the African continent using SPOT-4 Vegetation data

Abstract

Geografisk Tidsskrift, Danish Journal of Geography 106(1):87–102, 2006 The AVHRR (Advanced Very High Resolution Radiometer) 8 km resolution Pathfinder NDVI (Normalized Difference vegetation Index) 10-day composite data set has been used for numerous local and global scale vegetation time series studies during recent decades. The dataset is a result of considerable processing and resampling from the original 1 km resolution AVHRR LAC (Local Area Coverage) data and combined with inappropriate sensor band design for vegetation monitoring these factors potentially introduce noise in the Pathfinder NDVI. The quality of the Pathfinder data has been difficult to assess but the recent release of SPOT-4 Vegetation (VGT) 10-day composite (S10) NDVI data is considered to be an improvement on the AVHRR data and offers the first possibility for a correct analysis/evaluation of the Pathfinder data.—In this study, three years of AVHRR Pathfinder and resampled SPOT-4 VGT (1998–2000) data has been evaluated/analysed using an ortho-regression analysis on 10-day, monthly and annual integrated values. Annual integrated values of AVHRR Pathfinder and SPOT-4 VGT data can be characterized by a linear relationship and correlate well on a continental scale. However the dynamic range of the SPOT-4 VGT NDVI is higher than the AVHRR Pathfinder NDVI. Analysis of individual IGBP biomes shows biome specific differences; evergreen broadleaf forest characterized by lower r values and highest RMSE values and normalized RMSE values indicate largest divergence for the shrubland biome. When performing the analysis on monthly maximum composites and 10-day composite data, intra-annual variations appear. Analyses of 10-day data also show a linear relationship between the NDVI of the two composite products; the relationship being characterized by lower r values and higher RMSE's. Monthly and 10-day maximum composites reveal intra-annual variations in the correlation between the SPOT-4 VGT and AVHRR Pathfinder data. This is attributed to different cloud masking algorithms; the SPOT-4 VGT cloud screening algorithm being insufficient thereby suppressing the rainy season ND VI. However, the correspondence between the SPOT-4 VGT and A VHRR PAL data is considerably better for a transect analysis covering an area not severely influenced by clouds when compared to the continental scale analysis. This suggests that the major part of the noise found in the continental scale SPOT-4 VGT NDVI and AVHRR PAL NDVI analyses can be attributed the different cloud masking algorithms and is to a lesser degree a consequence of the AVHRR PAL NDVI resampling. It is concluded that the quality of the AVHRR NDVI PAL is adequate for time series continental scale vegetation analysis despite the resampling scheme.