@article{ref1,
title="Automatic flood detection using Sentinel-1 images on the Google Earth engine",
journal="Environmental monitoring and assessment",
year="2021",
author="Moharrami, Meysam and Javanbakht, Mohammad and Attarchi, Sara",
volume="193",
number="5",
pages="e248-e248",
abstract="Flood is considered to be one of the most destructive natural disasters. It is important to detect the flood-affected area in a reasonable time. In March 2019, a severe flood occurred in the north of Iran and lasted for 2 months. In the present paper, this flood event has been monitored by Sentinel-1 images. The Otsu thresholding algorithm has been applied to separate flooded areas from remaining land covers. The threshold value of -14.9 dB was derived and applied to each scene to delineate flooded areas. There was high variability of the inundated area; however, the presented threshold correctly represented the variation of the flood. The resultant maps were further verified by independent datasets. The overall accuracies were higher than 90%, confirming the applicability of the Otsu automatic thresholding method in flood mapping. The automatic approach is efficient in rapid fold mapping across complex landscapes.<p /> <p>Language: en</p>",
language="en",
issn="0167-6369",
doi="10.1007/s10661-021-09037-7",
url="http://dx.doi.org/10.1007/s10661-021-09037-7"
}