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基于多源遥感数据的河流断面提取进展与展望

Progress and prospects in river cross section extraction based on multi-source multisource remote sensing

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【作者】 薛源; 覃超; 徐梦珍; 傅旭东; 李丹; 吴保生; 王光谦;

【Author】 XUE Yuan;QIN Chao;XU Mengzhen;FU Xudong;LI Dan;WU Baosheng;WANG Guangqian;State Key Laboratory of Hydroscience and Engineering, Tsinghua University;Key Laboratory of Hydrosphere Sciences of the Ministry of Water Resources, Tsinghua University;Department of Hydraulic Engineering, Tsinghua University;Emergency Science Research Academy, China Coal Research Institute, China Coal Technology & Engineering Group Co., Ltd.;

【通讯作者】 覃超;

【机构】 清华大学水圈科学与水利工程全国重点实验室; 清华大学水利部水圈科学重点实验室; 清华大学水利水电工程系; 中国煤炭科工集团有限公司煤炭科学研究总院有限公司,应急科学研究院;

【摘要】 河流断面形态是开展河流水文过程、物质通量等研究的基础。断面形态的获取多基于现场量测,制约了难以抵达地区的断面获取及全流域、大范围河段的断面提取。随着多源遥感观测及水面、水下无人观测等智能技术的发展,融合有限的地面观测数据,建立与河流特征相适应的多源遥感自动化提取方法,成为获取河流断面形态的重要途径和新方向。本文系统梳理了近20年来河流断面形态提取的相关研究进展,提出并展望了适用于缺资料地区或大范围流域断面形态提取的“空—天—地”一体化观测方案,结合技术进步,探讨了方案的可行性及未来发展趋势。

【Abstract】 Natural rivers carry water and materials within a certain boundary geometry. Research on rivers oftenfrequently involves extracting the geometric information of river surfaces and boundaries or hydraulic characteristics, such as flow velocity and discharge. Among these hydraulic attributes, geometric data that pertaining to river cross sections and other river features, which are easier to observe than the dynamic flow characteristics, are indispensable for conducting research on hydrological processes and material fluxes within a river system.Traditionally, the extraction of such data has relied heavily relied on field measurements, posing challenges in obtaining data for from inaccessible areas, such as mountainous regions, canyons, disaster-prone regionsareas, or expansive river basins. With the continuous advancement of multi-source remote sensing technology, which encompassing includes underwater remote sensing, near-earth Earthremote sensing, and satellite remote sensing, it has become possible to addressing the data scarcity in mountainous regions, canyons, and other areas has become possible by integrating multi-source remote sensing observations with limited ground measurements and establishing automatic extraction methods. Building upon the advancements made in the extraction of river cross section morphology over the past two decades,this paper study examines the strengths and limitations of current methods. This studyIt presented presents an integrated “air-space-ground” remote sensing data observation scheme, amalgamatedcombined with the corresponding automatic extraction methodologies, such as river surfaces extraction method, river width, extraction method and river water level extraction methods, to extract river information, particularly cross section morphology, in data-scarce or large-scale river basins. Furthermore, this study offered offers valuable insights into the future development trends by considering the existing technical progress in the field.

【基金】 国家自然科学联合基金(编号:U2243218,U2243222);清华大学水沙科学与水利水电工程国家重点实验室课题(编号:sklhseTD-2024-E01,sklhse-2023-B-03,sklhse-2024-B-01)~~
  • 【文献出处】 遥感学报 ,National Remote Sensing Bulletin , 编辑部邮箱 ,2024年11期
  • 【分类号】P332;TP79
  • 【下载频次】36
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