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Two approaches for estimation of remotely sensed land surface temperature, Ts, based on MSG-SEVIRI data have been tested in a semi-arid environment in West Africa. A local algorithm, based on in situ measured Ts and a regional algorithm, based on MODIS LST products. They are both based on the split-window technique and show encouraging results, however applications are limited to the region for which they are derived. The land surface temperature and vegetation index (NDVI) has in combination been used as an indicator of soil moisture and/or evapotranspiration through a dryness index. The index, denoted TVDI, is based on an evaluation of the Ts/NDVI space. The introduction of MSG-SEVERI data in the estimation of Ts and TVDI offers new possibilities in the application of these parameters since the improved temporal resolution allows for analysis of diurnal variations and greater likelihood of finding cloud free pixels. Plots of diurnal variation in TVDI for selected locations show little variation around midday, suggesting that the index is relatively independent of diurnal variations in Ts.