摘要
为探究海滩对风暴潮的响应过程,采用视频监测设备和计算机视觉方法,通过设立在岸边高处的Argus相机获取海岸带彩色图像,利用改进后的Canny算法结合双阈值处理法自动提取水边线,使用相机标定获得水边线地理坐标,对多时相的水边线进行高程插值,得到海岸线位置及海滩地形。通过对秦皇岛平水桥海滩的连续监测分析,发现平水桥海滩对风暴潮过程短时响应剧烈,泥沙向西、向海输移,滩肩明显冲刷,砂质粗化,潮间带整体淤积,海滩坡度变缓,岸线向海推进4.34 m;风暴潮后的恢复期,平水桥海滩岬角掩护岸段高潮带微冲而中低潮带淤积,泥沙离岸输移;平直岸段演变主要受中小恢复浪作用,呈现上淤下冲的态势,泥沙由中低潮带向高潮带输移。
In order to study the response process of storm surge on the beach,video monitoring and computer vision were used to obtain color images of the beach through several cameras set up on the shore high place.The improved Canny algorithm combined with dual threshold processing was used to automatically extract the shoreline. Used camera calibration to obtain the geographic coordinates of the shoreline. The multitemporal shorelines were interpolated to obtain the shoreline coordinates and beach topography. Through continuous monitoring and analysis,it was found that Pingshuiqiao beach in Qinhuangdao responded sharply to the storm surge process in a short time. Sediment was transported westward and toward the sea,the beach berm suffered obviously erosion and sand was coarsened.This caused the intertidal siltation, the beach slope decrease,and the coastline advancing 4.34 m toward the sea. In the recovery period after the storm surge,the high tide zone of Pingshuiqiao beach headland shield section was slightly eroded and silted in the middle and low tide zone,and the sediment was transported offshore. The evolution of the straight section is mainly affected by the small and medium recovery waves,which show the trend of upper siltation and lower erosion,and the sediment was transported from the middle and low tide zone to the high tide zone.
作者
匡翠萍
刘旭
夏子龙
朱磊
丛新
KUANG Cuiping;LIU Xu;XIA Zilong;ZHU Lei;CONG Xin(College of Civil Engineering,Tongji University,Shanghai 200092,China;Water Pollution Control Center of Longhua District,Shenzhen 518110,China;The Eighth Geological Brigade,Hebei Geological Prospecting Bureau,Qinhuangdao 066000,China)
出处
《同济大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2022年第7期1009-1016,共8页
Journal of Tongji University:Natural Science
基金
国家自然科学基金(41776098)
国家重点研发计划(2019YFC1407900)。
关键词
计算机视觉
视频监测
水动力模型
风暴潮
computer vision
video monitoring
hydrodynamic model
storm surge
