The Miombo woodlands are characterized by a transition period which is defined as the dry period in which grasses wither, trees shed and flush their leaves a few weeks before the rainy season. It is difficult to measure evaporation, due to the influence of the plant water storage on the water availability during the dry season. The seasonal variation in the plant water storage makes it even harder, as the time lag between the plant water storage and the terrestrial groundwater storage varies between the 0 to 90 days depending on the vegetation density. (Tian et al., 2018). It is unclear why the trees prefer this early flushing strategy and what is triggering the shedding of old leaves and flushing of new leaves. It is difficult to remotely sense the variation during this period. In this report, the outputs of several evaporation products and the vegetation indices are studied and compared to see how models follow the transition period. Three models, that are chosen for the comparison use different methods to indirectly calculate the evaporation flux. The first model is the Surface Energy Balance System (SEBS), which is based on the Surface Energy Balance as the name suggests and calculates the evaporation through land-atmosphere relationships. The second model is the Global Land Evaporation Amsterdam Model (GLEAM); this model uses the water balance model to calculate the water stress factor and in return the actual evaporation. And lastly, the MODIS Terrestrial Evapotranspiration (MOD16A2) which uses the Penman-Monteith equation as a basis to separately calculate the evaporative fluxes such as transpiration, soil evaporation, and interception. The outputs of the evaporation models differ quite a lot, especially during the transition period. This is among other things due to the input variable such as vegetation indices. There are several vegetation indices such as the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Infrared Index (NDII) and the Leaf Area Index (LAI). The difference in the indexes is minimal and only small timing differences can be found. This means that the output differences are not influenced by the vegetation indices. MODIS follows the trends found by the vegetation indices best as it does not have the shortcomings that GLEAM and SEBS display. GLEAM overestimates the water stress because the model doesn’t account for plant water storage. While SEBS responds well until the start of July in which the model starts to oscillate. The oscillations could be due to the slash and burn culture which happens around this time which could impact SEBS substantially due to its dependency on temperature and radiation. Even if the MODIS output is the most similar to the vegetation output, it is limited by the fact that it is average values and daily variations might be lost. As this research is based on mostly satellite images supplemented by field observations, no statements can be made about it how accurate the models are. But based on this research, the MODIS model seems to be the preferred evaporation output.