大洪水
阈值
计算机科学
大津法
遥感
阈值限值
环境科学
人工智能
地图学
地质学
水文学(农业)
地理
图像(数学)
岩土工程
环境卫生
考古
医学
作者
Meisam Moharrami,Mohammad Javanbakht,Sara Attarchi
标识
DOI:10.1007/s10661-021-09037-7
摘要
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.
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