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引用本文:

DOI:

10.11834/jrs.20243315

收稿日期:

2023-07-19

修改日期:

2024-01-03

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基于多源遥感数据的河流断面提取进展与展望
薛源1, 覃超1, 徐梦珍2, 傅旭东1, 李丹3, 吴保生2, 王光谦2
1.清华大学水圈科学与水利工程全国重点实验室;2.清华大学 水圈科学与水利工程全国重点实验室;3.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。

Progress and Prospects in River Cross Section Extraction Based on Multi-Source Remote Sensing
Abstract:

Natural rivers carry water and materials within a certain boundary geometry. Research on rivers often involves extracting geometric information of river surfaces and boundaries or hydraulic characteristics such as flow velocity and discharge. Among these hydraulic attributes, geometric data 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 river system. Traditionally, the extraction of such data has heavily relied on field measurements, posing challenges in obtaining data for inaccessible areas such as mountainous regions, canyons, disaster-prone regions or expansive river basins. With the continuous advancement of multi-source remote sensing technology, encompassing underwater remote sensing, near-earth remote sensing, and satellite remote sensing, it has become possible to address the data scarcity in mountainous regions, canyons, and other areas 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 examines the strengths and limitations of current methods. This study presented an integrated “air-space-ground” remote sensing data observation scheme, amalgamated with the corresponding automatic extraction methodologies, such as river surfaces extraction method, river width extraction method and river water level extraction method, to extract river information, particularly cross section morphology, in data-scarce or large-scale river basins. Furthermore, this study offered valuable insights into the future development trends by considering the existing technical progress in the field.

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