Drone-derived 2 cm orthomosaics for selected reefs in the Far North region of the Great Barrier Reef, Australia December, 2017
收藏Mendeley Data2023-01-14 更新2024-06-27 收录
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https://doi.pangaea.de/10.1594/PANGAEA.892876
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Orthomosaics for this project were created using Structure-from-Motion (SfM) algorithms from drone-derived imagery. The resultant orthomosaics have 2 cm resolution and are georeferenced to the GDA94 MGA zone 54 coordinate system. Positional accuracy is subject to errors from the on-board GPS and estimated between 5-10 m.
GeoTiff data is available and can be requested. Please email the author (jleon@usc.edu.au) and provide a brief paragraph as to the intended use of the data.
Images were acquired with a DJI Mavic Pro drone (< 2 kg) at 50 m altitude using DJI Ground Station Pro mission planner. The drone was operated as part of a GBRMPA accredit institution (University of Queenland).
The following were considered to improve image quality over water:
- The camera was tilted 10 degrees off nadir
- 90% forward / 60% side overlap was used
- Flights were undertaken only when wind was < 15 knots
- Sun azimuth was kept away from the flight direction to reduce glint
- Flights were mostly undertaken before midday to reduce glint, although this was not always possible. Similarly, timing low tide levels was not always possible.
Images were processed using Agisoft Photoscan 1.4.3 software using the following steps/parameters:
- Alignment: Highest accuracy
- Resultant sparse point cloud was cleaned selectively and manually.
- Build Dense cloud: High quality, Aggressive depth filtering
- Calibrate colours: source data - model, no white balance correction
- Build Texture: Generic mapping mode
- Build DEM: source dense cloud, resolution - 0.02 m/pix, projection - GDA94 MGA zone 54
- Build Orthomosaic: Surface - DEM, resolution - 0.02 m, projection - GDA94 MGA zone 54
本项目的正射镶嵌影像通过基于无人机影像的运动恢复结构(Structure-from-Motion, SfM)算法生成。生成的正射镶嵌影像分辨率为2厘米,且采用GDA94 MGA第54带坐标系进行地理配准。其定位精度受机载GPS误差影响,估计误差范围为5至10米。
GeoTiff格式数据可申请获取,请发送邮件至作者邮箱jleon@usc.edu.au,并简要说明数据的预期用途。
影像采集采用DJI Mavic Pro无人机(重量小于2千克),飞行高度为50米,使用DJI Ground Station Pro任务规划软件进行作业。本次飞行作业由获得GBRMPA资质的机构——昆士兰大学(University of Queensland)执行。
为提升水面区域的成像质量,本次作业采用以下策略与参数:
- 相机偏离天底角倾斜10度
- 航向重叠率设为90%,旁向重叠率设为60%
- 仅在风速低于15节时开展飞行作业
- 调整太阳方位角使其与飞行方向错开,以减少水面反光
- 多数飞行作业安排在午前进行以降低反光,但该条件并非总能满足;同理,选择低潮时段进行拍摄也难以始终实现。
影像处理采用Agisoft Photoscan 1.4.3软件,具体流程与参数如下:
- 影像匹配:最高精度模式
- 对生成的稀疏点云进行选择性手动降噪清理
- 生成密集点云:高质量模式,启用强深度滤波
- 色彩校准:以模型为源数据进行色彩校正,不执行白平衡修正
- 生成纹理:通用映射模式
- 生成数字高程模型(DEM):以密集点云为源数据,分辨率为0.02米/像素,投影坐标系为GDA94 MGA第54带
- 生成正射镶嵌影像:以DEM为表面模型,分辨率为0.02米,投影坐标系为GDA94 MGA第54带
创建时间:
2023-01-14



