Emerging remote sensing techniques for hydrological applications

IF 11.4 1区地球科学 Q1 ENVIRONMENTAL SCIENCES

Remote Sensing of Environment Pub Date : 2025-10-15 DOI:10.1016/j.rse.2025.115060

Jiangyuan Zeng, Di Long, Yongqiang Zhang, Dongryeol Ryu, Jean-Pierre Wigneron, Qi Huang

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引用次数: 0

Abstract

In light of the rapid advancements in hydrological science research facilitated by cutting-edge remote sensing technologies, such as synthetic aperture radar (SAR), hyperspectral imaging, and Light Detection and Ranging (LiDAR), we have curated a special issue in Remote Sensing of Environment entitled “Emerging remote sensing techniques for hydrological applications”, spanning from October 2022 to April 2024. This special issue comprises 31 publications that highlight methodologies leveraging multi-sensor satellite platforms, unmanned aerial vehicles (UAVs), and advanced physical models and machine learning approaches to improve the monitoring and modeling of key hydrological flux and state variables. These remote sensing retrievals (e.g., river discharge and soil moisture) have been applied to various operational hydrological applications such as real-time flood monitoring and drought risk assessment. To provide a systematic overview, we categorize these publications based upon hydrological themes and the number of publications, covering topics such as water body, soil moisture, river discharge, water level, drought, water storage, and other related areas. Finally, we provide an outlook that envisages how the emerging trends (e.g., multi-sensor integration and machine learning-driven approaches) identified from the published studies will evolve and shape future research directions in hydrological remote sensing.

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水文应用的新兴遥感技术

鉴于尖端遥感技术（如合成孔径雷达（SAR）、高光谱成像和激光探测与测距（LiDAR））推动了水文科学研究的快速发展，我们在《环境遥感》杂志上策划了一期特刊，题为“水文应用的新兴遥感技术”，时间跨度为2022年10月至2024年4月。本期特刊包括31篇出版物，重点介绍了利用多传感器卫星平台、无人机（uav）、先进的物理模型和机器学习方法来改进关键水文通量和状态变量的监测和建模的方法。这些遥感检索（例如河流流量和土壤湿度）已应用于各种业务水文应用，例如实时洪水监测和干旱风险评估。为了提供一个系统的概述，我们根据水文主题和出版物数量对这些出版物进行分类，包括水体、土壤湿度、河流流量、水位、干旱、储水和其他相关领域。最后，我们提供了一个展望，设想从已发表的研究中确定的新兴趋势（例如，多传感器集成和机器学习驱动的方法）将如何发展并塑造未来水文遥感的研究方向。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

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.