Flooding is the gravest natural disaster that Madagascar is facing, so the government and disaster experts must monitor and assess the damage. The adoption of the traditional approach is time-taking and expensive, with advances in remote sensing techniques and the availability of free satellite data and platforms for analysis made experts easy. This study is mainly focused on flood mapping and damage assessment in an open-source cloud computing platform, i.e., Google Earth Engine, it is more economical and this methodology can be implemented by underdeveloped nations. For this study, flood-inundated maps were generated using pre and post-flood images of SAR, i.e., sentinel-1 which provides data by continuous observation during flooding, as it can penetrate through the cloud. A land use/land cover map was generated using pre-flood cloud-free sentinel-2 datasets, the overall accuracy is 92.89% and kappa coefficient is 0.91. Finally, an assessment of damage was done by overlaying flood-inundated maps on a land use/land cover map. A total area of 373.88 km2 was flooded out of which 311.52 km2, and 1.01 km2 of cropland and built-up were flooded, respectively. Therefore, this study concludes that combining microwave and optical data for flood mapping and damage assessment in the Google Earth Engine platform is more advantageous and cost-efficient.