Applications of unmanned aerial vehicles in fluvial remote sensing: An overview of recent achievements

被引:30
|
作者
Rhee, Dong Sop [1 ]
Kim, Young Do [2 ]
Kang, Boosik [3 ]
Kim, Dongsu [3 ]
机构
[1] Korea Inst Civil Engn & Bldg Technol, Goyang 10223, South Korea
[2] Inje Univ, Dept Environm Engn, Nakdong River Environm Res Ctr, Gimhae 50834, South Korea
[3] Dankook Univ, Dept Civil & Environm Engn, Yongin 16890, South Korea
关键词
unmanned aerial vehicle; remote sensing; fluvial; river; LiDAR; STRUCTURE-FROM-MOTION; SUBMERGED AQUATIC VEGETATION; PARTICLE-IMAGE VELOCIMETRY; BENTHIC MACROALGAL COVER; HIGH-SPATIAL-RESOLUTION; TURBID COASTAL WATERS; HYPERSPECTRAL IMAGERY; AIRBORNE LIDAR; UAV; RIVER;
D O I
10.1007/s12205-017-1862-5
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Previously, understanding of the fluvial process from the ecological, morphological, and hydrodynamic perspectives has largely relied on the limited scale of in-situ field observation or the sparse spatial and temporal scale of satellite-based remote sensing. However, with the recent advent of unmanned aerial vehicles (UAVs) and concurrent advances in sensor technology, measurement campaign has been revolutionized and the view of rivers has fundamentally changed from the local scale to the holistic scale; the perspective has shifted from a static to a dynamic one. UAVs can provide a fine spatial and temporal resolution of measurements with a relatively low cost, which, as compared to conventional satellite or pilot-controlled airborne systems, can be more suitable for the analysis of fluvial processes in narrow rivers and small lakes. In this paper, we comprehensively review and document various crucial achievements driven by UAVs-based remote sensing in fluvial environments, among a variety of other relevant applications. Specifically, the paper highlights the UAV-based fluvial remote sensing in terms of riparian vegetation, hazardous aquatic algae blooms, submerged morphology, water-surface slope, sediment, flow velocity, and disasters, including flood inundation mapping.
引用
收藏
页码:588 / 602
页数:15
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