THE CAPABILITY OF SENTINEL 1 (SAR) FOR FLOOD MAPPING: A CASE STUDY IN SERANG WATERSHED, KULONPROGO REGENCY

Artha Uli Simatupang, S. Murti, T. H. Purwanto
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Abstract

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
sentinel 1 (sar)在洪水制图中的能力:以kulonprogo县serang流域为例
洪水是印尼最常见的自然灾害,其强度高于其他任何自然灾害。洪水是指由于水溢出超过房间的水处理能力而导致一个地区被淹没,造成物质、社会和经济损失的情况。雪朗流域(DAS)属于优先I(危急)流域,因此在未来的管理中有必要确定易发生洪水的地区。哨兵1号遥感图像(SAR)可以在任何时间,白天或晚上,在任何天气条件下进行记录,使其适合洪水分析。本研究旨在确定Sentinel 1 Image (SAR)在确定印度尼西亚Kulonprogo Regency Serang流域的淹没洪水面积方面的能力。使用的方法是Otsu算法,通过测量和评估从图像的归一化直方图中计算出的某一水平阈值的类间方差来确定阈值。Kulonprogo县Serang流域的洪水主要发生在农业地区。哨兵图像在所有条件下获取地表数据的能力可以用于洪水分析,而被动传感器图像无法记录它。此外,使用Otsu算法提取Sentinel 1图像上的淹没区域可以确定一个阈值,以77%的混淆矩阵区分淹没和未淹没区域。关键词:洪水,SAR, Otsu算法
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