­A developed approach to detect flooded areas (case study: Firozkoh county in Tehran province)

Floods have severe consequences on infrastructure, agriculture, human lives, and the economy, making them one of the most destructive water-related disasters. To effectively manage this disaster, monitoring and analysis are crucial. In this research, a developed approach was presented to identify flooded areas, with a focus on Firozkoh county in Tehran province, Iran. Specifically, a flood event that occurred on July 28th, 2022, was investigated. To detect flooded areas, Sentinel1 images before and after the flood were collected and preprocessed. These areas appear in dark tones in radar images. However, it is important to note that water bodies such as rivers, lakes, and reservoirs exhibit similar characteristics, and shadows can be mistakenly classified as flooded areas. Therefore, the proposed approach in this study deal with these challenges. At the end, a total of 1369.29 hectares was identified as flooded areas in the case study. To validate the accuracy of the results, TWI and SPI indexes maps were computed and overlaid. This comparison confirmed an accuracy rate of 67%. Additionally, the tweets posted during the flood were examined. Most of them had a hashtag or comment about Mozdaran, a village in Firozkoh county and it is approved by the heat map of detected flooded areas. Overall, this study provides valuable insights into the detection and analysis of flooded areas, offering potential strategies for managing such disasters effectively.