Flood monitoring with satellite images is an effective method of detecting and tracking floods. This approach involves the use of satellite imagery to detect changes in water levels and identify flooded areas. To monitor floods using satellite images, the images are analyzed to detect changes in water levels over time. To detect changes in water levels and identify flooded areas based on a set of predefined criteria, we can train algorithms. Amazon SageMaker geospatial capabilities make it easier for data scientists and machine learning (ML) engineers to build, train, and deploy ML models using geospatial data.  These capabilities also provide pre-trained models. One of the pre-trained models is land cover segmentation model. This land cover segmentation model can be run with a simple API call and can be leverage to analyze changes in the water level.