基于无人机低空遥感和现场调查的潮滩地形反演研究  

Inversion of tidal flat topography based on unmanned aerial vehicle low-altitude remote sensing and field surveys

作　　者：李阳[1] 袁琳[1,2] 赵志远[1] 张晋磊 王宪业 张利权 LI Yang;YUAN Lin;ZHAO Zhiyuan;ZHANG Jinlei;WANG Xianye;ZHANG Liquan(State Key Laboratory of Estuarine and Coastal Research,Institute of Eco-Chongming,East China Normal University,Shanghai 200241,China;Yangtze Delta Estuarine Wetland Ecosystem Observation and Research Station(Ministry of Education&Shanghai Science and Technology Committee),Shanghai 202162,China)

机构地区：[1]华东师范大学河口海岸学国家重点实验室,崇明生态研究院,上海200241 [2]长江三角洲河口湿地生态系统教育部/上海市野外科学观测研究站,上海202162

出　　处：《自然资源遥感》2021年第3期80-88,共9页Remote Sensing for Natural Resources

基　　金：国家自然科学基金项目“长江口盐沼湿地生态系统稳态转换过程与机制研究”(编号:41876093);交通运输行业重点科技项目“长江口南槽生态航道建设技术研究”(编号:2019-MS5-106);上海市科委科研计划项目“长江河口滩涂生态脆弱区监测与安全预警关键技术”(编号:20dz1204701)共同资助。

摘　　要：潮滩地形与滩涂湿地生态系统的结构和功能密切相关,准确获取高精度的地形数据,对于分析潮滩的冲淤动态和盐沼植被扩散过程具有十分重要的意义。受自然潮滩观测时间有限、观测条件恶劣及植被覆盖等因素影响,传统的潮滩地形监测方法往往存在操作困难、效率较低、成本过高及覆盖范围有限等不足。文章通过无人机低空遥感方法获取航拍影像与其波段信息,基于运动结构技术提取影像三维坐标信息,构建研究区高精度数字表面模型(digital surface model,DSM),利用DSM模型直接获得无植被覆盖的光滩数字高程模型(digital elevation model,DEM);对于有盐沼植被覆盖的区域,利用红、绿、蓝3个可见光波段信息计算可见光差异植被指数(visible-band difference vegetation index,VDVI),同时结合野外现场调查,获取潮滩盐沼植物株高与VDVI指数的定量关系,建立株高反演模型;并利用株高反演模型从DSM中滤除植被,准确反演出潮滩植被区的DEM,从而整体获得潮滩地形的反演结果。结果表明,结合无人机低空遥感和现场调查的方法可以较好地实现对潮滩地形的精确反演:光滩区地形均方根误差为0.07 m,其精度与高精度三维激光扫描仪测量结果接近;经过植被滤除后,潮滩植被区地形均方根误差下降到0.14 m,数据精度可提升60%,优于传统的点云过滤方法。文章提供了一种基于无人机和现场调查的潮滩地形反演方法,实现了潮滩地形高效、大范围的监测,研究方法可应用到其他类似的潮滩或海岸区域,为海岸带滩涂湿地保护和管理提供重要的技术支撑。Tidal flat topography is closely related to the structure and function of the ecosystem in intertidal wetlands.Therefore,it is significant for the analyses of tidal flat dynamics and the monitoring of the diffusion process of saltmarsh vegetation to obtain high-precision topography data.However,owing to limited ebb time,muddy tidal flats,and saltmarsh vegetation,traditional geographic observation techniques suffer the shortcomings such as low accuracy and efficiency,high cost,and limited coverage.In this study,unmanned aerial vehicle(UAV)low-altitude remote sensing was employed to obtain aerial images and their band information.Then the 3D and spectral information with precise coordinates were extracted based on the structure obtained using motion technology.They were used to construct a high-precision digital surface model(DSM)of the study area.The DSM of bare flats can be directly used as the digital elevation model(DEM)of the tidal flat.In the areas with saltmarsh vegetation,the information of red,green,and blue bands was used to calculate the visible-band vegetation index(VDVI),which was combined with field surveys to build an inversion model for vegetation height.Finally,vegetation was filtered out from the DSM using the height inversion model to obtain accurate DEM.In this way,the elevation of the vegetation zone in the tidal flat can be reflected.As indicated by the results of this study,the method that combines UAV low-altitude remote sensing with field surveys can realize precise inversion of tidal flat topography.The root mean square error(RMSE)of the topography in bare flat obtained using the method was 0.07 m and the accuracy was close to the terrestrial laser scanner(TLS).For areas with saltmarsh vegetation,the RMSE was reduced to 0.14 m and the geographical accuracy can be improved by 60%after the vegetation was filtered out.Therefore,the method is superior to traditional point cloud filtering.Overall,this study provided an inversion method of tidal flat topography based on UAV remote sensing and fi

关 键 词：潮滩 地形 无人机 滤除植被 可见光植被指数 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置]