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Pakistan's 2022 floods: Spatial distribution, causes and future trends from Sentinel-1 SAR observations
Chen, Fang1,2,3; Zhang, Meimei1,2; Zhao, Hang4; Guan, Weigui1,2,3; Yang, Aqiang1,2
作者部门光谱成像技术研究室
2024-04-01
发表期刊Remote Sensing of Environment
ISSN00344257
卷号304
产权排序4
摘要

Floods are a great threat to Pakistan with increasing concern. As the consequences of increased extreme weather related to climate change, Pakistan experiences severe floods almost every year. This study aims to explore and analysis the actual inundated situation, magnitude, the possible causes of the 2022 devastating floods, and future trends. We presented an enhanced nationwide flood mapping method and compared with other pixel-based image processing techniques including active contours and change detection. These algorithms were applied to Sentinel-1 Ground Range Detected (GRD) Synthetic Aperture Radar (SAR) imagery (10 m spatial resolution) with various land types and inundation scenarios in Pakistan, and were evaluated using other reference flood products. Accuracy evaluation analysis demonstrated that our algorithm has high robustness and accuracy, with the overall accuracy (OA) higher than 0.83 and critical success index (CSI) up to 0.91, and is suitable for automated flood monitoring in near real time. Nearly one-third of the lands were flooded in 2022, and more than half were inundated croplands. Punjab and Sindh provinces were the most severely affected regions, with the proportions of inundated area in 2022 (21.26% and 20.55%) nearly twice of that in 2010 (11.40% and 12.70%), indicating an intensified flooding trend. Analysis of possible influential factors showed that the intense and cumulative rainfall during the monsoon season (June to August) was the major cause of the 2022 flood event. Although the snow melted rapidly in June (the average change in snow depth is ∼10 mm), the overall ablation contributed insignificant amount to the flood water. The glacial lake outburst floods (GLOFs) induced by abnormal April–May heatwave provide water flowed into the tributaries of the Indus River, but are difficult to spread for thousands of kilometers from mountains to the plain downstream. The combination of the intrinsic arid climate and extreme floods exacerbate the already severe situation. © 2024 Elsevier Inc.

关键词Flood monitoring Climate change Snow melting Pakistan Synthetic Aperture Radar (SAR)
DOI10.1016/j.rse.2024.114055
收录类别EI
语种英语
出版者Elsevier Inc.
EI入藏号20240915643476
引用统计
文献类型期刊论文
条目标识符http://ir.opt.ac.cn/handle/181661/97254
专题光谱成像技术研究室
通讯作者Zhang, Meimei; Zhao, Hang
作者单位1.International Research Center of Big Data for Sustainable Development Goals, Beijing; 100094, China;
2.Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing; 100094, China;
3.University of Chinese Academy of Sciences, Beijing; 100049, China;
4.Key Laboratory of Spectral Imaging Technology, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an; 710119, China
推荐引用方式
GB/T 7714
Chen, Fang,Zhang, Meimei,Zhao, Hang,et al. Pakistan's 2022 floods: Spatial distribution, causes and future trends from Sentinel-1 SAR observations[J]. Remote Sensing of Environment,2024,304.
APA Chen, Fang,Zhang, Meimei,Zhao, Hang,Guan, Weigui,&Yang, Aqiang.(2024).Pakistan's 2022 floods: Spatial distribution, causes and future trends from Sentinel-1 SAR observations.Remote Sensing of Environment,304.
MLA Chen, Fang,et al."Pakistan's 2022 floods: Spatial distribution, causes and future trends from Sentinel-1 SAR observations".Remote Sensing of Environment 304(2024).
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