评估测量河道内水深的方法:绿色激光雷达遥感技术可提供高分辨率的河床地形图,但受到水渗透能力的限制

IF 1.7 4区 环境科学与生态学 Q4 ENVIRONMENTAL SCIENCES
Leif Kastdalen, Morten Stickler, Christian Malmquist, Jan Heggenes
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引用次数: 0

摘要

目的是评估使用机载绿色激光雷达在三条具有不同坡度、水深和透光度(3.5-10 米)的河流的漫长多变河段(4 千米或以上)测量水深的可行性,并使用四种可供选择的激光雷达传感器。绿色激光雷达数据的准确性与分层横断面点取样和多波束测深法收集的现场测量数据进行了比较。对可能限制绿色激光雷达在河流中应用的因素进行了探讨。如果遥感信号被河床反射,传感器提供的高程数据通常与现场高程测量值一致,表明在不同的水力条件下精度很高(±10 厘米)。绿色激光雷达数据的丢失主要是由于信号的水穿透能力(即水的透明度)有限造成的。Secchi 深度是与绿色激光雷达在河流中的穿透能力密切相关的替代变量。在达到 Secchi 深度之前,数据丢失率较低,但在达到 Secchi 深度之后,数据丢失率迅速上升。表层水湍流("白水")和暗色河床植被也会增加绿色激光雷达的信号损失。点密度较低因而空间分辨率较低的传感器信号强度较大,因此能穿透更深的水域。然而,随着水面湍流("白水")覆盖范围的扩大,高点密度的重要性也随之增加。应根据河流特征和项目目标,平衡信号强度与信号密度(空间分辨率)。我们的结论是,遥感绿色激光雷达测深法是一种可靠的方法,可在不同水力条件和水深的河流中有效提供精确的高程数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating methods for measuring in-river bathymetry: Remote sensing green LIDAR provides high-resolution channel bed topography limited by water penetration capability
The objective was to evaluate the feasibility of measuring bathymetry using airborne green LiDAR in long and variable river reaches (4 km or more), across three rivers with varying gradients, water depths and light penetration (3.5–10 m), using four alternative LiDAR sensors. The accuracy of green LiDAR data was compared to in situ measurements collected by stratified transect point sampling and Multibeam bathymetry. Factors potentially limiting the feasibility of green LIDAR in rivers were explored. If remote sensing signals were reflected by the riverbed, the sensors generally provided elevation data consistent with in situ elevation measurements, indicating high accuracy (±10 cm) across different hydraulic conditions. The loss of green LiDAR data was mainly a consequence of limited signal water penetration capability, that is, water clarity. Secchi depth was a proxy variable strongly associated with green LiDAR penetration capability across rivers. Data loss was low up to the Secchi depth but increased rapidly thereafter. Surface water turbulence (‘white water’) and dark riverbed vegetation also increased green LiDAR signal loss. Sensors with lower point density and therefore less spatial resolution had more signal strength and therefore penetrated deeper water. However, with increasing coverage of surface turbulence (‘white water’), the importance of high point density also increased. Signal power should be balanced with signal density (spatial resolution), depending on river characteristics and project objectives. We conclude that remote sensing green LiDAR bathymetry is a robust method that efficiently provides accurate elevation data across rivers with different hydraulic conditions and water depths.
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来源期刊
River Research and Applications
River Research and Applications 环境科学-环境科学
CiteScore
4.60
自引率
9.10%
发文量
158
审稿时长
6 months
期刊介绍: River Research and Applications , previously published as Regulated Rivers: Research and Management (1987-2001), is an international journal dedicated to the promotion of basic and applied scientific research on rivers. The journal publishes original scientific and technical papers on biological, ecological, geomorphological, hydrological, engineering and geographical aspects related to rivers in both the developed and developing world. Papers showing how basic studies and new science can be of use in applied problems associated with river management, regulation and restoration are encouraged as is interdisciplinary research concerned directly or indirectly with river management problems.
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