基于PhotoScan的径流小区三维重建参数优化  

Process Optimization of Runoff Plot 3D Reconstruction Based on PhotoScan

作　　者：张兴义[1,2] 甄怀才 JAMES R Mike 杨薇 张晟旻 李浩[2] ZHANG Xingyi;ZHEN Huaicai;JAMES R Mike;YANG Wei;ZHANG Shengmin;LI Hao(College of Resources and Environmental Sciences,Northeast Agricultural University,Harbin 150030,China;Key Laboratory of Mollisols Agroecology,Northeast Institute of Geography and Agroecology,Chinese Academy of Sciences,Harbin 150081,China;Lancaster Environment Centre,Lancaster University,Lancaster LA14YQ,UK;Heilongjiang Province Hydraulic Research Institute,Harbin 150081,China;University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]东北农业大学资源与环境学院,哈尔滨150030 [2]中国科学院东北地理与农业生态研究所黑土区农业生态重点实验室,哈尔滨150081 [3]兰卡斯特大学环境中心,兰开夏郡LA14YQ [4]黑龙江省水利科学研究院,哈尔滨150081 [5]中国科学院大学,北京100049

出　　处：《农业机械学报》2019年第12期144-150,230,共8页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家重点研发计划项目(2017YFC0504200);国家自然科学青年基金项目(41601289)

摘　　要：提高径流小区数字地面模型精度是应用三维重建技术研究面蚀细沟间与细沟侵蚀过程的关键。以位于黑龙江省海伦市的中国科学院海伦水土保持监测研究站的裸地小区为研究对象,以验证点与控制点误差比和数字高程模型(Digital elevation model,DEM)误差为指标,优化Agisoft PhotoScan三维重建径流小区的处理参数,降低DEM误差。PhotoScan的精度参数和相机模型设置对DEM误差有较大影响。优化后的验证点与控制点误差比降低35%,改善了径流小区DEM对地面控制点的过度拟合。优化后的相机模型包含焦距、像主点、径向畸变、切向畸变等。基于单点和点云的验证结果表明,优化过程误差降低约40%。相对于默认参数设置下的验证点误差(20.0 mm),优化后的验证点误差为11.0 mm,与细沟侵蚀深度标准相当(沟深大于等于10 mm),因此优化后的径流小区三维重建过程更适宜于细沟侵蚀过程的三维表达。Structure-from-motion with multi-view stereo(SfM MVS)facilitates the acquisition of photos by unmanned aerial vehicle(UAV)to generate the DEM and has been gradually applied to research on surface change processes such as channel erosion and slope erosion.Improving the DEM accuracy of the runoff plot is essential for investigating the interrill and rill erosion process by using SfM MVS 3D reconstruction technology.The runoff plot 3D reconstruction process using Agisoft PhotoScan was optimized to improve DEM accuracy.The study was carried out in the bare land plot(4.5 m wide and 20.0 m long)at the Hailun Soil and Water Conservation Monitoring and Research Station of Chinese Academy of Sciences.Before the ploughing in spring of 2019,totally 7 and 30 measured points were evenly distributed around the outside and inside the plot,and the 3D coordinates were measured by using differential global positioning system(dGPS).Using the Phantom 4 Pro UAV,42 photos covering the runoff plot were taken,and the shooting height was 3.5 m.Each photo covered the width of the runoff and the UAV was gradually moved along the runoff to take the next photo.The results proved that potentially DEM accuracy improvement existed for the commercial SfM MVS 3D reconstruction software by optimizing parameters.Within the PhotoScan,the appropriate processing setting parameters were determined by evaluating the image observation accuracy of the tie point and the ground measurement point,in order to weaken the DEM s over-fitting to the tie points or the ground measurement point.For the default parameter,the check point to control point error ratio was 1.95,and the optimized value was 1.26,which was reduced by 35%.Then,the camera models in PhotoScan were evaluated and the results showed that the 3rd model could reduce the error ratio between the check points and the control points,although the difference among different camera models was small.After the optimization process implementation,the DEM error was reduced by about 40%,both by point verificat

关 键 词：径流小区 三维重建 参数优化 误差 黑土区 

分 类 号：P231.2[天文地球—摄影测量与遥感] S157.1[天文地球—测绘科学与技术]