Seasonal wetlands (dambos) are a vital element in Sub-Saharan Africa for their functionality toward food production and ecosystem services they provide. However, over the years the intensive use of dambos has caused uncertainty about land degradation with associating effect to environment and local livelihood. WET-Health assessments has been one of the primary assessment techniques used to manually evaluate ecological health of these dambos. This manual assessment involves local farmer’s interviews and manual classification of satellite images, which has heavily depended on an expert’s time and his capacity to produce the correct assessment, likewise the cost of his expertise. As remote sensing has widely used to monitor and evaluate environmental changes with consideration of time and cost management, hence the need to integrate both remote sensing technique and WETHealth assessment to address issues faced by these experts. The aim of this research is to develop remote sensing (RS)-based wetland assessment methods. To achieve this aim, I conducted an unmanned aerial vehicle (UAV) survey of four dambos in Central Malawi. These UAV data were processed and analysed to produce the landcover extent using supervised classification methods (SVM). The UAV-generated outputs (classification maps) were then compared with the manual assessment of the same dambos to evaluate effectiveness of UAV-based wetland assessment. These classification maps were used to calculate overall magnitude impact scores and ecological health categories. Overall, the UAV-based assessment provided more detailed and accurate (Kappa = 0.31 - 0.76) representation of the landcover types when compared to the manual assessment result. While the ecological health categories were similar to the expert’s manual assessment, this is due to the high intensity impact score calculated from the cultivated land set higher than other features These results demonstrate that UAV-based assessment is feasible and can produce a more detailed and accurate assessment of land-use of dambos, however there is need to revise the overall WET-Health protocol analysis to implement UAV-based (remote sensing) assessment.