Leif Kastdalen, Morten Stickler, Christian Malmquist, Jan Heggenes
{"title":"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","authors":"Leif Kastdalen, Morten Stickler, Christian Malmquist, Jan Heggenes","doi":"10.1002/rra.4245","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":21513,"journal":{"name":"River Research and Applications","volume":"293 1","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluating methods for measuring in-river bathymetry: Remote sensing green LIDAR provides high-resolution channel bed topography limited by water penetration capability\",\"authors\":\"Leif Kastdalen, Morten Stickler, Christian Malmquist, Jan Heggenes\",\"doi\":\"10.1002/rra.4245\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":21513,\"journal\":{\"name\":\"River Research and Applications\",\"volume\":\"293 1\",\"pages\":\"\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2024-01-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"River Research and Applications\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1002/rra.4245\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"River Research and Applications","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1002/rra.4245","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
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.
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.