A comparison of SMMR and AVHRR data for continental land cover characterization

Images using reflected visible and near-infrared data and images using passive microwave data were compared in terms of their usefulness for characterizing land-cover types in South America and Africa. The former images are of the normalized difference vegetation index (NDVI) subsampled to approximately 15-20 km resolution in the NOAA global vegetation index product. The latter images of the microwave polarization difference temperature (MPDT) are derived from the difference between horizontally and vertically polarized radiation in the 37 GHz band. Results of maximum-likelihood classifications applied to multi-temporal data sets indicate that, overall, the NDVI data sets are substantially better than the MPDT data sets for land-cover characterization. However, the greater sensitivity of the MPDT data in semi-arid areas results in their superior performance for some classes in these areas. The combined use of MPDT and NDVI data sets show clear synergistic benefits in using the two data sets. However, the evidence suggests that for most cover types, increasing the temporal frequency of the NDVI images is more advantageous than incorporating MPDT data sets.