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Floods are the most common natural disaster in Indonesia, with high intensity than any other natural disaster. A flood is a condition where an area is inundated due to an overflow of water that exceeds the water disposal capacity in a room, resulting in physical, social, and economic losses. The Serang watershed (DAS) belongs in the Priority I (critical) watershed condition, so it is necessary to determine flood-prone areas in future management. Sentinel 1 Remote Sensing Image (SAR) can record at any time, day or night, and in all weather conditions, making it suitable for flood analysis. This study aimed to determine the ability of Sentinel 1 Image (SAR) in determining the inundation flood area in Serang watershed, Kulonprogo Regency, Indonesia. The method used was the Otsu algorithm with threshold determination by measuring and evaluating the variance between classes of a threshold at a certain level calculated from the normalized histogram of the image. Floods in the Serang watershed, Kulonprogo Regency, mainly occur in agricultural areas. The ability of Sentinel images to obtain land surface data in all conditions can be used for flood analysis where passive sensor images cannot record it. In addition, the withdrawal of inundation areas on Sentinel 1 imagery using the Otsu algorithm can determine a threshold to separate inundated and unflooded areas with a confusion matrix of 77%. Keywords: Flood, Sentinel 1 (SAR), Otsu Algorithm