Introduction

The image segmentation model can be used to extract real-world objects from images, blur backgrounds, create self-driving automobiles, and perform other image processing tasks. The goal of this research is to create a mask that shows floodwater in a given location based on Sentinal-1 (a dual-polarization synthetic-aperture radar (SAR) system) images or features.

Dataset

MBRSC satellites obtained aerial imagery of Dubai and annotated it with pixel-wise semantic segmentation in six classes. The total volume of the dataset is 72 images grouped into six larger tiles. They are:

• Building: #3C1098

• Land (unpaved area): #8429F6

• Road: #6EC1E4

• Vegetation: #FEDD3A

• Water: #E2A929

• Unlabeled: #9B9B9B

Masks are RGB, and information is provided as a HEX color code.