Article(id=1311351203422892570, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1311351152067830064, articleNumber=null, orderNo=null, doi=10.20040/j.cnki.1000-7709.2026.20250206, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1738944000000, receivedDateStr=2025-02-08, revisedDate=1744214400000, revisedDateStr=2025-04-10, acceptedDate=1744819200000, acceptedDateStr=2025-04-17, onlineDate=1790580090622, onlineDateStr=2026-09-28, pubDate=1769270400000, pubDateStr=2026-01-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1790580090622, onlineIssueDateStr=2026-09-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1790580090622, creator=13701087609, updateTime=1790580090622, updator=13701087609, issue=Issue{id=1311351152067830064, tenantId=1146029695717560320, journalId=1205116964453384197, year='2026', volume='44', issue='1', pageStart='1', pageEnd='246', issueExtLink='null', onlineDate='null', pubDate='1769270400000', pubDateStr='2026-01-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1790580078378, creator='13701087609', updateTime=1790588459421, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1311386304772927717, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1311351152067830064, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1311386304772927718, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1311351152067830064, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=11, endPage=14, ext={EN=ArticleExt(id=1311351203594859035, articleId=1311351203422892570, tenantId=1146029695717560320, journalId=1205116964453384197, language=EN, title=Application Research of Thermal Imaging Technology in Video Image River Flow Velocity Monitoring, columnId=null, journalTitle=Water Resources and Power, columnName=null, runingTitle=null, highlight=null, articleAbstract=

The video image flow monitoring technology has been applied in hydrological monitoring and irrigation area monitoring. Due to the limitation of received light, video image flow monitoring method has limitations in monitoring at conditions of night and low light. The thermal imaging was used to increase the spectral applicability of video flow measurement and compensate for the low applicability of video flow measurement under night conditions. By using a visible light and thermal imaging double-sided camera device mounted on a drone, the flow velocity field inversion results of visible light and thermal imaging camera devices under conditions of visible light and night were compared with the flow velocity monitoring data. The results show that under the condition of sufficient visible light during the day, the inversion effect of visible light video image flow velocity is better, and the accuracy error can reach within -5% except for a few monitoring points; Due to the limitation of its resolution, thermal imaging camera has a certain ability to capture natural tracers on the river surface, and has the ability and potential to invert the flow velocity field on the river surface. If missing particles of cold ice are added to the river section, the monitoring accuracy of thermal imaging at night can be significantly improved. Except for one monitoring point, the relative error of monitoring accuracy is 8.4%, and the accuracy of the other three monitoring points is relatively high, all around -1%. The research results can provide important references for improving the monitoring accuracy of video velocity measurement under conditions of nighttime and low light.

, authors=Zhao CAI¹, Min-han LIAO², Jiu-fu LIU¹, Hong-wei LIU¹, Shao-zhi CHU¹, Xing MIN¹, authorsList=Zhao CAI, Min-han LIAO, Jiu-fu LIU, Hong-wei LIU, Shao-zhi CHU, Xing MIN, authorCompany=null, correspAuthors=Hong-wei LIU, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1311351203905237532, articleId=1311351203422892570, tenantId=1146029695717560320, journalId=1205116964453384197, language=CN, title=热成像技术在视频图像河段流速监测中的应用研究, columnId=1207627659488632924, journalTitle=水电能源科学, columnName=水文水资源与环境, runingTitle=null, highlight=null, articleAbstract=

视频图像流速监测技术在水文监测、灌区监测中已有一定的应用，但由于受到光的限制，视频图像流速监测在夜晚和低光照条件下的监测存在局限性。为此，利用热成像增加视频测流的光谱适用范围，弥补视频测流在夜晚条件适用性不高的缺点，通过无人机搭载可见光和热成像双面摄像装置，对比了可见光条件下和夜晚条件下可见光和热成像摄像装置的流速场反演结果与流速仪监测数据。结果表明，在白天可见光充足条件下，使用可见光视频图像流速反演的效果较好，除去个别点监测精度误差可达到-5%以内；热成像相机由于自身分辨率的限制，对河道水面天然示踪物有一定的捕获能力，具有河道表面流速场的反演能力和潜力，若在河段中加入冷冰块失踪粒子，可明显提高热成像在夜间的监测精度，除去1个点监测精度的相对误差为8.4%外，其他3个点的精度较高，均在-1%左右。研究结果为提高视频测流在夜间和光照低条件下的监测精度提供了重要参考。

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蔡钊（1991-），男，高级工程师,研究方向为水文试验与水文仪器，E-mail: caizhao@nhri.cn

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蔡钊（1991-），男，高级工程师,研究方向为水文试验与水文仪器，E-mail: caizhao@nhri.cn

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