小型无人机垂直+倾斜立体对影像生成林冠DSM的生成

Kengo Sakai, Kouiti Hasegawa, T. Izumi, H. Matsuyama
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引用次数: 1

摘要

最近,利用小型无人机(UAV)进行摄影测量引起了人们的关注。SfM (Structure from Motion)方法可以从多个2D图像中创建3D点云和3D模型。此外,还可以从三维模型中生成正射影和数字曲面模型。有报道称,当目标为植被时,由于图像分辨率不足、植被在风中移动、图像中存在阴影区域等原因,点云的精度会降低。因此,本研究使用小型无人机拍摄的最低点+倾斜立体对图像创建了森林树冠的DSM。该研究于2015年7月在日本山梨县Yatsugatake山脚下的落叶松森林进行。一架带有数码相机的无人机在研究地点上空飞行,使用自动驾驶系统获取最低点和倾斜方向的冠状图像。我们首先生成密集的点云,然后根据三种模式生成正射影图和dsm:(1)在距地面100米的高度拍摄的70幅最低点图像;(2)(1)加上54张在离地50米高度拍摄的最低点图像;(3)(1)加上54张在离地50米高度拍摄的斜向图像。在模式(1)下,17.5%的面积没有点云,而模式(2)和模式(3)分别为12.8%和9.7%,没有点云。我们获得了所有三种模式的空间分辨率为2.0 ~ 2.5 cm的dsm。图(1)的DSM部分区域表面粗糙度较小;这些区域在模式(2)和(3)中减少。总之,本研究表明,与单独使用最低点图像相比,通过添加倾斜图像,dsm的再现性得到了改善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Generation of DSM of forest crown generated by vertical + oblique stereo pair images taken by small-sized UAV
Photographic surveying using a small-sized UAV (Unmanned Aerial Vehicle) has recently attracted attention. The SfM (Structure from Motion) method makes it possible to create 3D point clouds and a 3D model from multiple 2D images. Furthermore, an orthomosaic photograph and DSM (Digital Surface Model) can be generated from the 3D model. It has been reported that the precision of the point clouds becomes low when the target is vegetation due to insufficient resolution of images, the vegetation moving in the wind, and shadow areas in the images. This study, therefore, created a DSM of a forest crown using nadir+oblique stereo pair images taken by a small-sized UAV. The study was carried out in the larch forests at the foot of the Yatsugatake Mountains, Yamanashi Prefecture, Japan, in July, 2015. A UAV with a digital camera flew over the study site to acquire crown images in the nadir and oblique directions using an autopilot system. We first generated dense point clouds, from which we then generated orthomosaic photographs and DSMs following three patterns: (1) 70 nadir images taken at an altitude of 100m above the ground; (2) (1) plus 54 nadir images taken at an altitude of 50m above the ground; and (3) (1) plus 54 oblique images taken at an altitude of 50m above the ground. Under Pattern (1), 17.5% of the total area had no point clouds, while Patterns (2) and (3) showed 12.8% and 9.7%, respectively, with no point clouds. We obtained DSMs with a spatial resolution of 2.0∼2.5 cm for all three patterns. Some areas of the DSM of Pattern (1) showed less surface roughness; such areas decreased in Patterns (2) and (3). In conclusion, the present study demonstrates an improvement in the reproducibility of DSMs by adding oblique images in comparison with the use of nadir images alone.
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