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Unveiling the hidden dynamics of intermittent surface water: A remote sensing framework

文献类型：期刊论文

作者Xiao, Zhen3; Li, Runkui2,3; Ding, Mingjun1; Cai, Panli3; Guo, Jingxian3; Fu, Haiyu3; Zhang, Xiaoping3; Song, Xianfeng2,3
刊名REMOTE SENSING OF ENVIRONMENT
出版日期2024-09-01
卷号311页码:17
关键词Intermittent water bodies Intermittency degree Spatiotemporal dynamics Remote sensing Water body classification
ISSN号0034-4257
DOI10.1016/j.rse.2024.114285
英文摘要Intermittent surface water frequently transitioning between water and land over months and years, plays a crucial and increasingly significant role in both social and ecological systems. However, their vital and dramatic dynamics have mainly remained invisible due to monitoring limitations. We present a new remote sensing framework to capture the long-term monthly dynamics of surface water bodies, applying it to Poyang Lake, the largest freshwater lake in China. This framework employed a random forest classifier on all available Landsat data to identify monthly surface water bodies. Additionally, we developed a Spatial and Temporal Neighborhood Similarity-based Gap Filling method to restore water bodies obscured by clouds and ensure spatial integrity. Furthermore, we introduced an index to quantify the intermittency of surface water bodies on a scale from 0 to 1, allowing for the classification of water bodies into three categories: perennial, wet intermittent, and dry intermittent. Employing this framework, we reconstructed the most complete monthly 30-m surface water dataset for cloudy regions to date, covering April 1986 to September 2023, demonstrating a strong correlation (Spearman's rank correlation coefficient of 0.909) with observed water levels. The results reveal a landscape dominantly composed of intermittent water bodies (91.2%), with a rapidly shrinking trend of perennial water bodies at 1303.58 ha per year. Notably, 162,685 ha (21.9%) of water bodies transitioned toward drier and more intermittent statuses. Dry intermittent water bodies exhibited the most pronounced land-water transitions, with the highest water-to-land (82.5%) and land-to-water (89.9%) proportions among the three categories. By uncovering the hidden dynamics of intermittent surface water, and highlighting its prevalence, expansion, and vulnerability, this framework paves the way for a better understanding of these critical water dynamics across the globe.
WOS关键词POYANG LAKE WETLAND ; FLOW INTERMITTENCE ; INDEX NDWI ; LANDSAT ; CLIMATE ; RIVERS ; COVER ; CHINA ; CLOUD ; INUNDATION
资助项目National Natural Science Foundation of China[42341206] ; National Natural Science Foundation of China[42161021] ; Fundamental Research Funds for the Central Universities[E3E40503X2]
WOS研究方向Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:001261865300001
出版者ELSEVIER SCIENCE INC
资助机构National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities
源URL[http://ir.igsnrr.ac.cn/handle/311030/207751]  
专题资源与环境信息系统国家重点实验室_外文论文
通讯作者Li, Runkui
作者单位1.Jiangxi Normal Univ, Sch Geog & Environm, Nanchang 330022, Peoples R China
2.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
3.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714		 Xiao, Zhen,Li, Runkui,Ding, Mingjun,et al. Unveiling the hidden dynamics of intermittent surface water: A remote sensing framework[J]. REMOTE SENSING OF ENVIRONMENT,2024,311:17.
APA Xiao, Zhen.,Li, Runkui.,Ding, Mingjun.,Cai, Panli.,Guo, Jingxian.,...&Song, Xianfeng.(2024).Unveiling the hidden dynamics of intermittent surface water: A remote sensing framework.REMOTE SENSING OF ENVIRONMENT,311,17.
MLA Xiao, Zhen,et al."Unveiling the hidden dynamics of intermittent surface water: A remote sensing framework".REMOTE SENSING OF ENVIRONMENT 311(2024):17.

入库方式： OAI收割

来源：地理科学与资源研究所

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