Aerial images collected by an Unmanned Aerial Vehicle in Hermitage, Réunion - 2023-12-07

This dataset was collected by an Unmanned Aerial Vehicle in Hermitage, Réunion - 2023-12-07. Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation. These images can be annotated and shared to train IA models which can in turn predict the objects on the images. We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps. This dataset is part of larger collection referencing numerous underwater and aerial images Seatizen Altas. Methods, tools and scientific objectives are also described in a dedicated data paper. Survey information Camera: Hasselblad L1D-20c Number of images: 720 Total size: 6.45 Gb Flight start: 2023:12:07 02:30:34 Flight end: 2023:12:07 03:03:49 Flight duration: 0h 33min 15sec Median height: 59.9 m Area covered: 14.22 a Photogrammetry OpenDroneMap software was used to create an orthophoto from the raw images. Here is the list of parameters different from the default values for the orthophoto generation. For more details, you can read the log.json file or the 000_photogrammatry_report.pdf report. {'auto_boundary': True, 'cog': True, 'fast_orthophoto': True, 'feature_quality': 'ultra', 'max_concurrency': 128, 'optimize_disk_space': True, 'orthophoto_resolution': 1.0, 'rolling_shutter': True, 'skip_3dmodel': True, 'use_exif': True} Generic folder structure YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number ├── DCIM : folder to store videos and photos depending on the media collected. ├── GPS : folder to store any positioning related file. If any kind of correction is possible on files (e.g. Post-Processed Kinematic thanks to rinex data) then the distinction between device data and base data is made. If, on the other hand, only device position data are present and the files cannot be corrected by post-processing techniques (e.g. gpx files), then the distinction between base and device is not made and the files are placed directly at the root of the GPS folder. │ ├── BASE : files coming from rtk station or any static positioning instrument. │ └── DEVICE : files coming from the device. ├── METADATA : folder with general information files about the session. ├── PROCESSED_DATA : contain all the folders needed to store the results of the data processing of the current session. │ ├── BATHY : output folder for bathymetry raw data extracted from mission logs. │ ├── FRAMES : output folder for georeferenced frames extracted from DCIM videos. │ ├── IA : destination folder for image recognition predictions. │ └── PHOTOGRAMMETRY : destination folder for reconstructed models in photogrammetry. └── SENSORS : folder to store files coming from other sources (bathymetry data from the echosounder, log file from the autopilot, mission plan etc.). Software All the raw data was processed using our worflow. All predictions were generated by our inference pipeline. You can find all the necessary scripts to download this data in this repository. Enjoy your data with SeatizenDOI!本数据集由无人驾驶航空器（Unmanned Aerial Vehicle）于留尼旺岛（Réunion）埃米塔日（Hermitage）于2023年12月7日采集。 科研人员与民众采集的水下及航空影像可广泛应用于科学研究、资源管理与生态保护领域。此类影像可通过标注与共享，用于训练人工智能（Intelligence Artificielle）模型，以实现影像内目标的识别预测。 本项目提供一套软硬件工具集，可用于海洋数据采集、物种与生境识别预测及地图制作。 本数据集隶属于涵盖海量水下与航空影像的大型数据集集合Seatizen图集（Seatizen Atlas）。相关方法、工具及科学目标已在专门的数据集研究论文中详细说明。 ## 调查信息 - 相机型号：哈苏（Hasselblad）L1D-20c - 影像总数：720张 - 总数据量：6.45 GB - 飞行起始时间：2023-12-07 02:30:34 - 飞行结束时间：2023-12-07 03:03:49 - 飞行时长：0小时33分钟15秒 - 飞行高度中位数：59.9米 - 覆盖面积：14.22公亩 ## 摄影测量 本研究采用OpenDroneMap软件基于原始影像生成正射影像。以下为正射影像生成过程中与默认参数存在差异的配置项列表： {'auto_boundary': True, 'cog': True, 'fast_orthophoto': True, 'feature_quality': 'ultra', 'max_concurrency': 128, 'optimize_disk_space': True, 'orthophoto_resolution': 1.0, 'rolling_shutter': True, 'skip_3dmodel': True, 'use_exif': True} 如需获取更多细节，请查阅log.json文件或000_photogrammetry_report.pdf报告。 ## 通用文件夹结构 命名格式：YYYYMMDD_国家代码-[可选地点]_设备_会话-编号 ├── DCIM：用于存储采集所得的视频与照片文件的目录。 ├── GPS：用于存储所有定位相关文件的目录。若可对文件进行各类校正（例如基于星历数据（rinex data）进行后处理运动学校正），则需区分设备数据与基准站数据；若仅存在设备位置数据且无法通过后处理技术校正文件（例如gpx格式文件（gpx files）），则无需区分基准站与设备数据，文件直接存放于GPS目录根目录下。 │ ├── BASE：来自RTK基准站（RTK station）或其他静态定位仪器的文件。 │ └── DEVICE：来自采集设备的文件。 ├── METADATA：用于存储本次采集会话通用信息文件的目录。 ├── PROCESSED_DATA：用于存储本次会话数据处理结果的所有子目录。 │ ├── BATHY：从任务日志中提取的水深原始数据的输出目录。 │ ├── FRAMES：从DCIM目录下的视频中提取的地理参考帧的输出目录。 │ ├── IA：用于存放图像识别预测结果的目录。 │ └── PHOTOGRAMMETRY：用于存放摄影测量重建模型的目录。 └── SENSORS：用于存储其他来源文件的目录（例如回声测深仪获取的水深数据、自动驾驶仪日志文件、任务规划文件等）。 ## 软件 所有原始数据均通过本团队开发的工作流进行处理，所有预测结果均由本团队的推理流水线生成。您可在本代码仓库中获取下载该数据集所需的全部脚本。祝您使用SeatizenDOI愉快！