利用无人机倾斜影像与GCP构建高精度侵蚀沟地形模型  

Establishment of high precision terrain model of eroded gully with UAV oblique aerial photos and ground control points

作　　者：冯林 李斌兵[1] 

机构地区：[1]武警工程大学信息工程学院,西安710086

出　　处：《农业工程学报》2018年第3期88-95,共8页Transactions of the Chinese Society of Agricultural Engineering

基　　金：国家自然科学基金项目"黄土丘陵区切沟侵蚀过程的三维数值模拟研究(41171224)"

摘　　要：为了提高侵蚀沟立体建模与监测的精度,该文采用消费级无人机作为低空遥感平台,以黄土高原一典型切沟为研究对象,通过无人机采集的倾斜影像与部署的地面控制点,采用多视立体运动恢复结构方法(structure from motion with multi-view stereo,Sf M-MVS)构建了高精度侵蚀沟表面模型,对其建模精度与数字高程模型、正射影像等成果进行分析,并与传统正射航图建模成果进行了比较。结果表明:构建的侵蚀沟稠密点云模型的水平均方根误差约为0.096 m,高程均方根误差约为0.018 m,满足1:500比例尺数字线划图与正射影像图的要求。与正射航图建模成果相比,高程误差减小了50%;侵蚀沟稠密点云的整体密度与地面激光雷达相当,且避免了后者多站拼接造成的密度不均问题。除了沟头部分的小块内凹区域,沟壁、沟头部分没有明显的空洞,植被覆盖的区域也能够正常建模。而正射航图的建模成果中在沟头内凹部分以及植被覆盖部分存在大块的空洞;由侵蚀沟的数字高程模型与等高线图可见,构建的侵蚀沟模型能够准确地反映切沟的形态特征。总体而言,该方法在侵蚀沟的高精度建模与监测方面具有显著优势,具有推广应用的潜力。In this paper, Sf M-MVS（structure from motion with multi-view stereo） method was introduced to construct a high precision terrain model of the typical gully on the Losses Plateau of northern Shaanxi in China, with oblique aerial photos acquired by a COTS（commercial off-the-shelf） UAV（unmanned aerial vehicle）（DJI INSPIRE-1） and 30 high-precision pre-deployed ground control points（GCPs） measured by FIFO A30 RTK（real-time kinematic）. A sequence of 194 oblique photos were captured by UAV camera with 70° pitch angle following a dual-Z shaped flight route, which were in comparison with 74 orthophotos captured by a nadir-point UAV camera in single Z shaped flight route. The photos were imported into Photo Scan software for terrain construction along with POS（position and orientation） information. Firstly, a preliminary alignment of aerial photos was performed as well as a rough estimation of camera parameters. The RMS（root mean square） reprojection error of tie points was 0.808 pixel and the maximum reprojection error was 41.143 5 pixel. Secondly, the corresponding projections of GCPs were marked on each photo and a set of GCP references were established in Photo Scan. Thirdly, camera estimation was iteratively optimized with high precision GCP references until errors of GCPs and reprojection errors of tie points met desired standard. After 4 iterations, the GCP errors were stabilized and its reprojection error was down to 0.538 pixel, and the RMS reprojection error of tie points also decreased to 0.51 pixel and its maximum reprojection error was down to 7.8 pixel. Fourthly, based on the optimized camera parameters and original aerial photos, depth image of each photo was calculated and a dense gully point cloud model consisting of 9 537 948 points was built through PMVS（patch-based multi-view stereo） algorithm in Photo Scan. And fifthly, the 30 GCPs were classified into 2 categories; 10 GCPs that numbered multiples of three were selected as check points to evaluate the overall accur

关 键 词：无人机 图像处理 模型 倾斜影像 侵蚀沟 多视立体运动恢复结构方法 

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