Abstract: Floods are natural disasters characterized by the overflow of water onto normally dry land. They are among the most common and widespread of all natural hazards, causing extensive damage to infrastructure, homes, and agricultural land, as well as posing significant risks to human lives. This study proposes an innovative approach leveraging Artificial Intelligence (AI) and Machine Learning (ML) techniques to identify flood-prone areas within urban environments. Monsoons are becoming more erratic because of climate change and global warming. Floods can occur due to various factors such as changes in landscape, rainfall conditions, humidity and temperature. One of the challenges of Urban areas is to prepare for eventuality such as floods in new areas and having safety measures in place to protect human lives and at the same time restrict damages.

Keywords: Machine Learning algorithms, Flood Prediction, SAR images, Image Processing.

| DOI: 10.17148/IARJSET.2024.11485