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

IF 11.1 1区 地球科学 Q1 ENVIRONMENTAL SCIENCES Remote Sensing of Environment Pub Date : 2024-06-27 DOI:10.1016/j.rse.2024.114285
Zhen Xiao , Runkui Li , Mingjun Ding , Panli Cai , Jingxian Guo , Haiyu Fu , Xiaoping Zhang , Xianfeng Song
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Abstract

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.

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揭示间歇性地表水的隐藏动态:遥感框架
间歇性地表水在数月或数年中经常在水与陆地之间转换,在社会和生态系统中发挥着至关重要且日益重要的作用。然而,由于监测的局限性,它们的生命力和戏剧性的动态主要还是被忽视了。我们提出了一种新的遥感框架,用于捕捉地表水体的长期月度动态,并将其应用于中国最大的淡水湖--鄱阳湖。该框架在所有可用的 Landsat 数据上使用随机森林分类器来识别月度地表水体。此外,我们还开发了一种基于时空邻域相似性的间隙填充方法,用于恢复被云层遮挡的水体,确保空间完整性。此外,我们还引入了一个指数来量化地表水体的间歇性,指数范围从 0 到 1,可将水体分为三类:常年水体、湿间歇水体和干间歇水体。利用这一框架,我们重建了迄今为止最完整的多云地区月度 30 米地表水数据集,涵盖时间为 1986 年 4 月至 2023 年 9 月,结果表明该数据集与观测水位具有很强的相关性(斯皮尔曼等级相关系数为 0.909)。结果表明,景观主要由间歇性水体组成(91.2%),常年性水体呈快速缩减趋势,每年缩减 1303.58 公顷。值得注意的是,162,685 公顷(21.9%)的水体向更干燥、更间歇的状态过渡。干旱间歇性水体的水陆过渡最为明显,水到陆地(82.5%)和陆到水(89.9%)的比例在三类水体中最高。通过揭示间歇性地表水的隐性动态,并强调其普遍性、扩展性和脆弱性,该框架为更好地了解全球这些关键的水动态铺平了道路。
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来源期刊
Remote Sensing of Environment
Remote Sensing of Environment 环境科学-成像科学与照相技术
CiteScore
25.10
自引率
8.90%
发文量
455
审稿时长
53 days
期刊介绍: Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing. The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques. RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.
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