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Abstract Most previous applications of coarse scale remote sensing data for land-cover mapping and land-cover change analysis were based on multi-temporal Normalized Difference Vegetation Index (NDVI) data. Recent empirical studies have documented that the combination of measurements of thermal infrared radiation (e.g., land brightness temperature, Ts) and vegetation indices (VI) improves the mapping and monitoring of land cover at broad scales. We investigate the biophysical justification for such a combination, using 10 years of Advanced Very High Resolution Radiometer (AVHRR) global area coverage ( GAC) data over the African continent. First, we review recent findings on the biophysical interpretation of the TS-VI space. Second, we analyse the seasonal time trajectories of different biomes in the TS-NDVI space. Third, we measure the relative role of multi-temporal NDVI and Ts data in the discrimination of land cover classes for land-cover mapping. Fourth, we analyse trajectories of land-cover change in the TS-NDVI space for study sites in three different environments. We illustrate the usefulness of the ratio between Ts and VI as an index to perform measurements in the Tj-NDVI space.
Lambin et al. (1996) studied this question.